consultancy report on health financing - cambodia

Table of contents

ContentsSection 1- Introduction to the project and progress as per TOR..................................................5

1.1. Background and context....................................................................................................5

1.2. Major Components of the program.......................................................................................5

1.3. Scope of the Assignment.......................................................................................................6

1.4. Reporting Requirements........................................................................................................7

1.5. Objectives and organization of the report............................................................................7

1.6. Progress as per the TOR.......................................................................................................8

Section 2: Works carried out for Service Delivery Grants (SDG)...............................................13

2.1. Introduction............................................................................................................................13

2.2. Activities carried out..............................................................................................................13

2.2.1. Tasks assigned and completed....................................................................................13

2.3. Conclusion..............................................................................................................................14

List of Annexures..............................................................................................................................15

Annex 2.1, 2.2 and 2.5: (soft copy in the CD). In addition to these annexes there are several other files related to data used in the estimation process.........................................15

Annex 2.3: Allocation of Funds – User’s Guide to Methodology for Allocation of SDGs across the Provinces given below..............................................................................................15

Annex 2.4: Calculation of Cambodia Service Delivery Grants - User's Guide – Text given below (soft copy in CD)................................................................................................................22

Annex 2.6, 2.7, 2.8 and 2.9 – Four alternative models with different weights assigned (soft copies in CD).................................................................................................................................27

Annex 2.10: Minutes of the meeting on 5th January 2011 – Soft copy in CD........................27

Annex 2.11– Presentations made on 5th January 2011 - soft copy in CD.............................27

Annex 2.12– Presentations made on 5th January 2011 - soft copy in CD.............................27

Annex 2.13: Minutes of Meeting on SDG Progress – soft copy in CD..................................27

Annex 2.14: Presentation on SDG allocation on 17th October 2011......................................27

Annex 2.15: Allocation of SDG for 2012-13 suggested methodology....................................27

Annex 2.16a and 2.16b: Base data used for SDG Estimates (Soft copy in CD)..................27

Annex 2.17: Population Projection by OD.................................................................................27

Annex 2.18: Population projection by province.........................................................................27

Section 3- Works carried out for Health Equity Fund (HEF).......................................................28

3.1. Introduction............................................................................................................................28

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3.2. Activities carried out..............................................................................................................28

3.2.1. Phase 1 of activities related to HEF............................................................................28





3.2.6. Final activities related to HEF.......................................................................................33

3.2.7. Additional Tasks completed..........................................................................................33

3.3. Problems and Constraints........................................................................................................34

List of Annexures..............................................................................................................................35

Annex 3.1 – The base file on HEF collected from BHEF-DPHI (soft copy in CD)...............35

Annex 3.2, 3.3, 3.4 and 3.5: Estimated models – different simulation and modifications in different dates. The final copy is Annex 3.5 presented to JPIG on 25th March 2011 (soft copy of files in CD)........................................................................................................................35

Annex 3.6.: Detailed methodology given in a power point presentation (soft copy in CD). 35

Annex 3.7: Minutes of Meetings held on HEF Allocation on 25th March 2011. (Hard and soft copy in CD).............................................................................................................................35

Annex 3.8: SOA Manual revision (soft copy provided in CD).................................................35

Annex 3.9: A detailed analysis of HEF 2007-2010 (soft copy in CD)....................................35

Annex 3.10a –3.10M (soft copy of all the data collected and cross checked with the earlier information collected from URC).................................................................................................35

Annex 3.11a, 3.11b: Soft copy of the model provided for your reference.............................35

Annex 3.12: Soft copy of the HEF estimates provided for reference,....................................35

Annex 3.14 – soft copy of the model presented to AFD, and.................................................35

Annex 3.15: Power point presentation on methodology for target setting, costing and assumptions – soft copy of the presentation for your reference)...........................................35

Annex 3.16 – : Estimated model for 2012 with HC and RH separately and Cost of CPA1, 2 and 3 separately- soft copy in CD...............................................................................................35

Annex 3.17 – Minutes of meeting on 27th June- soft copy in CD............................................35

Annex 3.18a and 3.18b– HEF Expansion Plan – soft copy in CD.........................................35

Annex 3.19 – HEF expansion and costing for Dr Kiry– soft copy in CD................................35

Annex 3.20- Model used for costing the outputs – Soft Copy in CD......................................35

Annex 3.21: HEF Expansion Plan – User’s Manual.................................................................36

Section 4: Works carried out for Hospital Costing Study.............................................................55

4.1. Introduction............................................................................................................................55

Annex 4.1: Costing template for hospital costing – soft copy for your reference.................55

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Annex 4.2: Proposal for piloting – hard copy inserted and soft copy in CD).........................56

Project Officer............................................................................................................................64

Section 5: Works carried out on Health Financing – PMR..........................................................75

5.1. Introduction............................................................................................................................75

Annexures......................................................................................................................................75

Annex 5.1 – Health Care Financing in Cambodia – Progress during 2010..........................75

Annex 5.2 – Text given below and soft copy in CD..................................................................91

Health Care Financing in Cambodia – Bi-annual Progress 2011 (for PMR).........................91

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Section 1- Introduction to the project and progress as per TOR

1.1. Background and contextThe Royal Government of Cambodia received a credit from the International development Association (IDA) to a tune of US $30 million, together with grants of $50 million from the U.K. Department for International Development (DFID), $30 million from the Australian Agency for International Development (AusAID), and additional funding from Agence Francaise de Development (AFD), Belgian Technical Cooperation (BTC), U.N. Children's Fund (UNICEF), and the U.N. Population Fund (UNFPA). This funding, along with counterpart funds from the Royal Government of Cambodia, is financing the Second Health Sector Support Program (HSSP2) since 2009 and expected to continue till 2013. The activities under the program are being implemented under the overall supervision and responsibility of the Ministry of Health (MoH) of the Royal Government of Cambodia.

The funding arrangements under HSSP2 are basically of two types: (a) Pooled funds: - contributed by IDA/World Bank, DFID, AusAID, and UNICEF and UNFPA, and, (b discrete funds1: - funding from UNFPA, UNICEF, AID and BTC. All partners have adopted common management arrangements, set out in a Joint Partnership Arrangement.

The Program’s objective is to support the implementation of Cambodia's Second Health Strategic Plan (HSP2), 2008-15 that aims to ensure improved and equitable access to, and utilization of, essential quality health care and preventive services with particular emphasis on women, children and the poor. The Program's development objective is to support the implementation of HSP2 so as to improve health outcomes through strengthening institutional capacity and mechanisms by which the Government and development partners can achieve more effective and efficient sector performance.

1.2. Major Components of the programA. Strengthening health service delivery through: (a) the provision of Service Delivery

Grants (SDG) and internal contracting for health services at provincial levels and below; and (b) strengthening health services management, supervision, and public health functions at provincial and operational district levels; and (c) investments for the improvement, replacement, and extension of the health service delivery network

B. Improving health financing by supporting: (a) health protection for the poor (Social Health Protection) through the consolidation of Health Equity Funds (HEF) under common management and oversight arrangements, and expansion of coverage of the same for the entire country; and (b) supporting the development of health financing policies and institutional reforms

C. Strengthening human resources that will focus on: (a) strengthening pre- and in-service training and supporting enrolments where shortages exist; (b) strengthening human resources management in the MoH; and (c) supporting the merit based performance incentive scheme for health managers and key technical staff participating in the implementation of HSP2 at central and provincial levels

D. Strengthening health system stewardship functions by supporting (a) the development of policy packages identified for strengthening institutional capacity, particularly for meeting the demands of the RGC's decentralization and de-concentration policy; (b) private sector regulation and partnerships; (c) supporting

1 Discrete funds are the funds that are under the exclusive disposal of the donor’s account. Any decision regarding the disbursement and spending is made by the donors exclusively. In that matter if any activity that is to be funded from the discrete fund the requests are to be made from the MoH.

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governance and stewardship functions of national programs and centers overseeing the three HSP2 strategic programs; and (d) strengthening community participation.

As part of HSSP2 implementation of component B above, the MOH recruited a Health Financing Adviser, initially for a period of 2 years starting from June 1, 2010 through May 31, 2012 with the possibility of extension subject to availability of funds. Through it was proposed to appoint from June 2010, due to delay in the processes I joined as Health Financing Advisor during November 2010. My first term of contract was from 15th

November 2010 to 14th November 2011 with the possible extension as is mentioned above. Unfortunately, because of my personal circumstances I completed the first term and requested the competent authority for the discontinuation of my contract further. The position was funder from HSSP2 discrete funds, specifically the grant from the Agence Francaise de Development (AFD).

1.3. Scope of the Assignment As the health financing advisor I was responsible for the following:

I. Providing technical assistance to the Bureau of Health Economics and Financing (BHEF) of the Department of Planning and Health Information (DPHI) in the formulation of a detailed implementation plan for areas within the responsibility of the MOH under the RGC's Master Plan for Social Health Protection . This includes design (benefit package, provider payment methods and other major components), oversight, and monitoring of demand-side financing schemes.

II. Providing technical assistance to the BHEF/DPHI for the scaling up and national roll out of Health Equity Fund schemes for the poor, and implementation and monitoring of community based health insurance schemes (CBHI)

III. In collaboration with senior staff of the BHEF/DPHI and other technical assistance, conducting in depth analysis of current financing of health facilities and formulating alternative financing schemes based on key criteria such as effectiveness, efficiency, equity, sustainability, and policy and administrative feasibility

IV. In collaboration with senior staff of the BHEF/DPHI and other technical assistance, examining pricing policies at the different types of health facilities, including CPA1, 2, and 3 referral hospitals, and health centers with and without beds and recommending appropriate policy options

V. In collaboration with senior staff of the BHEF/DPHI, HSSP2 Secretariat, and other technical assistance, (a) determining the required amount of resources for scaling up of Service Delivery Grants (SDGs) across the sector, (b) establishing the sustainable amounts of SDGs for each type of health facility as mentioned in item (iv) above, and (c) examining different options for financing SDGs with appropriate recommendations for policy options

VI. Providing technical support for the design and implementation of a comprehensive health financing policy for public health facilities, including suitable modifications for application at each service delivery level: health center, referral hospital, and national hospitals including semi-autonomous institutions

VII. Assisting the BHEF/DPHI in the drafting and production of the MOH's Annual Health Financing Report, including conducting in depth analysis of sector financing policies and schemes, as deemed necessary

VIII. Assisting the BHEF/DPHI in the design and implementation of monitoring of health financing schemes including small sample surveys as required

IX. Participating in the preparatory and final meetings for the Joint Annual Plan Appraisal and the Joint Annual Performance Review, and assisting the BHEF/DPHI with preparation of relevant analyses and reports for both events

X. Working in close collaboration with other technical assistants in the MOH to provide technical support for the design and implementation of internally contracted schemes

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for service delivery including the monitoring of SOA activities and performance based contacts.

XI. Providing capacity building to the BHEF/DPHI staff as determined by Director/DPHIXII. Conducting site visits to provincial and operational district offices and service delivery

points to monitor smooth functioning of health financing schemesXIII. Collaborating closely with the HSSP2 Secretariat and directly contributing to the

preparation of the health financing sections of the HSSP2 Performance Monitoring Reports on a semi-annual basis, and participating in the HSSP2 Joint Quarterly Meetings and meetings in connection with the Joint Review Missions

XIV. Handling any other tasks that may reasonably be assigned by the Program Coordinator/ Director, DPHI

1.4. Reporting Requirements The HF Adviser will be based in the BHEF/DPHI and will report to the Program Director/Coordinator for overall guidance and fulfilling contractual obligations. On a day to day basis the consultant will work closely with Director/DPHI, and senior staff of the BHEF/DPHI, and be guided by them on key outputs and deliverables to be produced. S/he will also liaise closely with other technical assistants based at DPHI to ensure that DPHI tasks are successfully completed.

To be brief, I was appointed for two major components of the program i.e., Component A and B. How the TOR is too extensive and it is not possible to fulfill all of them unless there is proper institutional arrangement and inter-sectorial coordination across the line ministries.

1.5. Objectives and organization of the reportThe objectives of the report are as follows: Giving a detailed overview of the works that I did during my tenure of my contract i.e., 15th November 2010 to 14th November 2011 related to the following areas of Health Financing in Cambodia:

1. Works related to services delivery grants (Section - 2 of the document) –This part of the report describes the works and progress done on Service Delivery Grants (SDG) to the Special Operating Agencies (SOA) Operational Districts (ODs).

2. Works related to Health Equity Fund (HEF) and Hospital Costing (Section - 3 of the document)

3. Section 4 of the document reports the activities carried out for hospital costing study. 4. Section 5 reports the works related to Health Financing as part of PMR.

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1.6. Progress as per the TORTerms of Reference as in contract Objectively Verifiable Indicators (OVI) –

Proof of all documents provided in AnnexesComments and recommendations

Providing technical assistance to the Bureau of Health Economics and Financing (BHEF) of the Department of Planning and Health Information (DPHI) in the formulation of a detailed implementation plan for areas within the responsibility of the MOH under the RGC's Master Plan for Social Health Protection. This includes design (benefit package, provider payment methods and other major components), oversight, and monitoring of demand-side financing schemes.

1. Model on resource allocation Criteria (explained in section on SDG)

2. User Guides to the models prepared for SDG3. HEF allocation model (explained in Section 3)4. HEF allocation model Manual -1 (Section 3)5. HEF expansion plan and designed computerised

software (explained in Section 3)6. Proposal submitted for the pilot study on Hospital

coasting along with the methodologies and tools (Section 4)

7. Data collection tools and tools for the analysis of costing data (Section 4)

8. Final proposal on costing submitted to the supervisor for the approval of the project director (Section 4)

9. Approval letter by the project director and letters issued to sample hospitals (Section 4)

Note: All these documents are submitted to the secretariat either in hard or soft copy

Designing the benefit package for the poor people needs scientific evidence. Presently the study on Hospital costing is being carried out and it is expected to be finished by the end of March /2nd week of April 2012. The standard benefit package can be developed after the completion of the study. However, I am happy that I have initiated the activities towards this end and have been successful.

Providing technical assistance to the BHEF/DPHI for the scaling up and national roll out of Health Equity Fund schemes for the poor, and implementation and monitoring of community based health insurance schemes (CBHI)

1. Methodology for calculation of Unit cost for HEF (Section 3)

2. HEF Expansion plan for 2012-2015 (Section 3)3. User’s Manual for HEF expansion plan (Section

3)4. Rolling out requires adequate funding from the

government. The level of government funding during 2010 and 2011analysed in the Health Financing Section of the report (Section –5)

Scaling up the national roll out of HEF schemes is a political decision and needs appropriate organisational setup across the ministries (i.e., MoH, Ministry of Labour, Ministry of Planning, Ministry of Economic and Finance and Ministry of Social Affairs). It is strongly recommended to have inter- ministerial collaborations for the successful implementation of the schemes.

In collaboration with senior staff of the 1. Health Financing Report 2010 submitted to JPIG as part of PMR (Section –5)

Health is the basic human right and should be funded adequately by the Government.

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Terms of Reference as in contract Objectively Verifiable Indicators (OVI) – Proof of all documents provided in Annexes

Comments and recommendations

BHEF/DPHI and other technical assistance, conducting in depth analysis of current financing of health facilities and formulating alternative financing schemes based on key criteria such as effectiveness, efficiency, equity, sustainability, and policy and administrative feasibility

2. Health Financing Report 2011 (Semi Annual) submitted to JPIG as part of PMR (Section – 5)

As far as the current arrangement is concerned, a chunk of the funding comes from the donors and as the evidence and discussion with key staff of the hospitals goes, it is commonly agreed phenomenon that HEF funds are being grossly misused at many places just by increasing ALOS. Government need to have strict regulation and provision for adequate funding for staff salaries to have control over the situation.

In collaboration with senior staff of the BHEF/DPHI and other technical assistance, examining pricing policies at the different types of health facilities, including CPA1, 2, and 3 referral hospitals, and health centres with and without beds and recommending appropriate policy options

1. Proposal for hospital costing study (Section – 4)2. The methodology developed to collect the data (Section – 4)3. The software developed (Cost It for Hospitals) for the analysis of data in the Cambodian context (Section – 4)

The pricing policies mostly depend on scientific investigation of the present pricing policy and design the new mechanism (if desired) on the basis of scientific evidences. The hospital costing study will through appropriate insights towards this end.

In collaboration with senior staff of the BHEF/DPHI, HSSP2 Secretariat, and other technical assistance, (a) determining the required amount of resources for scaling up of Service Delivery Grants (SDGs) across the sector, (b) establishing the sustainable amounts of SDGs for each type of health facility as mentioned in item (iv) above, and (c) examining different options for financing SDGs with appropriate recommendations for policy options

1. Proposed SDG estimate for 2012-13 (Section – 2)2. Proposal for government to fund the SDG in a phased manner (Participated in almost all the discussion with the partners but no plan for future expansion – Section -2)3. Presentation made on 17th October 2011(Section–2)

Presently the SDG is funded by HSSP2 through the grants from development partners. The funding is assured till 2013. At present the HSSP secretariat does not have any plan for scaling up the SDGs to more SOAs. However, the decision on the expansion of SDG lies with the policy makers and provision for funding. This needs inter sectorial coordination across the ministries.

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Providing technical support for the design and implementation of a comprehensive health financing policy for public health facilities, including suitable modifications for application at each service delivery level: health center, referral hospital, and national hospitals including semi-autonomous institutions

1. Proposal for piloting the hospital costing study2. Report of the hospital piloting study (Section – IV)3. Proposal for costing 9 referral hospitals (CPA1 2 and 3)3. Checklist for data collection4. Computerised software for data analysis

It is hoped that after the hospital costing study an appropriate Provider Payment Mechanism (PPM) and fee structure for the hospitals developed and implemented. In the absence of PPM It is difficult to have a robust health financing policy for the health sector. It may take next few years to have that for the MoH.

Assisting the BHEF/DPHI in the drafting and production of the MOH's Annual Health Financing Report, including conducting in depth analysis of sector financing policies and schemes, as deemed necessary

1. Detailed health financing report for the year 2010 (as part of PMR) submitted to HSSP2 secretariat (Section –V)

The funding and disbursement from the government should increase substantially.

Assisting the BHEF/DPHI in the design and implementation of monitoring of health financing schemes including small sample surveys as required

1. Proposal for pilot costing study on Kampong Cham (Section – IV)2. Data collection and analysis of the pilot study (Section – IV)3. Presentation of pilot study results (Section – IV)3. Prepared list of sample hospitals on the basis of their performance indicators (Section – IV)

Small sample survey conducted and results disseminated

Participating in the preparatory and final meetings for the Joint Annual Plan Appraisal and the Joint Annual Performance Review, and assisting the BHEF/DPHI with preparation of relevant analyses and reports for both events

1. Actively participated in all the meetings organised by DPHI (no evidence with me on paper. But the person who prepared the minutes will have my signature of my attendance)2. Several presentations to Partners and SDMG members (Section 2, 3 and 4)

In the meeting the decisions are made and when it comes to the stage of implementation nothing is done. Moreover the meetings in the ministry are not focussed and gets diverted with some other discussion.

Working in close collaboration with other technical assistants in the MOH to provide

1. Evaluation report of all internally contracted SOAs (Section – 2)

Went through all the proposals (written in English) during the collection of population data for SDG allocation.

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technical support for the design and implementation of internally contracted schemes for service delivery including the monitoring of SOA activities and performance based contacts.

Providing capacity building to the BHEF/DPHI staff as determined by Director/DPHI

1. Training on the operation of HEF software and data base (Section - III)

No Comments

Conducting site visits to provincial and operational district offices and service delivery points to monitor smooth functioning of health financing schemes

1. Visit to Ratanakiri OD and health facilities2. Visit to Kampong Cham Hospital3. Training the OD staff at Ratanakiri on SDG, HEF and Monitoring mechanism

One should have more exposure to the field rather than working in office like a dump. During my period of consultancy I was allowed to have limited visit to the field, even if the budget for the same was a lot and was written in my TOR.

Collaborating closely with the HSSP2 Secretariat and directly contributing to the preparation of the health financing sections of the HSSP2 Performance Monitoring Reports on a semi-annual basis, and participating in the HSSP2 Joint Quarterly Meetings and meetings in connection with the Joint Review Missions

1. Prepared the Health financing report for 2010 for PMR (Section – V)2. Prepared the bi-annual progress report on health financing for 2011 (Section – V)3. Attended all the joint quarterly meetings (See the list of participants from the person who wrote the minutes of meetings)

The meetings are just conducted for the sake of conducting them. I have never seen any positive output out of these meetings.

Handling any other tasks that may reasonably be assigned by the Program Coordinator/ Director, DPHI

1. HEF- Expansion plan and cost estimates by province submitted to Dr Kiry (Section – 3)2. Methodology of the preparation of Expansion Plan (Section – 3)

DPHI needs to be strengthened and made functional. As per my observation the people in DPHI work in isolation and most of times absent / go on mission for monitoring. I strongly recommend having a separate monitoring cell in the ministry to carry out the monitoring activities in the field.

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Section 2: Works carried out for Service Delivery Grants (SDG)

2.1. IntroductionThis chapter reports the activities carried by me on Service Delivery Grants (SDGs) for the Special Operating Agency (SOA) Operational Districts (ODs). The activities mainly involved the development of an appropriate methodology for the SDG estimates for the year 2011. Since this was my first task during my period of assignment, it took a little bit time to adjust in a new environment get the work started. The present chapter describes the details of the method that was followed for developing the model, data constraints and the final outcome.

2.2. Activities carried out 2.2.1. Tasks assigned and completed My first meeting with the HSSP-2 Secretariat staff was held on 25 th November 2010 at 3.30 P.M. where I was introduced to the Secretariat staff. This was followed by the discussion with my supervisor Dr Kanha (who is my reporting authority) who explained me all the activities that are to be carried out during the first one year of my contract. Initially I was assigned the task of estimating SDG by Province/OD.

2.2.1a. First Phase of SDG Estimation

Tasks assigned1. To develop a computerised model and the methodology for SDG estimates and

allocations by province. 2. To develop basic criteria and a computerised model for the estimation of the

appropriate allocation of SDGs to different provinces. 3. To develop at least two models of SDG allocation which were to be presented and

discussed with the concerned partners / counterparts.

Since the time was short it was agreed that the required support will be provided by the HSSP2 Secretariat in order to finalise the models quickly.

Tasks completed and outputs1. Prepared a draft computerised model (first model) for provincial SDG allocation to

SOAs by taking various indicators (socio economic, health status, RCH status, population and remoteness) into consideration and shared with shared SDG allocation model (SOA-OD wise) with the Chief Programme Administrator, HSSP2 and representatives from JPIG.

2. In the second model the remoteness and the number of health facilities were taken as major criteria for the allocation of SDG among Operational districts. (Ref: Annex 2.1, 2.2 and 2.5 – Soft copy of all the models in CD. Annex 2.3 and 2.4: User manuals prepared for understanding the model – Hard copy attached and soft copy in CD). The information collected for the entire process is given in Annex 2.16, 2.16a –data used for estimation soft copy.)

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2.2.1b. Second Phase of Estimation:

Comments from SDMG and JPIG and modification of model 2

The first two models were prepared and presented to SDGM and JPIG on 5 th January 2011. The following comments were received and I was asked to revise the model accordingly.

1. Preparation of alternative allocation models with different weights assigned to the distance from OD to RH and RH to HC and weights assigned to CPA1, CPA2 and CPA3 status of the hospitals. (Ref: Annex 2.6, 2.7, 2.8 and 2.9 – Four alternative models with different weights assigned-soft copies in CD, Annex 2.10 - Minutes of the meeting - soft copy in CD, Annex 2.11– Presentations made on 5 th

January 2011 - soft copy in CD.)2. Out of several simulations, selecting the best 4 models with different weights on the

distance that are acceptable to the partners and SDGM members. 3. Presentation of the models to SDMG and JPIG members and selection of final model

of allocation for their approval 4. Preparation of minutes of meetings held with SDMG and JPIG and circulating them

for comments 5. Revising the accepted model on the basis of comments received from JPIG and

SDMG members6. Preparation of users guide for understanding the final allocation model

2.2.1c. Third Phase of Estimation:

Tasks completed 1. Prepared 4 SDG allocation Models and made a presentation of the same to JPIG

and SDMG members on 5th January 2010. 2. Model 2 was approved in the meeting. However some additional modifications were

suggested which was incorporated and presented in the next meeting on 19th

January 2011. (Ref: Annex 2.12: Presentation on 19th January-Provided in soft copy, Annex 2.13: The minutes or meeting on 19th January- soft copy in CD)

3. Prepared minutes of all the above meetings, circulated them among the JPIG and SDMG members. The process continued till the final SDG allocation is agreed by all the members.

4. Made population projections for OD as well as Provinces for the estimation of the model and made corrections in population figures as per the signed contract by OD directors (Ref: Annex 2.17 and 2.18 -soft copy)

5. Prepared the User Manual for SDG allocation model (Ref: Annex 2.4- text and soft copy)

2.3. Conclusion

Though the allocation model was accepted by all the partners, the final decision was taken by the Program Director. Because of the reasons better known to him, he was not in favour of allocating the resources to SOAs on the basis of the model developed. In addition, as the of SDG allocation is more a negotiation process rather than technical, the final decision was made by the Project Director and the development partners and contracts signed. The final allocation for the year 2011 and tentative allocation for 2012 was presented in SDGM quarterly meeting held on 17th October (Ref: Annex 2.14 – Presentation on SDG allocation (provided in soft copy). However, the proposed model of SDG allocation should take into consideration the population as well as the inflation rate. The model proposed by the consultant is suggestive and, it is hoped that the future allocation probably would take those factors into consideration while allocating the grants to SOAs. (Given in Annex 2.15)

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List of Annexures

Annex 2.1, 2.2 and 2.5: (soft copy in the CD). In addition to these annexes there are several other files related to data used in the estimation process.

Annex 2.3: Allocation of Funds – User’s Guide to Methodology for Allocation of SDGs across the Provinces given below. The Ministry of health Under Second Health Sector Support Programme (HSSP) - 2 intends to evolve an equitable basis for allocation of Services Delivery Grants (SDG) to provinces, taking into account socio-economic and health status and population of each province. This technical note presents a methodology to compute a ‘composite disparity index’ (CDI) and recommends allocation of funds to individual Provinces in proportion of their index values.

Computation of CDIThe composite disparity index is constructed following the United Nations Development Programme (UNDP) approach of constructing human development index. CDI attempts to assess distance (disparity) of a province relative to the best positioned one among all the Provinces, based on four criteria, namely (a) socio-economic status, (b) public health status, (c) RCH status, and (d) a scale (size) factor measured in terms of a province’s share in total population in the state (Table 1). CDI does not take into account status of health infrastructure (Referral Hospitals, Community Health Centres, Health Posts etc.) since infrastructure development needs be considered separately based on an integrated plan. However an attempt has been made to include some of the performance indicators as they do play an important role in prioritising the allocation of resources.

Table 1: Criteria/indicators for construction of composite disparity indexCriteria Indicators

1. Socio-economic status

1.1 Percentage of Families having no access to proper water supply, Electricity and basic sanitation1.2 Percentage Inter province migration1.3 Percentage Female illiteracy rate

2. Public health status

2.1 Annual parasite index (malaria)2.2 Annual new smear positive case detection per lac (tuberculosis)2.3 Prevalence rate of leprosy2.4 HIV positive case per 10,000 population

3. RCH status

3.1 Crude birth rate3.2 Non-institutional delivery3.3 Incomplete ANC3.4 Percentage of children (12 - 35 months) not received immunisation or received incomplete immunisation3.5 Lack of awareness regarding ORS

4. Scale (or size) Percentage of total population3. Barring the scale factor, index value of criterion j (say, socio economic status) for province i with respect to a set of underlying indicators k=1,2 ,. . ,m (Mentioned in Table 1) is estimated as given under:

I ji= 1m ∑

k=1

k=m (x jk−min xk )(max xk−min xk )

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where max xk and min xk represent maximum and minimum values of the indicator k across

the Provinces. Thus, I ji measures distance (disparity) of a province relative to the best

positioned one among all the Provinces, distance being scaled to the max-min range. I ji can

take value between 0 (best positioned province among all the Provinces) and 1 (worst positioned province among all the Provinces). 4. Probably an example would make it clearer. Let us consider the criteria for Socio Economic Status of Bantey Meanchey province. In other words, we want to know where the Province Bantey Meanchey stands among all the provinces. As mentioned above for one of the provinces the value of each of the Socio Economic Status indicators (given in Table 1) will be ‘0’ thus indicating the province is best positioned in terms of the indicator selected (say percentage of population with access to safe drinking water, electricity and sanitation). Similarly a value 1 shows the worst positioned provinces among all the provinces. The following table would make it simpler:

Table 2: Indexing the Socio Economic Status

Criteria

Socio-economic status

SE1 Percentage no access to safe drinking water supply (piped water), Electric Power, Toilet facility with premisesSE2 Percentage migration to different other provinces (Excludes migration to other countries)

SE3Female illiteracy rate

Max 96.00 90.63 77.72Min 12.83 19.54 22.28

Districts SE 1 SE 2 SE 3 IndexRank

Sl noDistricts Value Score Value Score Value Score Index Ran

k1 Bantey Meanchey 82.21 0.834 48.73 0.411 44.36 0.398 0.548 112 Battambang 85.63 0.875 41.10 0.303 41.97 0.355 0.511 133 Kampong Cham 91.69 0.948 25.41 0.083 46.51 0.437 0.489 184 Kampong Chhnang 93.33 0.968 19.54 0.000 48.43 0.472 0.480 195 Kampong Speu 94.46 0.981 33.45 0.196 49.30 0.487 0.555 106 Kampong thom 94.78 0.985 22.08 0.036 49.93 0.499 0.507 157 Kampot 92.75 0.961 22.15 0.037 48.58 0.474 0.491 178 Kandal 80.54 0.814 50.52 0.436 37.97 0.283 0.511 149 Kohkong 73.36 0.728 72.49 0.745 55.46 0.598 0.690 310 Kratie 91.44 0.945 51.70 0.452 44.44 0.400 0.599 811 Mondul Kiri 90.32 0.932 68.52 0.689 77.72 1.000 0.874 112 Phnom Penh 12.83 0.000 56.48 0.520 22.28 0.000 0.173 2413 Preah Vihear 94.67 0.984 52.29 0.461 42.39 0.363 0.602 714 Prey Veng 96.00 1.000 19.92 0.005 25.47 0.058 0.354 2315 Pursat 92.86 0.962 29.05 0.134 27.99 0.103 0.400 2116 Ratanak Kiri 87.72 0.900 61.74 0.594 62.58 0.727 0.740 217 Siem Reap 83.31 0.847 39.25 0.277 34.09 0.213 0.446 2018 Preah Sihanouk 63.54 0.610 78.11 0.824 24.68 0.043 0.492 1619 Stung Treng 89.07 0.917 49.89 0.427 45.56 0.420 0.588 920 Svay Rieng 92.13 0.953 59.19 0.558 27.72 0.098 0.536 1221 Takeo 94.98 0.988 22.49 0.041 27.96 0.102 0.377 2222 Otdar Meanchey 91.53 0.946 70.74 0.720 42.00 0.356 0.674 523 Kep 94.83 0.986 84.64 0.916 30.77 0.153 0.685 424 Pailin 77.09 0.773 90.63 1.000 31.49 0.166 0.646 6

Steps for SE1:

First take the actual value (the value is available in census book for the people having access to all the facilities). The figures for not having access can be easily obtained after

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subtracting each figure from 100. Similarly the value columns in the Table are the original data or computed from the basic data base. Find out the maximum and minimum values of the indicators within Socio Economic Criteria. As mentioned above the formulae for calculating the score

= (Actual value of the Indicator-the minimum value of the indicator )(Maximum value of the Indicator-minimum value of the indicator)

After applying this formulae for the province Bantey Meanchey the value of the score is

=(82.21−12.83)(96.00−12.83)

= 0.834

The score for each of the provinces is calculated in the same fashion and the province Phnom Penn has a “0” value indicating the best performance Prey Veng has value “1” indicating the worst one. Same method is followed for arriving at the score for each of the values. For Socio Economic Indicator we have three values, thus three scores. The Index on the table is the average of three scores.Next step is to rank the district on the basis of index values, with the rank 1 given to the highest index and 24 to the lowest index.

In the similar Fashion the Index values of each of the indicators are arrived at (here we have three Indicators as given in Table 1)

Table 3: Indexing the Public Health Status (The same method as above) Public health status PH 1: Annual parasite index (malaria)

PH 2: Annual smear positive case detection per lac (tuberculosis)PH 3: Prevalence rate of leprosyPH 4: HIV positive cases per 10,000 population

Max 19.14 2027.80 27.76 15.41Min 0.03 0.00 0.00 0.00

Districts PH 1 PH 2 PH 3 PH 4 Index Rank

Districts Value Score Value Score Value Score Value Score Average

Bantey Meanchey 0.37 0.018 81.1 0.040 20.51 0.739 10.56 0.686 0.371 1Battambang 1.18 0.060 48.9 0.024 12.00 0.432 4.95 0.321 0.209 8Kampong Cham 1.12 0.057 57.5 0.028 13.45 0.485 3.35 0.217 0.197 10Kampong Chhnang 0.96 0.049 66.1 0.033 11.43 0.412 0.40 0.026 0.130 18Kampong Speu 1.00 0.051 48.7 0.024 7.81 0.281 2.45 0.159 0.129 19Kampong thom 1.38 0.071 77.6 0.038 19.64 0.707 0.00 0.000 0.204 9Kampot 1.07 0.054 62.8 0.031 14.85 0.535 1.72 0.112 0.183 12Kandal 0.08 0.002 86.6 0.043 0.00 0.000 0.61 0.039 0.021 21Kohkong 2.15 0.111 27.3 0.013 2.55 0.092 15.41 1.000 0.304 4Kratie 5.24 0.273 243.8 0.120 8.46 0.305 0.47 0.030 0.182 13Mondul Kiri 10.41 0.543 0.9 0.000 0.00 0.000 0.00 0.000 0.136 17Phnom Penh 0.03 0.000 41.3 0.020 0.00 0.000 0.22 0.014 0.009 23Preah Vihear 19.14 1.000 595.5 0.294 0.00 0.000 0.00 0.000 0.323 3Prey Veng 0.14 0.006 78.6 0.039 19.00 0.684 3.39 0.220 0.237 6Pursat 5.96 0.310 129.2 0.064 0.00 0.000 2.85 0.185 0.140 16Ratanak Kiri 6.13 0.319 311.6 0.154 0.00 0.000 0.27 0.017 0.123 20Siem Reap 0.95 0.048 214.8 0.106 3.12 0.113 5.91 0.384 0.163 15Preah Sihanouk 0.21 0.009 3.8 0.002 0.00 0.000 0.18 0.012 0.006 24Stung Treng 8.37 0.437 0.0 0.000 27.76 1.000 0.358 0.023 0.365 2Svay Rieng 0.19 0.008 2027.8 1.000 0 0.000 1.864 0.121 0.282 5

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Takeo 0.35 0.017 925.0 0.456 0.237 0.009 3.042 0.197 0.170 14Otdar Meanchey 12.13 0.633 63.7 0.031 0 0.000 3.175 0.206 0.218 7Kep 1.01 0.051 23.8 0.012 0 0.000 0 0.000 0.016 22Pailin 6.47 0.337 8.8 0.004 8.512 0.307 1.561 0.101 0.187 11

Table 4: Indexing the RCH Status indicators (Results)RCH status RCH 1: CBR

RCH 2: Non-institutional delivery

RCH 3: Incomplete ANC

RCH 4: Percentage of children not fully immunisedRCH 5: Percentage not received atleast first post natal consultation

Max 4.14 87.82 66.0046.0

091.0

0

Min 2.00 38.74 18.00 4.0011.0

0

Districts RCH 1 RCH 2 RCH 3RCH

4 RCH 5 Index Rank

Districts Value Score Value Score Value Score Value Score Valu

e Score Average Rank

Bantey Meanchey 2.95 0.445 66.4 0.564 28.0 0.208 16.0 0.286 68.0 0.713 0.443 13Battambang 3.00 0.469 76.8 0.776 32.0 0.292 21.0 0.405 67.0 0.700 0.528 9Kampong Cham 2.95 0.445 73.6 0.710 29.0 0.229 4.0 0.000 53.0 0.525 0.382 17Kampong Chhnang 3.40 0.655 49.5 0.219 36.0 0.375 7.0 0.071 52.0 0.513 0.367 19Kampong Speu 3.07 0.501 78.1 0.801 36.0 0.375 18.0 0.333 69.0 0.725 0.547 8Kampong thom 3.02 0.478 82.2 0.885 46.0 0.583 18.0 0.333 79.0 0.850 0.626 6Kampot 2.83 0.389 77.4 0.789 30.0 0.250 17.0 0.310 72.0 0.763 0.500 11Kandal 2.59 0.275 55.4 0.339 22.0 0.083 15.0 0.262 66.0 0.688 0.329 22Kohkong 2.86 0.404 64.4 0.522 35.0 0.354 24.0 0.476 11.0 0.000 0.351 21Kratie 3.18 0.553 87.8 1.000 59.0 0.854 46.0 1.000 82.0 0.888 0.859 1Mondul Kiri 4.04 0.953 77.9 0.797 45.0 0.563 28.0 0.571 91.0 1.000 0.777 2Phnom Penh 2.00 0.000 55.4 0.339 41.0 0.479 31.0 0.643 91.0 1.000 0.492 12Preah Vihear 3.07 0.500 70.6 0.650 46.0 0.583 27.0 0.548 52.0 0.513 0.559 7Prey Veng 2.65 0.306 71.6 0.669 22.0 0.083 11.0 0.167 54.0 0.538 0.353 20Pursat 3.18 0.553 77.5 0.789 23.0 0.104 13.0 0.214 37.0 0.325 0.397 16Ratanak Kiri 4.14 1.000 74.5 0.728 45.0 0.563 34.0 0.714 75.0 0.800 0.761 3Siem Reap 3.21 0.567 71.4 0.665 18.0 0.000 14.0 0.238 68.0 0.713 0.437 14Preah Sihanouk 2.86 0.405 73.2 0.702 56.0 0.792 33.0 0.690 85.0 0.925 0.703 5Stung Treng 3.12 0.523 77.74 0.795 37.0 0.396 19.0 0.357 54.0 0.538 0.522 10Svay Rieng 2.51 0.241 53.15 0.294 19.0 0.021 5.0 0.024 36.0 0.313 0.178 24Takeo 2.80 0.376 44.73 0.122 18.0 0.000 15.0 0.262 57.0 0.575 0.267 23Otdar Meanchey 2.86 0.405 57.39 0.380 27.0 0.188 15.0 0.262 60.0 0.613 0.369 18Kep 2.70 0.329 80.84 0.858 66.0 1.000 27.0 0.548 83.0 0.900 0.727 4Pailin 2.75 0.354 38.74 0.000 24.0 0.125 29.0 0.595 90.0 0.988 0.412 15As mentioned earlier, scale (size) factor for a province measures its share in the total population. Thus, scale index value considered for CDI computation simply represents percentage population figure indexed province wise.

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Table 6: Population IndexDistricts Value Index Rank

Bantey Meanchey 6,77,872 0.051 9Battambang 10,25,174 0.077 4Kampong Cham 16,79,992 0.125 1Kampong Chhnang 4,72,341 0.035 13Kampong Speu 7,16,944 0.054 8Kampong thom 6,31,409 0.047 10Kampot 5,85,850 0.044 11Kandal 12,65,280 0.094 3Kohkong 1,17,481 0.009 20Kratie 3,19,217 0.024 15Mondul Kiri 61,107 0.005 23Phnom Penh 13,27,615 0.099 2Preah Vihear 1,71,139 0.013 18Prey Veng 9,47,372 0.071 5Pursat 3,97,161 0.030 14Ratanak Kiri 1,50,466 0.011 19Siem Reap 8,96,443 0.067 6Preah Sihanouk 2,21,396 0.017 16Stung Treng 1,11,671 0.008 21Svay Rieng 4,82,788 0.036 12Takeo 8,44,906 0.063 7Otdar Meanchey 1,85,819 0.014 17Kep 35,753 0.003 24Pailin 70,486 0.005 22It must be noted that the population ranking is obtained by just dividing the total population of the province by the total population of Cambodia as per 2008 census.

The Composit Disparity Index and Weights:

The composite disparity index value for province i

is computed taking weighted average of

all the index values corresponding to criteria j=1,2 ,. . ,n

as given under:

CDI i=∑j=1

j=n

w j I ji

where w j

represents weight of j

criterion. The weights are determined after giving due

consideration to each criterion and their correlation with each other.

5. Rank Correlation and assigning weights to Criteria: In order to arrive at the final results, we computed the Spearman’s Rank Correlation coefficient so that we have some idea about the interrelationship among the indices. The results are given below:

6. Spearman’s Rank Correlation Coefficient and Interpretation: Index values related to RCH status are not found to be significantly correlated with those of other three criteria. Thus, RCH status represents an independent criterion and it carries 40 per cent weight in the composite index. The scale factor (share in population) is given 10 per cent weight in the composite index. Relatively lower weight is assigned in view of the fact that a province’s larger share in population does not necessarily mean poor socio-economic and health status. In fact, the scale index values are found to be negatively correlated with those of socio-economic status (correlation coefficient = -0.76) and public health status

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(correlation coefficient = -0.06). However, larger population requires more RCH coverage and that justifies the inclusion of this criterion in CDI computation.

A/B A/C A/D B/C B/D C/D A B C D

d2 d2 d2 d2 d2 d2 A 1

4 64 16 100 4 144 B -0.76 1

81 16 25 25 16 1 C -0.06 0.16 1289 81 256 64 1 49 D -0.40 0.43 -0.28 136 25 36 1 0 14 121 0 81 4 12125 1 16 36 81 936 1 0 25 36 1121 324 361 49 64 1289 256 1 1 324 28949 4 196 25 49 144484 36 441 256 1 225484 441 100 1 144 121121 225 121 16 0 16324 1 225 289 9 19649 4 4 25 25 0289 1 256 324 1 289196 81 64 25 36 10 64 121 64 121 361

144 361 121 49 1 640 49 144 49 144 361

225 49 256 64 1 81144 100 1 4 169 121400 4 400 324 0 324256 121 49 25 81 16

Summation d2 4050 2430 3210 1922 1312 2936

Rank correlation -0.76 -0.06 -0.40 0.16 0.43 -0.28

Allocation of fundsIt is recommended that MOH allocate funds to Provinces in proportion of their CDI values. According to our computed CDI values based on available data, the province Mondul Kiri stands first in the resource allocation criterion (Table 7)

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Table 7: CDI and the Final Ranking:

B C D ADistrict Criteria

Com

posi

te In

dex

Allo

catio

n (%

)

Ran

kSocio-Economic Status

Public Health Status RCH Status Scale

(Population)

20% 30% 40% 10%Districts Index Rank Index Rank Index Rank Index Rank

Bantey Meanchey 0.548 11 0.371 1 0.443 13 0.051 9 0.403 4.61 8Battambang 0.511 13 0.209 8 0.528 9 0.077 4 0.384 4.39 9Kampong Cham 0.489 18 0.197 10 0.382 17 0.125 1 0.322 3.69 16Kampong Chhnang 0.480 19 0.130 18 0.367 19 0.035 13 0.285 3.26 19Kampong Speu 0.555 10 0.129 19 0.547 8 0.054 8 0.374 4.28 11Kampong thom 0.507 15 0.204 9 0.626 6 0.047 10 0.418 4.78 7Kampot 0.491 17 0.183 12 0.500 11 0.044 11 0.357 4.09 13Kandal 0.511 14 0.021 21 0.329 22 0.094 3 0.250 2.86 22Kohkong 0.690 3 0.304 4 0.351 21 0.009 20 0.371 4.24 12Kratie 0.599 8 0.182 13 0.859 1 0.024 15 0.520 5.96 2Mondul Kiri 0.874 1 0.136 17 0.777 2 0.005 23 0.527 6.03 1Phnom Penh 0.173 24 0.009 23 0.492 12 0.099 2 0.244 2.79 23Preah Vihear 0.602 7 0.323 3 0.559 7 0.013 18 0.442 5.06 4Prey Veng 0.354 23 0.237 6 0.353 20 0.071 5 0.290 3.32 18Pursat 0.400 21 0.140 16 0.397 16 0.030 14 0.284 3.25 20Ratanak Kiri 0.740 2 0.123 20 0.761 3 0.011 19 0.490 5.61 3Siem Reap 0.446 20 0.163 15 0.437 14 0.067 6 0.319 3.65 17Preah Sihanouk 0.492 16 0.006 24 0.703 5 0.017 16 0.383 4.38 10Stung Treng 0.588 9 0.365 2 0.522 10 0.008 21 0.437 5.00 5Svay Rieng 0.536 12 0.282 5 0.178 24 0.036 12 0.267 3.05 21Takeo 0.377 22 0.170 14 0.267 23 0.063 7 0.239 2.74 24Otdar Meanchey 0.674 5 0.218 7 0.369 18 0.014 17 0.349 4.00 15Kep 0.685 4 0.016 22 0.727 4 0.003 24 0.433 4.95 6Pailin 0.646 6 0.187 11 0.412 15 0.005 22 0.351 4.02 14

Total 12.969101 4.3 11.9 1 8.739 100.00

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Annex 2.4: Calculation of Cambodia Service Delivery Grants - User's Guide – Text given below (soft copy in CD)

SECTION - 1Introduction: A simple model has been developed for the calculation of Services Delivery Grant size of 22 Operational Districts. The model takes remoteness as the major criteria for allocation of resources across the SOA-ODs.

The grant size for an OD is calculated by multiplying the population of each OD with USD 1.5 (USD 1.5 is the per capita allocation of the SDG which is defined prior to the model formulation)

The total size of SDG is the sum of the SDGs allocated to Operational Districts.

Thus the size of the SDG acts as the resource envelop for the ODsThe per capita allocation of SDG across the ODs is subject to change depending on the size of the district (i.e., operational area in square kilometre), number of different levels of health care institutions (RHs of different levels, HCs and HPs) in the district and the average distance of each of these health care institutions in the district (remoteness).

Since the cost of providing services to remotest ODs is higher due to the known reasons for accessibility, due care is taken by assigning appropriate weights and making adjustments to the existing population size.

What the model/tool does?The model generates per capita annual allocations to each OD based on pre assigned weights that best fit to the model.

About the tool / Model: The tool first requires selection of some or all of the appropriate weightings to be placed on the proportion of the grant allocated according to:

remoteness from health facilities (Boxes 4 & 5 ‘Options’ worksheet)number of Health Centres in the OD (Box 6 ‘Options’ worksheet)

number of Referral Hospitals in the OD (Box 7 ‘Options’ worksheet)

the OD population (this weight is a residual generated by the model; if the weights in Boxes 6-7 are set to zero, the population weight is 100%) - Else it changes

Please note that parameters of the model interact to some extent. For example, if the number of health centres is increased this reduces the average (estimated) distance to a health centre so reducing the impact of weights for remoteness. The formula assumes that health facilities are equally distributed across a province. If this is not the case then some manual correction to the allocations may be required.

The tool is prepared by using a MS Excel workbook with worksheets linked with each other.

The first sheet of the model contains a brief description about the instructions which are elaborated in this manual.

The second worksheet contains 8 Boxes

(a) Box 1:- Per Capita Allocation figure set at 1.5 USD

(b) Box 2:- Total population of ODs taken from the sheet named “SDG allocations per SOA-OD” (3rd worksheet)

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(c ) Box 3:- Indicates the total amount of budget and arrived at by multiplying figure in Box 1 and 2. (Named as: total allocation)(d) Box 4:- (Named: rhdensity) the weight per capita that the user want to give to the RHs that are above the average distance of RH.

In our case it is set at “0”(e) Box 5:- (Named: hcdensity) the weight per capita that the user would like to give to HCs that are above the average distance from HC.

In our case this is set at 5%(f) Box: -6 (Named as: perhc) the weight that the user would like to give to number of Health Centres in the allocation criteria.

In our case we have set it at 10% level (g) Box: -7 (Named as: perrh) the weight that the user would like to give to the number / type of RH in the allocation criteria.

In our case it is 5% as we believe that type of RH does play a role in allocation (h) Box 8: - This is the weight given to the population and automatically arrived at once the weights for box 6 and 7 are given. This is called remainder.

To sum up about the worksheet 2: Box 4 and 5 represents the remoteness in the sense that if the difference between the actual area of the HC/ RH is more than their average coverage area, then the HC/RH are located at more remote places with dispersed population. The higher the value of the difference between actual and average the more remote is the place and more dispersed are the population. This is arbitrary and mostly depends on the human judgement on the basis of the experience of remoteness of the health facilities

Box 6 and 7: This is not related to remoteness; rather it captures the average population that a HC/RH covers. As the population are not evenly distributed, the weight is given to cover the evenness in the distribution of the health care institutions in the area. These two boxes are mostly meant for the proportionate grant that should go to the ODs on the basis of number of institutions in this area.

Box 8: The weights assigned to the population of the ODs. This is closely related to Box 6 and 7. Total weights within the boxes 6, 7 and 8 should add up to 100.

The sheet 3: “Base data for SDG estimates”: - This is a sheet where all the basic data required for the computation of SDG grants are recorded. It must be noted that the figures of surface area is estimated for the year 2011. Once we have actual data then one should replace the estimated figures with actual figures. This sheet is the input data sheet from which is linked to all other sheets in the workbook.

Note: The worksheet 2 (named as ‘Options’) and worksheet 3 named as “Base data for SDG estimates” are the input sheets. Therefore any changes in these two sheets are to be made with precaution. The most important worksheet in the work book is Worksheet – 4 and named as “Computations”. The section below makes an attempt to explain the Worksheet in detail. SECTION – 2In this section attempts are made to explain the linkages and interactions among different sheets, the formulae used and the logic behind each formula. Since the worksheets are linked together, the explanation of each of these aspects are not made in isolation. At each point references are made for each of the work sheets.

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It must be clearly understood that the allocation to any OD is divided into three parts:

First: Allocation to the Referral hospitals on the basis of their weights assigned

Second: Allocation to the health centres, which is purely on the basis of number of health centres and the weight assigned to it in box 6 of worksheet 2 (perhc)

Third: Allocation as per the adjusted population (which takes in to consideration of the variables related to remoteness of the health facilities)

The sum total of the allocations to these 3 gives the total allocation per OD.

In the computation sheet the name of the ODs and the population figures are given in column A and B respectively. In column C the number of referral hospitals is explained in terms of weights. We assign 1 to CPA1, 2 to CPA2 and Zero (extremely small number say 0.00001) to CPA 3 referral hospitals.

In the absence of data on the area of the ODs in square kilometres the following formula has been used to arrive at the approximate coverage area per OD: (The area of the province in sq. km. /Total population of the province as per 2010)*The population of OD in 2010). The estimated figures are given in column E. -It is suggested that the actual figures are inserted once they are made available)

The model is specifically meant for calculating per capita allocation to 22 SOA-ODs only and cannot be generalised for provincial referral hospitals.

The formula in column F and G: It is assumed that the area of an OD is like a circle, with the referral hospital/s and HCs are evenly distributed. Thus the average distance of any HC/RH is same across the OD. The figure is different for different ODs depending upon the area and number of HC / level of referral hospital.

In some of the ODs the Health Posts are also there. In that case the health centres having ≤ 3 RHs is assigned with an additional weight of 0.25 (equivalent to one fourth of a health center) and the HCs having ≥ 4 HPs is assigned a weight equivalent to one third of a health centre (i.e., 0.34) and the appropriate weights added to the formula.

Mathematically:

A=π r2

A: Area of the circle

π2 : Called (Pie) is the value 3.14

r: Indicates the radius of a circle

We have the area of the ODs in Square Kilometres. For illustration, let us take the example of Samrong OD.

The area of the OD (A) = 6643 square kilometres.

N = the number of health centres is 17

π = 3.14

Now in order to get the radius of a health centre we apply the following formula:

r=√((A /N) /π¿)¿

= √((6643/17)/3.14) = 13.9

2 . If you measure the distance around a circle and divide it by the distance across the circle through the centre, you will always come close to a particular value, depending upon the accuracy of your measurement. This value is approximately 3.14159265358979323846... We use the Greek letter (pronounced Pi) to represent this value.

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This implies that the each of these 17 health centres in the OD covers a distance of 13.9 kilometres from its location.

If any of the ODs has ≤ 3 Health Posts the value of the radius is multiplied by 1.25

If any of the ODs has ≤ 3 Health Posts the value of the radius is multiplied by 1.34

The same formula applies for Referral hospitals also.

Formula for Column I: This formula is written logically to incorporate the remoteness of the OD by adjusting the population. Take the same example i.e., Samrong OD.

=B20*(1+IF(F20>F$30,F20*rhdensity,0)+IF(G20>G$30,G20*hcdensity,0))

Where

B20: Original population of the OD

F20 : Actual distance (radius) covered by RH

F30: Average distance, which is 32.5 kilometres covered by RH under consideration

“rhdensity”: already defined in Section 1 (in our case the weight is “0”).

G20: Actual distance (radius) covered by HCs under consideration

G30: Average distance covered under health center, which is 13.9 kilometres

“rhdensity”: Already defined in section 1 (in our case the weight is 5 per cent)

This formula takes the weights assigned in sheet 2 and gives appropriate weights to the OD population to get the adjusted population. For our example, the actual population of Samrong OD is 238265. Since the OD is one of the remote ODs (as per the criteria set in the formula), an additional population of 166,124 has been added to the actual population, thus adjusting the additional cost for remoteness.

The total adjusted population is around 744,247 for 6 remotest ODs i.e., Smach Meanchey, Sre Ambel, Ban Lung, Sen Mnorum, Tbeng Meanchey and Samrong. This accounts for about 20 of the total allocation, which has been adjusted for remoteness.

The total allocation to each of the ODs is sum of the allocation to RHs, HCs and the adjusted population The formulae for all these allocations are self-explanatory and needs no explanation. Basic knowledge on Excel is adequate enough to understand those columns.

Adjusted populationof ODUnderConsideration{(∑ totalof the adjusted population∈22ODs)×

(1−weights assigned ¿no of RH−Weight assigned ¿noof HC )×(Total Allocation (Box 3 ))}

( (Actual populationof OD )×(1+theweightsthat are due¿the¿actual distance of RH∧HC beingmorethan¿the average distancecovered ))

((Actual distance of RH∈Km×Weight assigned¿RH distance∈Options sheet )+(Actual distance of HC∈KmWeight assigned¿HCdistance∈Options sheet))

( Actual populationof OD×(1+Weights that are due¿ theaverage distance of ¿RH∧HCbeingmore thanthe original distancecovered))

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Annex 2.6, 2.7, 2.8 and 2.9 – Four alternative models with different weights assigned (soft copies in CD) Annex 2.10: Minutes of the meeting on 5th January 2011 – Soft copy in CD Annex 2.11– Presentations made on 5th January 2011 - soft copy in CD. Annex 2.12– Presentations made on 5th January 2011 - soft copy in CDAnnex 2.13: Minutes of Meeting on SDG Progress – soft copy in CD Annex 2.14: Presentation on SDG allocation on 17th October 2011Annex 2.15: Allocation of SDG for 2012-13 suggested methodology

No SOAPopulation

2011 Approved Budget 2011

Population growth rate

Population during 2012

Per Capita Adjustment in 2012 (by taking inflation into consideration) (5% assumed )

Allocation during 2012- excluding provincial hospitals

Allocation in 2012 after adjusting for population and inflation rate and

Population during 2013

Per Capita Adjustment in 2013 (by taking inflation

Allocation during 2013 excluding provincial hospitals

Allocation in 2013 after adjusting for population and inflation rate and 15% reduction

1 Kampong Cham PRH 1,65,000 156750 1489132 Memut OD 137141 1,77,793 0.43 1,37,731 1.30 179326 161393 1,44,617 1.37 197706 1680513 Punhea Krek OD 217061 2,54,600 0.43 2,17,995 1.30 283829 255446 2,28,894 1.37 312922 2659834 Cheung Prey OD 195799 2,37,500 0.43 1,96,641 1.30 256027 230424 2,06,473 1.37 282270 2399295 Chamkar Leu OD 161264 2,00,000 0.43 1,61,958 1.30 210869 189782 1,70,056 1.37 232483 1976116 Prey Chhor OD 186777 2,43,600 0.43 1,87,580 1.30 244229 219806 1,96,959 1.37 269262 2288737 Takeo PRH 2,00,000 190000 1805008 Daun Keo OD 220964 2,17,758 0.66 2,22,422 1.30 289594 260634 2,33,543 1.37 319277 2713859 Prey Kabas OD 162734 2,00,467 0.66 1,63,808 1.30 213278 191950 1,71,998 1.37 235139 199868

10 Baty OD 200283 2,46,723 0.66 2,01,605 1.30 262490 236241 2,11,685 1.37 289395 24598611 Kirivong OD 230990 2,62,801 0.66 2,32,514 1.30 302733 272460 2,44,140 1.37 333763 28369912 Ang Rokar OD 140150 1,59,849 0.66 1,41,075 1.30 183680 165312 1,48,129 1.37 202507 17213113 Smach Meanchey OD 58685 1,09,586 0.12 58,756 3.44 202355 182119 61,694 3.62 223096 18963214 Koh Kong PRH 73,058 0 69405 6593515 Sre Ambel OD 64634 2,01,160 0.12 64,712 3.44 222868 200581 67,948 3.62 245712 20885516 Ban Lung OD 172546 3,30,751 4.67 1,80,604 3.70 667514 600762 1,89,635 3.88 735934 62554417 Rattanakiri PRH 2,20,501 0 209476 19900218 Sen Mnorum OD 66801 1,85,525 6.34 71,036 4.87 346087 311478 74,588 5.12 381560 32432619 Mondulkiri PRH 91,378 0 86809 8246920 Tbeng Meanchey OD 190350 4,16,573 3.61 1,97,222 3.69 726861 654175 2,07,083 3.87 801364 68116021 Preah Vihear PRH 1,96,034 0 186232 17692122 Samrong OD 238265 4,40,800 8.64 2,58,851 2.78 720253 648228 2,71,794 2.92 794079 67496723 Oddor Meanchey PRH 1,10,200 0 104690 9945624 Siem Reap OD 311028 2,70,860 2.52 3,18,866 1.30 414526 373073 3,34,809 1.37 457015 38846325 Siem Reap PRH 1,82,038 0 172936 16428926 Sotnikum OD 300240 3,42,000 2.52 3,07,806 1.30 400148 360133 3,23,196 1.37 441163 37498927 Angkor Chum OD 224405 2,57,851 2.52 2,30,060 1.30 299078 269170 2,41,563 1.37 329734 28027328 Krolanh OD 130307 1,49,729 2.52 1,33,591 1.30 173668 156301 1,40,270 1.37 191469 16274929 Preah Sdach OD 119192 1,40,394 0.01 1,19,204 1.30 154965 139468 1,25,164 1.37 170849 14522230 Pearaing OD 201730 2,37,614 0.01 2,01,750 1.30 262275 236048 2,11,838 1.37 289159 245785

Total 3931348 65,22,143 40,05,787 7016652 7334535 42,06,076 7735859 7692963

Annex 2.16a and 2.16b: Base data used for SDG Estimates (Soft copy in CD)Annex 2.17: Population Projection by ODAnnex 2.18: Population projection by province

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Section 3- Works carried out for Health Equity Fund (HEF)

3.1. IntroductionA major chunk of my work in Cambodia HSSP2 was on Social Health Protection (SHP) and Health Equity funds. Most of the time was devoted for making the cost estimates for the HEF for 2010 and making the projection for future years. In addition preparing the health financing reports for the year 2010 and bi-annual progress report for the year 20113 was my responsibility. The reports for health financing was specifically prepared as a part of the Project Monitoring Report (PMR) that is submitted to the development partners for their assessment on overall health financing in Cambodia. Apart from these two activities, initiating a hospital costing study for establishing the provider payment mechanism and standardisation of hospital fee structure was another key responsibility. The following section of the report describes the progress of the activities related to HEF. The progress related to hospital costing is reported in Section 4 and Section 5 reports the works carried out relating to health financing chapters for PMR.

The works related to Services Delivery Grants (SDG) was almost over during the month of January and I was deeply involved in the activities related to SHP from February 2011 onwards.

3.2. Activities carried outDuring the beginning of this assignment I was made clear that I have to work on the following areas of Health Equity Fund:

3.2.1. Phase 1 of activities related to HEF

Activities Planned1. Preparation of Health Equity Fund estimates for all HEF supported ODs for the year

2011. 2. To collaborate with BTC, URC and GTZ to understand the HEF projection during

2010 and develop suitable methodology3. Preparation and presentation of the methodology adopted for HEF estimates for

2011 to development partners and SDMG members4. Preparation of the manual on HEF describing the methods adopted for unit cost for

2010 and projection for 2011 5. Revision of the SOA manual on the basis of the comments made by development

partners

Outputs Achieved1. Made initial preparation on the health equity fund estimates for 2011. The estimates

were made by taking all the ODs (the data collected from URC) and two models were prepared (a) Estimates for all the ODs (b) Estimates for HSSP supported ODs. However, the final estimates were made in March 2011 because of the reasons mentioned below: Initially collected the basic data files on health equity fund cost and utilisation data from Dr Kanha. The major problem with the data was that the utilisation as well as the cost figures for Health Centres and Hospitals were merged together for the year 2010 (Ref: Annex 3.1- soft copy in CD). It was therefore difficult to make unit /

3 The reports were part of PMR submitted to JPIG. I contributed the health financing chapter of the PMR for the year 2010 and bi-annual progress report for 2011. These are presented in Chapter -5.

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average cost estimates for 2010. Moreover there were many ODs who did not report any data.Had a detailed discussion (several rounds) with Dr Kanha regarding the problem with the data during the year 2010. During 2010, no method was followed for the allocation of HEF to the HSSP supported ODs. As there was no background information, Dr Kanha suggested taking the help of URC and BTC while preparing estimates. Therefore I had several round of meetings with Dr Dirk BTC) as well as Mr Tapley (URC) on these aspects. On the basis of discussion developed the methodology for estimating the unit costs for the HSSP supported ODs as the data for the other ODs were incomplete / under reported. The projections were shared with BTC and URC for their necessary inputs on the development of appropriate method of allocation. The presentation was made in URC in the presence of BTC and other staff of URC closely working in the area of HEF.Till this point, I was not aware that the HEF data base is maintained by URC. As there was a lot of data gap in the DPHI data base, I collected all the necessary information from the URC, BTC and SRC directly and organised the base data for the year 2010. (Ref: Annex 3.10a-3.10M - soft copy in CD) The entire exercise of consultation, collection of basic data for the year 2010 and took my entire February month and I was not able to go ahead with the estimates for 2011.. Therefore nearly two weeks during the month of March 2011 was spent on bridging these gaps and I could complete a draft estimate for 2011 by 15 th March 2011

Processes involved Several rounds of meetings with URC – Mr Tapley for understanding the HEF

allocation formulae Several rounds of discussion with Ms Thavry, Dr. Kanha and Dr. Kiry Had three rounds of meetings with Mr Julian Handson of GIZ and Mrs Putheany,

Director of ID-Poor Unit in MoP on the methods used for poverty estimates Collected poverty figures for 10 provinces (as the data is available for 10 provinces

only) Several (minimum 10 rounds) of e-mail communication with the JPIG and SDMG

members regarding the date of presentation of initial estimates of HEF for HSSP supported ODs.

Several rounds of meetings with Dr. Kanha (at least 10 long sittings with her for discussion on different issues related to data and calculation)

Revised the OD population (all 77 ODs) figures on the basis of provincial population and Health Coverage Plan 2004-05. The figures will be used for HEF allocation. This is what is called the adjusted population. The figures on adjusted population (explained later in user’s manual) were used for all future estimates of HEF.


Activities Planned1. Preparation of Health Equity Fund estimates for HSSP2 supported ODs for the year

2011 (as the data for other ODs were incomplete). 2. Preparing and making the presentation on the methodology for the estimates. and

estimates for the development partners 3. Preparing the manual on the methodology adopted for estimation of HEF for 20104. Revise the SOA manual on the basis of the comments made by development

partners5. As mentioned in the above paragraphs, a chunk of the time was devoted for getting

into a detailed understanding about the HEF, data limitations, data collection and developing appropriate methodology for cost projections for HEF estimates.

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So the activities during this phase were carry forward activities.

Outputs Achieved1. Completed the HEF cost estimates and projection for the year 2011(Ref: Annex 3.2,

3.3, 3.4, 3.5 – Soft copy in the CD). However, the model given in Annex 3.5 is the final model for the initial estimates of HEF for HSSP supported ODs for 2011 which was presented to development partners. Estimates for Referral Hospitals (RH) and Health center (HC) were combined in the model.

2. Prepared the presentation and manual on the methodology of cost estimates and projection for presentation of the models to development partners, SDMG and key staffs working on health financing in the ministry. (Ref: Annex 3.6 gives the detail of the methods adopted during the process of estimation and acts as a user’s guide – soft copy in CD)

3. The power point presentation was prepared to understand the model and act as step by step user’s guide on how the cost estimates and projections were made. (Ref: Annex 3.6 – soft copy in CD)

4. Prepared and circulated the minutes of meeting held on 25th March 2011 and revised on the basis of the comments received from the participants and recirculated for their records (Ref: Annex-3.7 – soft copy in CD)

5. On the basis of the comments received from the JPIG, revised the SOA manual. This was a consultative process as I was not very much clear about the queries made by JPIG. I took the help of Dr Kanha for addressing the queries in the manual. Completed and submitted to Dr Kanha (Ref: Annex 3.8: soft copy in CD)

6. Prepared the report on HEF for 2007-2010 (Ref: Annex 3.9: soft copy in CD)Processes involved

1. Meeting with various ministerial staff including Dr Kanha, Dr. Vengky and Mrs. Thavry

2. Collection of revised and validated data from URC, HIS data base and other sources for HEF cost estimates and projection. (Ref: Annex 3.10a to Annex 3.10M- 11 files in soft copy)


Activities Planned1. Collection of necessary data and modify the estimates with due consideration of the

comments received from JPIG and URC during the presentation on 25th March: 2. Preparation of separate estimate for Hospitals and Health centres 3. Making the modification in projections by taking CPA1, CPA2, and CPA3 hospitals

unit cost into consideration 4. Discussion on the definition of all direct cost components. There is no clear cut

definition on Non Food and Grants component of HEF estimates. 5. Preparation of the latest version of HEF estimates and sent it for approval. Even if

the presentation made on 25th March was purely based on the MDG Goals and The Health Sector Strategic Plan it was not well appreciated by Tapley as the estimates for 2011 were made without any target.

6. Preparation of three simulations by using URC data (a) combined estimate for HC and Hospitals (2) separate estimate for HC and Hospitals (3) estimates by category of hospitals (CPA1, CPA2, CPA3) with and without combined data

Outputs Achieved1. Collected HC and Hospital utilisation and cost data from URC data base. (Ref:

Annex 3.10 – 3.10M: soft copy of the data provided and cross checked with the earlier information collected from URC)

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2. Modified the models on the basis of the comments received from JPIG (Ref: Annex 3.11a and 3.11b: Soft copy of the model provided for your reference)

3. The base line unit/average cost estimate was prepared by taking the CPA status of Referral Hospitals (RH)

4. HEF estimates for the year 2011 were already approved by the time the model was prepared. It was decided not to make any estimate for 2011. Therefore the estimates for 2012 and 2013 were prepared (Ref: Annex 3.11a and 3.11b).

5. The definition for Non-food and Grants were clarified from HEF manual and it was decided that non-food and grants cost be included under direct benefit cost and the estimates will be made separately. Different permutation and combinations of the model was tried. (Ref: Annex 3.12 – soft copy in CD)

Processes involved 1. Meetings and discussions with various ministerial and HSSP2 secretariat staff

2. Collection of separate cost data for Hospitals and Health Centres from URC for further revision of the estimates (Ref: Annex 3.10a – Annex 3.10M – soft copy provided)

3.2.4. Phase 4 of activities related to HEFActivities Planned

1. Preparation of computerised model for estimation and projection of HEF for the years 2011, 2012 and 2013

2. Presentation of the methodology for HEF estimates for the year 2011, 2012 and 2013 at AFD

3. Discussion on the costing and projection methods with Dr. Kanha. The discussions were intended to be on target setting as per the national goal and the cost of hospital and health center outputs (base line cost 2010).

Outputs Achieved1. Prepared and presented the methodology of HEF estimates for the year 2011, 2012

and 2013 to AFD. (Ref: Annex 3.13 – soft copy of the model presented to AFD in CD, and Annex 3.14: Power point presentation on methodology for target setting, costing and assumptions – soft copy in CD)

2. Had a series of discussions (nearly 5) with Dr. Kanha on the presentation of the final model of HEF estimates. The discussions were mostly on the target setting as per the national goal and the cost of hospital and health center outputs. (Ref: Annex 3.15 – Presentation made on 27th June on HEF estimates and target setting – soft copy in CD)

3. Prepared, circulated and presented the new methodology for HEF estimates for the future on 27th June 2011. The positive outcome of the meeting was that most of the participants agreed on the proposed methodology. However the concern was mostly on the hypothetical assumptions and target setting. (Ref: Annex 3.15 – Presentation made on 27th June on HEF estimates and target setting – soft copy in CD, Annex 3.16: Estimated model for 2012 with HC and RH separately and Cost of CPA1, 2 and 3 separately- soft copy in CD)

4. Prepared the minutes of meeting on 27 th and circulated among participants for their comments. (Ref: Annex 3.17 – Minutes of meeting on 27th June soft copy in CD)

Processes involved: 1. Meeting with various ministerial staff including Dr Kanha, Dr. Vengky and Mrs Thavry

(several rounds)

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2. Discussion with URC regarding the availability of past 4 years utilisation data by output categories (it was difficult to collect past data on cost and utilisation by output categories, specifically surgeries and deliveries because the data recording and reporting system has changed from simple Fox-pro data base to the New Software developed by URC)

3.2.5. Phase 5 of activities related to HEFActivities Planned

1. Transferring the HEF data base to Dr Kanha’s computer and train her on the operation of software

2. Preparation of HEF expansion plan from 2011-2015 and estimation of resource requirements (Provincial estimates) Dr Kiry, the Program Coordinator, HSSP-2.

3. Initiation of Hospital costing study for provider payment mechanism4. Circulating the Minutes of meeting held on 27th June 2011 and finalising the model5. Providing the necessary inputs to standardised business plan format prepared by

GIZ6. Finalisation the methodology for cost estimation7. Finalisation of assumptions and preparation of methodology for target setting and

cost projection 8. Preparation of User’s Manual for the methodology adopted for expansion plan

Outputs Achieved1. Made an attempt to collect the necessary information on HEF beneficiaries i.e., (IPD

– Number of surgeries, Surgical deliveries, Normal deliveries and other IPD), (OPD – Number of OPD for hospitals and HCs), Number of deliveries at the health center from the URC for revising the estimate for HEF and determining the budget envelop for 2012-2015. However due to technical difficulties related to computer software only limited information could be collected4. (Ref: Annex 3.10a-3.10M – Soft copy in CD)

2. Finalised the estimation model for the HEF after incorporating the information collected from URC. This model was used for preparation of HEF expansion plan for 2012-2015. (Ref: Annex – 3.18a , 3.18b - soft copy in CD)

3. Prepared the expansion plan of HEF for Dr. Kiry for the full coverage (i.e., for the entire country) of HEF schemes and prepared a detailed estimate of the resource requirements from 2011-2015. This was prepared for submission to Ministry of Economy and Finance. (Ref: Annex 3.19 –soft copy in CD)

4. At present no standardised business plan format exists for submission of the business proposal by the HEF operators. Dr. Kanha, with the technical inputs from GIZ prepared a standardised business plan format and the same was discussed in the meeting held on 11th July 2011. From my side I provided the necessary technical inputs for the same before the meeting.

5. Access to HEF data base was a major problem for the Bureau of Health Economics and Financing. This is a major obstruction to prepare the estimates and future projections for the ministry. The data base is basically maintained and updated by the URC at their office in Phnom Penh and for any small information I had to go to URC frequently. In consultation with Dr. Kanha and URC, we have installed the software to access the data base from Dr. Kanha’s computer.

6. Finalised the method of calculating the unit cost of OPD (for RH and HC), IPD, and Deliveries (for RH and HC). The method of calculating the unit cost is described in User’s Manual and the model used for unit cost estimates (Ref: Annex 3.20- Soft copy in CD)

4 This was a carry forward activity from the month of May 2011.

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7. Attended the workshop on the preparation of AOP for 2012 and prepared a quick estimate of the resource envelop for the HEF for 2012.

8. Discussed about the expansion plan of HEF by OD and on the basis of the proposed expansion plan by Dr. Kanha, prepared a computerised software (by using excel 2010) for the estimates of number of HEF beneficiaries (IPD, OPD and Deliveries) and the resource implications for the same for the year 2012, 2013, 2014 and 2015.

9. Discussed the software prepared for expansion of HEF with Dr Kanha for her final comments and approval. Made the final revisions on the basis of her comments

Processes involved: 1. Had a series of discussions (at least once in two days) with Dr. Kanha on different

issues related to HIS data base and how to make the best use of the available data? In this context Dr. Kanha and I decided to make a detailed analysis of hospital performance data and prepare a policy paper from the available data.

2. Had several rounds of meetings with Dr. Kanha for developing and designing the costing templates required for hospital costing study.

3. Meetings and discussions with Dr. Kanha, URC, BTC and Dr. Kiry especially related to the common agreement on costing methodology, the procedure on the methodology of estimating HEF for future years, the methodology and formulae that is used for the expansion plan of HEF by province and the future plan to make the expansion by OD.

4. Minimum of 10 visits to URC for HEF data installation, Finalisation of costing methodology, training etc.

3.2.6. Final activities related to HEF Activities Planned

1. Completion of HEF-Expansion plan model software for future use and estimation of resource envelop for 2012-2015.

2. Completion of User’s Manual that describes the methodology and formulae used for the estimation process

3. Training the supervisor on the use of the software

Activities Completed

1. Completion of final HEF expansion plan software and preparation of User’s Manual for the same. (Ref: Annex – 3.21 – hard copy of user’s manual attached and soft copy in CD)

2. Trained my supervisor on the operation of the software and how to make changes when the new data comes in.

3.2.7. Additional Tasks completed 1. Attended meeting held by SDMG on the finalisation of the agenda for the workshop

proposed to be held on 10th May 2011.2. Attended SDMG quarterly meeting on 22nd March 20113. Had a meeting with RACK on the problems relating to the release of HEF. The

meeting was attended by Dr. Kanha, Tapley, Dr. Vibol and me4. Addressed delegates from Malaysia (15 member team) on the health financing

processes in Cambodia and discussed with them regarding the proposed costing study for the hospitals for developing Provider Payment Mechanism (PPM).

5. Attended the World Bank workshop on Provider Payment mechanism on 5th and 6th

March 20116. Reviewed the proposal for HEF submitted by GRET Sky for the year 2011 and

provided necessary comments as required

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7. Attended the P4H meeting in AFD office on 29th March 2011. 8. Went to Ratanakiri to understand the process of implementation of SDG and HEF

from 6 – 9 February 2011.9. Visited 4 health centres, one HP and had a detailed discussion with the PHD, OD

and RH staff. As AFH is the HEF operator in Ratanakiri, I had a detailed discussion about the procedure of post and pre identification and the reimbursement mechanism to the hospitals and poor patients.

10. The OD director in Ratanakiri organised a meeting and I was requested to take a training session on monitoring and evaluation of the health centres in Ratanakiri. I took a two hours training session for the OD staff on the issue of monitoring and supervision and explained how that should be inbuilt into the health system.

11. Attended the workshop on Health sector performance review for 2010 in the Hotel Intercontinental

12. Reviewed the Proposals submitted by AFH and Bfh and provided the feedback of the same to Dr. Kanha

13. Attended the meeting on Co-funding proposal and business plan for HEF in Phnom Penh. The meeting was organised by the HSSP secretariat to finalise the business plan for Phnom Penh city.

3.3. Problems and Constraints At the initial stages of my joining the environment was completely new. It took nearly a month or two to get adjusted to work environment, getting along with the people and exposure to the ministry. However, this happens in any new work environment and not uncommon to me. I would like to mention few points that need to draw attention of the authorities.

It is difficult for timely completion of the tasks assigned because of the information/data necessary for preparing the documents/ models are either not available or the person in charge of that information is absent. There is high level of absenteeism in the ministry.

Most of the times people are unclear on what they exactly want from others? This leads to a situation where wrong / inappropriate instructions are issues/imposed on them.

The data maintained in HIS is inaccessible at most of the times as the server is managed by URC. The consultants / policy makers, (who are mostly the users of the data set) have to take several permissions and approvals even for limited access to data set.

It is observed from HIS data set that most of the data are inconsistent and does not reflect the actual/real situation in the field. This is mostly due to lack of feedback mechanism in the system. Therefore, it is suggested that the feedback mechanism is managed by the DPHI, so that errors in data are minimised.

Limited opportunity to be exposed to the field. During my entire tenure I just went to the field two times. I hope my exposure to the field would have helped me to develop my capacity to understand the system better and to do the works faster than what I did.

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List of Annexures

Annex 3.1 – The base file on HEF collected from BHEF-DPHI (soft copy in CD)

Annex 3.2, 3.3, 3.4 and 3.5: Estimated models – different simulation and modifications in different dates. The final copy is Annex 3.5 presented to JPIG on 25th March 2011 (soft copy of files in CD)

Annex 3.6.: Detailed methodology given in a power point presentation (soft copy in CD)

Annex 3.7: Minutes of Meetings held on HEF Allocation on 25th March 2011. (Hard and soft copy in CD)

Annex 3.8: SOA Manual revision (soft copy provided in CD)

Annex 3.9: A detailed analysis of HEF 2007-2010 (soft copy in CD)

Annex 3.10a –3.10M (soft copy of all the data collected and cross checked with the earlier information collected from URC)

Annex 3.11a, 3.11b: Soft copy of the model provided for your reference

Annex 3.12: Soft copy of the HEF estimates provided for reference,

Annex 3.14 – soft copy of the model presented to AFD, and

Annex 3.15: Power point presentation on methodology for target setting, costing and assumptions – soft copy of the presentation for your reference)

Annex 3.16 – : Estimated model for 2012 with HC and RH separately and Cost of CPA1, 2 and 3 separately- soft copy in CD

Annex 3.17 – Minutes of meeting on 27th June- soft copy in CD

Annex 3.18a and 3.18b– HEF Expansion Plan – soft copy in CD

Annex 3.19 – HEF expansion and costing for Dr Kiry– soft copy in CD

Annex 3.20- Model used for costing the outputs – Soft Copy in CD

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Annex 3.21: HEF Expansion Plan – User’s Manual

SECTION – 1

1.1. BackgroundThis manual intends to provide a detailed guideline on methodology followed for the Health Equity Fund (HEF) estimates for the year 2011 and its expansion plan for the years 2012-2015. The process of developing appropriate methodology and making final estimates was a continuous and long process and took nearly 6 months to give its final shape. It is expected that the estimates should be acceptable to all the stakeholders. However, the estimates have already been submitted to the Government for its approval.

The entire process was consultative and the inputs were taken from all the stakeholders; Joint Partnership Initiative Group (JPIG), University Research Centre (URC), senior level officials from Department of Planning and Health Information (DPHI) Ministry of Health (MoH) and other national and international agencies working in the field of HEF. However, a chunk of the inputs were from Dr Sok Kanha, Dy. Director DPHI as I worked directly under her supervision. A brief overview of the process involved in the preparation of expansion plan is given below:

1. At the first instance two models of HEF (One for only HSSP supported ODs and another for all ODs) were prepared and presented to the JPIG and other stakeholders working for HEF.

2. On the basis of the comments received, the model was revised with the estimates for Health Centre (HC) and Referral Hospitals (RHs) separately. Several versions of the model were prepared (nearly 5-6) and simulations were made to find out a suitable model that could be acceptable to the stakeholders. The same was shared with the JPIG and senior officials and comments received for finalisation of a suitable model.

3. As a first step towards the preparation of the expansion plan of HEF, an initial model was prepared for provincial projections of HEF and submitted to the Program Coordinator for comments. Several discussion were made on the assumptions that are to be taken for setting up of the targeted number of beneficiaries for the years 2011-2015 which was mutually agreed for the purpose of estimation

4. As the allocation of resources for the health sector is made by Operational Districts, it was felt that, the estimates should be made by ODs in order to make the resource allocation for HEF more realistic and viable. As the estimates have already been made for 2011 and the resources allocated, the aim was to prepare an expansion plan for the HEF for future years.

1.2. HEF Expansion plan: - Brief IntroductionDuring the year 2012 the MoH have decided for a gradual expansion of HEF schemes from the current coverage of 58 ODs in 2011 to 65 in 2013 and 77 during 2014 – thus covering all the ODs during next 3 years. The coverage would include all the Provincial Referral Hospitals (PRHs), Referral Hospitals (RHs) and health centres in coming 3 years. Annexure Table 1 gives the details of the present coverage of HEF.The expansion plan involved: (a) Collection of basic data on population estimates of people below poverty line (b) The current utilisation pattern of health facilities by the public (non-poor and poor), (c) the target setting of the coverage of poor population (d) cost estimates for the implementation of HEF schemes.

1.2.1. Objectives of the present manual

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This manual aims at providing detailed guidelines on the process and methodology of the expansion plan model. It is a step by step guide to understand the model. Attempts are being made to make the manual simpler, so that everybody understands the way the estimates are being made. Several steps were involved in the process of estimation. Table 1 gives a bird’s eye view of the steps. In the subsequent sections a detailed description of each step is made and the logic and formulae used are explained with illustrations. The model is prepared by using Excel 2010. The excel workbook contains 8 worksheets. The worksheets are organised sequentially. Sheet 1 (HEF11-15): The first worksheet contains the base population data, the adjusted population, the projected total and poor population and the utilisation data by the poor (IPD, OPD and Deliveries). The sheet does not contain any cost data and the cost is computed by using another work book separately.

Sheet 2 (HIS – Data): This worksheet contains the basic statistics related to RH and HC collected from HIS data base. The information includes OPD, IPD, and Discharges etc. The information is used to compute certain statistics that are used for target setting for the poor HEF beneficiaries.

Sheet 3 (Target Setting): This worksheet gives the information about how the targets are being set for the poor IPD, OPD and Deliveries etc.

Sheet 4 (Cost Sheet-2010 base): As mentioned earlier in the above paragraph, the average costs of each of the services (direct benefit and indirect cost) are computed in another workbook. The results are presented in this worksheet.

Sheet 5-8 (2012, 2013, 2014 and 2014): The financial projections are presented on these sheets.

Note: It may be noted that all the sheets are linked together and any change in first 4 worksheets will change the financial estimates.

1.2. Steps involved and data requirements (Baseline data 2010)Steps Data Requirement / Estimates

1 Collection of baseline population data for 2010, adjusted population, and projection for the years 2012-2015. (Source: Census 2008)

2 Estimates of number of poor population by OD (Source: ID-Poor from Ministry of Planning)3 Collection of overall (poor and non-poor) utilisation data on IPD, OPD, Discharges and calculation of

basic indicators (Source: HIS data base maintained by URC)4 Calculation of basic indicators and target setting for OPD at RH:

Contact rate by poor during 2010 and projection (assumed that the contact rate for RH will remain constant over the projected period and will be expanded for HC in a phased manner))

5 Calculation of basic indicators and target setting for OPD at HC level:Contact rate by poor during 2010 and projection for future ((Source: Basic data from URC data base)

6 Calculation of basic indicators and target setting for IPD at RH level: Admission rate (% admitted in the hospitals) % poor IPD benefited from HEF during 2010 from RHs (including PRHs) and HCs Bed Turnover Ratio (BTR) – Assumptions and estimates

7 Calculation of basic indicators and target setting for the Deliveries at RH and HC Level – Assumptions and estimates

8 Collection of utilisation and expenditure data for the HEF beneficiaries for 2010 and calculation of average cost (Source: URC HEF data base)

9 Final estimates for OPD, IPD and Deliveries on the basis of set targets for the year 2012, 2013, 2014, 2015 (Calculated as per assumption)

SECTION – 22.1. Collection of baseline data and adjusted population: At the first instance the baseline population, utilisation and cost data is collected from the sources given in Table 1. The population data for the year 2010 was collected from the URC data base. This is mostly because the utilisation and cost information of the HEF is available

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with URC only. The population data by OD is available with DPHI only as the census does not report the population data by operational district. Population data for 2011by OD was arrived in the following manner.

First the provincial population data for the year 2008 is collected from Cambodia Census 2008 and projection for the years 2011-2015 is made by using exponential growth rate formulae i.e.,(Nt = N0 × e(r × t) ), where, Nt = future Population, N0 = base year population, e = exponential function that carries the value 2.718, r = growth rate of population, t = number of years.

OD wise population is collected from the HIS data base of DPHI. Corrections are made in DPHI figures by taking the population figures used for SDG allocation. It may be noted that the total population reported by DPHI does not match with the provincial population totals. In other words, if a province has 4 ODs then the total population of 4 ODs should match with the projected population of the province. Therefore adjustments are made in OD population so that total OD population tallies with the provincial population. This is what we call it as adjusted population.

After obtaining the adjusted population of the ODs, we took 2011 data as the base and made projection for 2012, 2013, 2014 and 2015 by using the exponential growth rate (as mentioned above)

2.2. Estimates of poor population by ODThe poverty estimates for 10 provinces are available with ID-Poor unit of Ministry of Planning. For another 14 provinces the average poverty figure for the country i.e., 30.1 per cent is taken as the base for calculating the total number of poor people. The provincial poverty percentages are used as proxy for arriving at the estimates of poor population at OD level.

2.3. Collection of data on overall utilisation and utilisation by poorThe overall utilisation data of the health facilities like number of OPD, IPD, discharges during 2010, number of beds in PRH and RHs etc. is collected from the HIS database maintained and managed by URC. Number of health facilities in the OD is collected from the DPHI. The latest update of the number of health facilities in each OD was done during 2010.

URC is officially authorised agency to maintain the HEF data base for the entire country. Therefore it is expected that the database maintained by them is accurate. The utilisation data by poor is also collected from URC from their HEF data base. This information is used to compute certain indicators that are used for setting up the targets for the poor.

2.4. Calculation of basic indicators and target setting for OPD 2.4.1. Target Setting for OPD for Referral Hospitals: (i). Calculation of baseline figures The baseline contact rate for PRH/RH is calculated by taking the total number of

reported HEF-OPD beneficiaries (by OD) during the year 2010 and calculated by using the formulae given below. It is assumed that the average contact rate for the poor during 2010 remains constant over the projection period.

For the ODs where the data is not reported, the mean (average) value of the contact rate of the reported ODs during 2010 is taken as the base value and it is assumed that the contact rate would remain constant during the projection period.

URC reports the number of beneficiaries by institution as well as by OD. For the ODs where there are both PRH and RH, we have added the OPD beneficiaries of both and use the aggregate figure for the calculation of contact rate. Example of Mongkol Borei OD is given as an illustration (given below).

The formulae used for the calculation of contact rates for the RHs are given below.

(ii) Formulae used for Target Setting

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The OPD contact rate by poor for PRH1,2,3...,24 during 2010= Total OPD beneficiaries in PRH 1,2,3,…,24 during 2010 (Popln. of the respective Provinces during 2010×Poverty Rate of the respective Provinces during 2010)

The OPD contact rate by poor for RH1,2,3...,77 during 2010=

Total OPD beneficiaries in RH1,2,3,…,77 during 2010 (Popln. of the respective ODs during 2010×Poverty Rate of the respective ODs during 2010)

The OPD contact rate by poor where there are PRH as well as RH =

(Total OPD beneficiaries in PRH 1,2,3,…,24 +beneficiaries in RH 1,2,3,…,24 during 2010) (Popln. of the respective Provinces during 2010×Poverty rate of the respective Provinces during 2010)

Targeted OPD Beneficiaries at RH level for the OD1,2,3 ,… ,77 = (OPD contact rates for

OD1,2,3,…77 × Poor population of OD1,2,3,…77 )

Where “O” is the number of ODs, “O”= 1, 2, 3, ..., 77 (there are 77 ODs.)

As per the assumption the OPD contact rate for PRH and RH would remain constant over the projection period.

By taking the assumptions given above and after applying the above formulae, we get the contact rates that are used to set the targets for Referral Hospitals. Column 3 of Table 3 gives the contact rates that are calculates and used for OPD target setting for hospitals.

2.4.2. Target setting for OPD at Health Centre LevelAs mentioned earlier, the data on the actual number of poor beneficiaries is available in HEF data base maintained by URC. Therefore it is easy to calculate the contact rate for the health centres for which the data is available.

It may be noted that, the HEF schemes were implemented in just 325 health centres during 2010, whereas the total number of health centres is around 1020. Therefore from the coverage point of view an expansion plan is prepared by increasing the contact rate gradually (0.20 per year) so that each poor has at least one contact in a year during the expansion phase. The targets set for the year 2012-2015 are given in Columns 4, 5, 6 and 7 of Table 3. For the ODs where the contact rate for the poor is more than one, it is retained as it is. Following assumptions were taken for calculating the targeted poor HEF beneficiaries for the years 2012-2015.

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Table 2: Assumptions on the contact rate for HCsIf present contact

rate is 2012 2013 2014 2015

≤ 0.10 0.30 0.50 0.70 0.900.20 0.40 0.60 0.80 1.000.30 0.50 0.70 0.90 1.100.40 0.60 0.80 1.00 1.200.50 0.70 0.90 1.10 1.300.60 0.80 1.00 1.20 1.400.70 0.90 1.10 1.30 1.500.80 1.00 1.20 1.40 1.60≥0.90 1.00 1.20 1.40 1.60

>1 1.2 1.4 1.6 1.8No data reported 0.40 0.60 0.80 1.00

For the ODs where the beneficiary data was not reported, the average of the reported contact rates is taken as the base for setting targets. The average base rate (rate during 2010) is 0.37, but we have rounded up it to 0.40. Table 2 gives the assumed contact rate for the ODs for the year 2012-2015 on the basis of which the targeted poor has been set. Table 3 gives the calculated contact rates for Hospitals and Health Centres.

Formulae used for Target SettingAn operational district may have several health centres. Therefore it is difficult to set the targets for individual health centres. An aggregate target has been set for the health centres for each of the ODs, irrespective of number of HCs that any OD has. The major objective here is to ensure at least one contact by the poor in the OD.

The formulae and methodology used for calculating the contact rates and the way the targets are being set for the Health Centres is given below.

The OPD contact rate of the poor for the HCs of OD1,2,3,...,77 during 2010 =

Total HEF- OPD beneficiaries in OD1,2,3…,77 during 2010 (Popln. of the respective ODs during 2010×Poverty Rate of the respective ODsduring 2010)

The targeted number of poor OPD for HCs of OD1,2,3,...,77 during 2012=

\{(Popln. of the respective ODs during 2012×Poverty Rate of the respective ODs during 2012)\}×

\{(Assumed contact rate for the OD for 2012 (given in Table 2)\}The targeted number of poor OPD for HCs of OD1,2,3,...,77 during 2013=


\{(Assumed contact rate for the OD for 2013 (given in Table 2)\}

The targeted number of poor OPD for HCs of OD1,2,3,...,77 during 2014=


\{(Assumed contact rate for the OD for 2014 (given in Table 2)\}The targeted number of poor OPD for HCs of OD1,2,3,...,77 during 2015=


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Note: As the poverty rate is available for the year 2010, we have used the poverty rate of 2010 for target setting for 2012-2015. The figures can be changed in worksheet 1 as and when the poverty data is available for other years. As the worksheets are linked the estimates are automatically modified once we change the poverty figures.

Table 3: Hospital and Health Center OPD contact rate – Assumptions and targets

Sl.No. Operational District

Contact rate – RH Target OPD Contact rate for HC2012-2015 2012 2013 2014 2015

1 Mongkol Borei 0.034 0.90 1.10 1.30 1.502 Ou Chrov 0.003 0.60 0.80 1.00 1.203 Preah Net Preah 0.006 0.80 1.00 1.20 1.404 Thma Puok 0.037 0.40 0.60 0.80 1.005 Thma Koul 0.037 0.30 0.50 0.70 0.906 Mong Russei 0.028 1.20 1.40 1.60 1.807 Sampov Luon 0.037 0.40 0.60 0.80 1.008 Battambang 0.006 0.90 1.10 1.30 1.509 Sangkae 0.000 0.80 1.00 1.20 1.40

10 Chamkar Leu - Stueng Trang 0.014 0.30 0.50 0.70 0.9011 Choeung Prey - Batheay 0.023 0.30 0.50 0.70 0.9012 Kampong Cham - Kampong Siem 0.014 0.80 1.00 1.20 1.4013 Kroch Chhmar - Stueng Trang 0.037 0.00 0.00 0.30 0.5014 Memut 0.002 0.30 0.50 0.70 0.9015 O Reang Ov - Koh Soutin 0.037 0.00 0.30 0.50 0.7016 Ponhea Krek - Dambae 0.076 0.40 0.60 0.80 1.0017 Prey Chhor - Kang Meas 0.001 0.40 0.60 0.80 1.0018 Srei Santhor - Kang Meas 0.037 0.30 0.50 0.70 0.9019 Tbong Khmum - Kroch Chhmar 0.037 0.60 0.80 1.00 1.2020 Kampong Chhnang 0.037 0.40 0.60 0.80 1.0021 Kampong Tralach 0.001 0.70 0.90 1.10 1.3022 Boribo 0.000 0.50 0.70 0.90 1.1023 Kg Speu (Including PRH) 0.037 0.40 0.60 0.80 1.0024 Kong Pisey 0.037 0.30 0.50 0.70 0.9025 Ou Dong 0.037 0.00 0.00 0.30 0.5026 Baray Santouk 0.037 0.30 0.50 0.70 0.9027 Kg Thom 0.040 0.40 0.60 0.80 1.0028 Stong 0.012 0.40 0.60 0.80 1.0029 Angkor Chey 0.037 0.40 0.60 0.80 1.0030 Chhouk 0.037 0.40 0.60 0.80 1.0031 Kampong Trach 0.037 0.40 0.60 0.80 1.0032 Kampot 0.113 1.99 1.99 1.99 1.9933 Ang Snuol 0.000 0.00 0.30 0.50 0.7034 Kean Svay 0.037 0.00 0.00 0.30 0.5035 Koh Thom 0.037 0.00 0.30 0.50 0.7036 Ksach Kandal 0.037 0.40 0.60 0.80 1.0037 Muk Kam Poul 0.037 0.00 0.30 0.50 0.7038 Ponhea Leu 0.000 0.00 0.30 0.50 0.7039 Saang 0.037 0.00 0.00 0.30 0.5040 Takhmau 0.037 0.40 0.60 0.80 1.0041 Kep 0.037 0.30 0.60 0.80 1.0042 Smach Mean Chey 0.156 0.30 0.50 0.70 0.9043 Srae Ambel 0.037 0.40 0.60 0.80 1.0044 Chhlong 0.002 0.50 0.70 0.90 1.1045 Kratie 0.037 0.40 0.60 0.80 1.0046 Senmonorum 0.037 0.40 0.60 0.80 1.00

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Sl.No. Operational District

Contact rate – RH Target OPD Contact rate for HC2012-2015 2012 2013 2014 2015

47 Samraong 0.073 0.40 0.60 0.80 1.0048 Pailin 0.037 0.40 0.60 0.80 1.0049 Cheung 0.036 0.40 0.60 0.80 1.0050 Kandal 0.040 0.40 0.60 0.80 1.0051 Lech 0.028 0.40 0.60 0.80 1.0052 Tbong 0.040 0.40 0.60 0.80 1.0053 Tbeng Meanchey 0.008 0.40 0.60 0.80 1.0054 Kamchay Mear 0.037 0.00 0.30 0.50 0.7055 Kampong Trabek 0.037 0.40 0.60 0.80 1.0056 Mesang 0.037 0.00 0.30 0.50 0.7057 Neak Loeung 0.037 0.00 0.00 0.30 0.5058 Peareang 0.004 0.40 0.60 0.80 1.0059 Preah Sdach 0.037 0.40 0.60 0.80 1.0060 Prey Veng 0.037 0.30 0.50 0.70 0.9061 Bakan 0.010 1.00 1.20 1.40 1.6062 Sampov Meas 0.022 0.90 1.10 1.30 1.5063 Banlung 0.037 0.40 0.60 0.80 1.0064 Kralanh 0.023 0.40 0.60 0.80 1.0065 Siem Reap 0.045 0.40 0.60 0.80 1.0066 Sot Nikum 0.089 0.40 0.60 0.80 1.0067 Ankor Chhum 0.019 0.40 0.60 0.80 1.0068 Sihanouk Ville 0.027 0.50 0.70 0.90 1.1069 Steung Treng 0.069 1.20 1.40 1.60 1.8070 Chi Phu 0.037 0.40 0.60 0.80 1.0071 Romeas Hek 0.037 0.40 0.60 0.80 1.0072 Svay Rieng 0.035 0.80 1.00 1.20 1.4073 Bati 0.037 0.30 0.50 0.70 0.9074 Daun Keo 0.041 0.90 1.10 1.30 1.5075 Kirivong 0.053 0.50 0.70 0.90 1.1076 Prey Kabass 0.037 0.40 0.60 0.80 1.0077 Ang Rokar 0.140 0.80 1.00 1.20 1.40

Illustration Let us take the example of Mongkol Borei OD and calculate the indicators related to OPD. The population of the OD is 257418 and the poor population in that OD is 83403 and total population of the province is 699022. The number of contacts by the poor is 2850. As mentioned earlier, the first worksheet of the excel workbook contains this information.

Following basic data was collected for the OD from the HIS data base:

OUTPATIENTS Number of beds Total Discharges Inpatient Days

PRH RH HC PRH RH PRH RH PRH RH

16152 11056 187069 195 52 7796 3108 75543 16735

The general contact rate of OPD at RH =

T otal number of OPD in PRH and RH during 2010 (16152+11056=27208)Total population of the province in 2010 (699022) = 0.038

The contact rate by the poor OPD at RH =

T otal number of Poor OPD in RH during 2010 (2850)Total poor population of the OD in 2010 (83403) = 0.034

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As the hospitals are basically for the curative care, the contract rate is assumed to remain constant over the years 2012-2015. However, the number of poor beneficiaries does not remain the same and increase with the population growth.

Example: Contact rate for the Health Centres in Mongkol Borei OD and target setting:

The targeted number of poor OPD for HCs of OD1,2,3,..., 77 during 2012=



Projected population

2012


2013


2014


2015Poverty level in percentage

Project poor 2012

Project poor 2013

Project poor 2014

Project poor 2015

263863 268011 272224 276504 32.4 85492 86836 88201 89587

The figures given above are for Mongkol Borei OD.

The targeted number of poor OPD for HCs of OD1,2,3,...,77 during 2012

= (263863×32.4100 )×0.90 = 76942

The targeted number of poor OPD for HCs of OD1,2,3,...,77 during 2013

= (268011×32.4100 )×1.10 = 95519

The targeted number of beneficiaries for other years is calculated in the similar fashion.

2.5. Calculation of basic indicators and target setting for IPD at RH levelAs the public hospitals are targeted to serve the poor, it is assumed that at least 60 per cent of the admissions should be by poor. Bed Turnover Ratio (BTR) is taken as one of the major indicators to capture this. Bed Turnover Ratio is the number of admissions per bed in a year.

For example, if in a hospital the BTR = 40 (i.e., 40 admissions/discharges per bed in a year) then a maximum of 24 people (i.e., 60% of 40) can be poor patients

Method Calculate the percentage BTR by HEF – IPD beneficiaries for 2010This is being calculated in the following manner:

Step 1: Calculation of overall BTR for PRHs and RHs: Calculate the BTR for each of the hospitals in the OD (separately for PRH and RH). As every province has at least one PRH the calculation is made separately. The formula used for calculation of BTR is:

Overall BTR for PRH1,2,3 ,… ,24 =

(Total number of Admissions or Discharges in the PRH1,2,3 ,… ,24 )(Number of Beds in the hospital PRH1,2,3 ,… ,24 )

Overall BTR for RH1,2,3 ,… ,77 =

(Total number of Admissions or Discharges in the RH1,2,3 ,… ,77 )(Number of Beds in the hospital RH1,2,3 ,… ,77 )

Calculation of average BTR for PRH and RH

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Calculate the average of BTR for PRH and RH = (BTR for PRH+BTR for RH)

2Note: Where there is no PRH/ RH in the OD, the BTR takes the value “0” automatically where there is no PRH/RH in the OD. This is inbuilt in the formulae.

Step 2: Calculation of BTR by poor IPD beneficiariesThe data on actual number poor HEF – IPD beneficiaries is available in HEF data base maintained by URC. The data is fed in the first worksheet of the excel workbook. The BTR for poor IPD beneficiaries for PRHs and RHs for the year 2010 (base year) is calculated by using the following formula:

BTR by HEF-IPD by PRH1,2,3 ,… ,24 =Number of HEF - IPD PRH1,2,3,…,24 during 2010Total number of beds in PRH1,2,3,…,24 during 2010

BTR by HEF-IPD by RH1,2,3 ,…, 77=Number of HEF - IPD RH1,2,3,…,77 during 2010Total number of beds in RH1,2,3,…,77 during 2010

For the ODs where there are PRH as well as RH the BTR is calculated in the following manner:

BTR by HEF-IPD by PRH and RH=Number of HEF - IPD in (P RH1,2,3,…,24 +RH1,2,3,…,77 ) in 2010Total number of beds in (P RH1,2,3,…,24 +RH1,2,3,…,77 ) in 2010

Note: Where there is no PRH/ RH in the OD, the number of beneficiaries as well as beds for PRH/RH takes the value “0” automatically. This is inbuilt in the formulae.

Step 3: Calculation of percentage of BTR by HEF-IPD beneficiaries

Percentage of BTR by HEF – IPD beneficiaries =

BTR by HEF- IPD beneficiaries of OD1,2,3 , … ,77

Overall BTR of the Hospitals of OD1,2,3 ,… ,77×100

For scaling up the IPD poor beneficiaries, the assumptions given in Table 4 are taken in to consideration.

As already mentioned, targeted IPD beneficiaries should not exceed 60 per cent of the total IPD in any hospital. In other words, the admissions by poor should not exceed 60 per cent of the total admissions in a hospital. The ODs for which baseline percentage of BTR by poor is less than 60 per cent, the expansion plan is made in a phased manner to achieve this target. For the ODs where the BTR for poor is already more than 60 per cent, the value is retained. For the ODs where the data is not reported the target is set in a different manner and for the ODs where the value is more than 100 the target has been brought down.

The percentage BTR by poor during the year 2010 is taken as the base for the setting the target of the poor IPD. A detailed expansion plan that is used in the model is given in Table 4.

Table 4: Target Setting for IPD beneficiaries – Scaling up planIf %BTR by poor in 2010 is Target 2012 Target 2013 Target 2014 Target 20150 – 9.9 20 40 50 6010 – 19.9 20 40 50 6020 – 29.9 30 40 50 6030 – 39.9 40 50 60 6040- 49.9 50 60 60 60

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50- 59.9 60 60 60 6060+ Value retain Value retain Value retain Value retainScaling up in 2012 20 40 50 60Scaling up in 2013 0 20 40 50Scaling up in 2014 0 0 20 40Data not reported 30 40 50 60% BTR more than 100 (i.e., invalid data) 50 60 60 60

Step 4: Calculation of Admission Rate by General Population (Poor + Non Poor) - 2010Percentage of admission for the base year 2010 for the general population is calculated by using the following formulae:

Admission rate for PRH1,2,3 ,… 24=Total number of admissions or discharges in PRH1,2,3 ,…24

Total population of the province

Admission rate for RH1,2,3 ,…,77 = Total number of admissions or discharges in RH1,2,3 ,… ,77 Total population of the OD

Step 5: Projection of total number of admissions for the general population Apply the admission rate of the base year for the future projection of total IPD. The formula used for the calculation is as follows:

Projected IPD for PRH1,2,3 ,… ,24 for 2012 = (Total population of the province in 2012× Admission rate for PRH1,2,3 ,…, 24 in 2010)

Projected IPD for 2012 RH1,2,3 ,… ,77 = (Total population of the OD1,2,3 ,…, 77 2012× Admission rate for RH1,2,3 ,…, 77 in 2010)

Projected total IPD in OD1,2,3 ,…, 77 = (Projected IPDfor PRH1,2,3 ,… ,24 in OD+ Projected IPD for RH1,2,3 ,… ,77 in OD)

2

Note: For the ODs where there is no PRH/RH, the Projected IPD automatically takes the value “0”. This is inbuilt in the formulae.

IPD for the year 2013, 2014 and 2015 is calculated in the similar fashion. The baseline admission rate is taken as the basis for calculation.

Step 6: Calculation of targeted number of poor beneficiaries For the target setting of the Poor IPD the following formula has been used:

Targeted number of HEF-IPD beneficiaries for 2012 =

(Projected total IPD for the PRH/RH for 2012)×(Targeted Poor given in Table 4

The targeted IPD beneficiaries for the year 2013, 2014 and 2015 are calculated in the similar fashion.

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Cross Checking Since this method of target setting is completely new it was necessary to cross check it with other formulae in order to justify the methodology. Cross checking of the targeted poor beneficiaries has been made by using the following formula:

Percentage of Targeted -Poor HEF beneficiaries =

Targeted poor-HEF beneficiaries as computed by using Table 3Total number of poor in the OD under consideration

×100

The results are reported in Annexure Table 1. It could be observed that the target set for poor IPD is not unrealistic.

2.6. Target setting for the deliveries Step 1: Calculation of expected number of pregnant women Expected number of deliveries by poor in the OD =

(Total number of poor population in OD × 26.91000 )

Where, 26.9 is the birth rate (national average). The birth rate is the number of live births per 1000 population.

Targets and assumptions: The target for the coverage of pregnant women is set by taking the Cambodia Millennium

Development Goals in to consideration. It is assumed that 70 per cent of the deliveries by poor would be covered during the year 2012 with a gradual scaling up of the coverage by 5 per cent in each year and achieving the goal of 85 per cent during 2015.

As far as the resource implications are concerned, it is further assumed that 70 per cent of the targeted deliveries are to be handled at Health Center Level and next 30 per cent at Referral Hospital Level.

2.7. Calculation of Average Cost of Beneficiaries by level of hospitals (CPA1, 2 and 3) As mentioned in the earlier section of the manual, the HEF data base contains the information on the number of beneficiaries (IPD, OPD and deliveries) and the total cost (expenditure) incurred on these beneficiaries. The data is available OD wise and separately for RH and HCs. However, no separate cost (expenditure) data is available. For the present costing exercise we collected the utilisation as well as expenditure information from HEF data base for the year 2010 and the average costs are calculated as follows:

Beneficiaries

Method of Calculation of Average and projected Total Cost by OD

RH-OPD Step 1: Calculated the Average cost of OPD by ODLet PRH1,2,3, ...,24 number of PRH-OPD beneficiaries in OD1,2,3, ...,24 during 2010Let PRHE1,2,3, ...,24 is the total expenditure incurred in OD1,2,3, ...,24 during 2010Let RH1,2,3, ...,77 is the number of RH-OPD beneficiaries in OD1,2,3, ...,77 during 2010Let RHE1,2,3,...,77 is the total expenditure incurred on the RH-OPD beneficiaries in OD1,2,3, ...,77 during the year 2010The Average cost of RH beneficiaries in OD1,2.3,...,77

(AC1,2,3...77) = (PRHE1,2,3, ...,24 + RHE1,2,3...,77) / (PRH1,2,3, ...,24+RH1,2,3, ...,77)The average cost of PRH / RH automatically becomes “0”where there is no PRH/RH in the ODs.It is known that the cost of OPD is different for different categories of Referral Hospitals (CPA1, CPA2 and CPA3). So the cost of OPD for each category of RH was calculated separately. The category of RH by OD was collected from Hospital Services Department. The average cost of CPA1, CPA2 and CPA3 hospitals was arrived at by sorting the ODs by hospital categories and finding out the average

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Beneficiaries


cost of each the following method:1. Average Cost of OPD for CPA1 hospital = (Sum total of the Average Cost

of CPA1 hospitals / Number of CPA1 hospitals in ODs)The average cost of OPD for CPA2 and CPA3 is calculated in the similar fashion.The Average cost of OPD by category of hospitals is given in worksheet 4 (Cost Sheet-2010 base).Step 2: Cost projection for 2012, 2013, 2014 and 2015The cost projections for the ODs are made by taking the targeted beneficiaries and the average cost of each category of hospital in respective ODs.The targeted number of OPD beneficiaries for the above mentioned years is calculated in the worksheet 3 (Target Setting).The projected cost of RH-OPD in OD1,2,3, ...,77 for the year 2012 = (The targeted beneficiaries for 2012 × Average cost of OPD in the respective category of hospitals in OD1,2,3, ...,77 )In some of the ODs (e.g., Mongkol Borei there are two RHs – one CPA1 and another CPA3). In this case the projected cost of targeted OPD is calculated in the following fashion:[The targeted beneficiaries for 2012 × (Average cost of OPD (reported) for CPA1 hospital + Average cost of OPD in CPA3 hospital)/2]Same method is followed where there is more than one hospital in the OD.The cost projections for RH-OPD for the years 2013, 2014 and 2015 are made in the similar fashion.

HC-OPD Step 1: Calculate the Average cost of OPD by ODLet HC1,2,3,...,1020 is the actual number of HC-OPD beneficiaries in OD1.2,3...,77 during 2010 (where health centres are distributed among the ODs depending on size and remoteness of the ODs) where 1020 is the number of HCs and 77 is the number of ODsLet ODE1,2,3,...,77 is the total expenditure incurred on the HC-OPD beneficiaries in OD1,2,3,...,77 during the year 2010The average cost of HC beneficiaries in OD1,2,3,...77 = (Total expenditure of the health centres in OD1,2,3,...77 / Number of health centre HEF beneficiaries under the respective ODs)The Average cost of OPD of the health centres is given in worksheet 4 (Cost Sheet-2010 base).Step 2: Cost projection for 2012, 2013, 2014 and 2015The cost projections for the ODs are made by taking the targeted beneficiaries and the average cost of HC beneficiaries.The targeted number of HC-OPD beneficiaries for the above mentioned years is given in the worksheet 3 (Target Setting).The projected cost of HC-OPD for OD1,2,3,...77 for the year 2012 = (Number of targeted HC-OPD beneficiaries in OD1,2,3,...77 for 2012 × Average cost of HC-OPD beneficiaries in OD1,2,3,...77)The projected cost of HC-OPD for the years 2013, 2014 and 2015 is calculated in the similar fashion.

RH-IPD Direct cost – User Fee

The total IPD is divided into three categories:(1) General IPD (All IPDs excluding surgical and delivery IPD)(2) Surgical IPD(3) Delivery IPD.At present there is no baseline cost (expenditure) data for surgical IPD and Delivery IPD cases. Baseline utilisation data is available for the deliveries. However, a hospital costing study has already been initiated and it is hoped that the cost estimates for delivery and surgical cases would be available separately

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by February 2012. Therefore in the expansion plan provisions are made to incorporate the information once the cost data is available. However, the present projection assumes the targeted surgical beneficiaries to be “0” and the average user fee cost for deliveries to be same as user fee cost of general IPD. Keeping these points in mind we have made the projections in the following way:Step 1: Calculate the Average cost of IPD-User Fee by ODLet “GIPD- OD1,2,3,...77” is the actual number of General IPD beneficiaries in OD1,2,3,...77 during 2010 respectively.Let “FEE-OD1,2,3,...77” is the total expenditure incurred towards user fees on General IPD beneficiaries in OD1,2,3,...77 during the year 2010 respectively.The Average user fee for General-IPD beneficiaries in GIPD- OD1,2,3,...77

= (FEE-OD1,2,3,...77 / GIPD- OD1,2,3,...77)It is known that the IPD-User fee would vary across the level of hospitals. Therefore user fee component of the direct benefit cost of IPD for each category of RH is calculated separately. The average cost of CPA1, CPA2 and CPA3 hospitals is arrived at by sorting the ODs by hospital categories and finding out the average cost of each by using the following formula:

1. User fee per IPD for CPA1 hospital = (Sum total of the average user fee of CPA1 hospitals (reported data) / Number of CPA1 hospitals in OD1,2,3,...77). For the ODs not having CPA1 hospitals the value of user fee is automatically “0”

The average user fee of IPD for CPA2 and CPA3 is calculated in the similar fashion.The average user fee cost of IPD by category of hospitals is given in worksheet 4 (Cost Sheet-2010 base)5.Step 2: Cost projection for 2012, 2013, 2014 and 2015The cost projections for the OD1,2,3,...77 are made by taking the targeted beneficiaries in the respective ODs and the user fee per IPD for each category of hospitals in those ODs.The targeted number of IPD beneficiaries for the above mentioned years is given in the worksheet 3 (Target Setting).The projected IPD-User fee in OD1,2,3,...77 for the year 2012 = (The targeted IPD beneficiaries in OD1,2,3,...77 for 2012 × User fee per General IPD for the Category of hospital in OD1,2,3,...77)In some of the ODs (e.g., Mongkol Borei there are two RHs – one CPA1 and another CPA3). In this case the projected user fee of targeted IPD is calculated in the following manner:[(Targeted General IPD beneficiaries for 2012) × (User fee per General IPD for CPA1 hospital in the OD+ User fee per General IPD for CPA3 hospital in the same OD)/2]Same method is followed where there is more than one referral hospital in the OD.The projection of user fee cost for General IPD for the years 2013, 2014 and 2015 is made in the similar fashion.The average user fee cost of IPD by category of hospitals is given in worksheet 4 (Cost Sheet-2010 base).

RH-IPD Direct cost –Food

Step 1: Calculation of baseline average cost:Let “IPD-OD1,2,3,...77” is the actual number of total IPD (General IPD+ Delivery IPD+ Surgical IPD) beneficiaries in OD1,2,3,...77 during 2010

5 As the cost as well as utilisation figures for surgical IPD cases is not reported in the baseline data, it was not possible to make any projection for the surgery.

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Beneficiaries


Let “F-OD1,2,3,...77” is the total expenditure incurred for food on total IPD beneficiaries in OD1,2,3,...77 during the year 2010 respectively

The average food cost per IPD beneficiaries in OD1,2,3,...77

= (F-OD1,2,3,...77 / IPD-OD1,2,3,...77)It is known that the average food cost vary across the level of hospital and mostly depend on the length of stay and complexity of cases. Therefore food cost component of the direct benefit cost of IPD for each category of RH is calculated separately. The average food cost of CPA1, CPA2 and CPA3 hospitals is arrived at by sorting the ODs by hospital categories and finding out the average cost of each by using the following formula:

Average food cost per IPD for CPA1 hospital in OD1,2,3,...77 = (Sum total of the average food cost of CPA1 hospitals in OD1,2,3,...77 / Number CPA1 hospitals in

OD1,2,3,...77)The average food cost of IPD for CPA2 and CPA3 is calculated in the similar fashion.Step 2: Food Cost projection for 2012, 2013, 2014 and 2015The cost projections for OD1,2,3,...77 are made by taking the targeted beneficiaries and the average food cost per IPD for each category of hospitals in OD1,2,3,...77.The targeted number of IPD beneficiaries for each category of hospitals for the above mentioned years is given in the worksheet 3 (Target Setting).The projected IPD food cost for CPA1 hospitals in OD1,2,3,…77 during 2012 = The targeted beneficiaries for CPA1 hospitals in OD1,2,3,…77 during 2012 × Average food cost per IPD for the CPA1 hospital in OD1,2,3,...77

¿

¿

The projected IPD food cost for CPA2 hospitals in OD1,2,3,…77 during 2012 = (The targeted beneficiaries for CPA2 hospitals in OD 1,2,3,…77 during 2012 × Average food cost per IPD for the CPA2 hospital in OD1,2,3,...77

¿

¿

The projected IPD food cost for CPA3 hospitals in OD1,2,3,…77 during 2012 = (The targeted beneficiaries for CPA3 hospitals in OD 1,2,3,…77 during 2012 × Average food cost per IPD for the CPA3 hospital in OD1,2,3,...77

¿

¿

The projected food cost for the year 2013, 2014 and 2015 is calculated in the similar fashion.In some of the ODs (e.g., Mongkol Borei there are two RHs – one CPA1 and another CPA3). In this case the projected food cost of targeted IPD6 is calculated in the following fashion:

( Targeted IPD beneficiaries for 2012 )×(Food cost per IPD for CPA1 hospital+Food cost per IPD for CPA3 hospital)2

Same method is followed where there is more than one hospital in the OD.The projection of transport cost for IPD for the years 2013, 2014 and 2015 is made in the similar fashion.

RH-Transport cost

Step 1: Calculation of baseline average cost:Let “IPD-OD1,2,3,...77” is the actual number of total IPD (General IPD+ Delivery IPD+ Surgical IPD) beneficiaries in OD1,2,3,...77 during 2010Let “T-OD1,2,3,...77” is the total expenditure incurred for transport on total IPD beneficiaries in OD1,2,3,...77 during the year 2010 respectively

The average cost of transport per IPD beneficiaries in OD1,2,3,...77

= (F-OD1,2,3,...77 / IPD-OD1,2,3,...77)

6 Note: Targeted IPD is the sum of General IPD, Surgical IPD and Delivery IPD

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Beneficiaries


It is known that the average transport cost vary across the level of hospital depending on the remoteness. Therefore the transport cost component of the direct benefit cost of IPD for each category of RH is calculated separately. The average transport cost of CPA1, CPA2 and CPA3 hospitals is arrived at by sorting the ODs by hospital categories and finding out the average cost of each by using the following formula:Average transport cost per IPD for CPA1 hospital in OD1,2,3,...77 = (Sum total of the average transport cost of CPA1 hospitals in OD1,2,3,...77 / Number CPA1 hospitals in

OD1,2,3,...77)The average transport cost of IPD for CPA2 and CPA3 is calculated in the similar fashion.Step 2: Transport Cost projection for 2012, 2013, 2014 and 2015The cost projections for OD1,2,3,...77 are made by taking the targeted beneficiaries and the average transport cost per IPD for each category of hospitals in OD1,2,3,...77.The targeted number of IPD beneficiaries for each category of hospitals for the above mentioned years is given in the worksheet 3 (Target Setting).The projected IPD transport cost for CPA1 hospitals in OD 1,2,3,…77 during 2012 = The targeted beneficiaries for CPA1 hospitals in OD1,2,3,…77 during 2012 × Average transport cost per IPD for the CPA1 hospital in OD1,2,3,...77

¿

¿

The projected IPD transport cost for CPA2 hospitals in OD1,2,3,…77 during 2012 = (The targeted beneficiaries for CPA2 hospitals in OD 1,2,3,…77 during 2012 × Average transport cost per IPD for the CPA2 hospital in OD1,2,3,...77

¿

¿

The projected IPD transport cost for CPA3 hospitals in OD 1,2,3,…77 during 2012 = (The targeted beneficiaries for CPA3 hospitals in OD 1,2,3,…77 during 2012 × Average transport cost per IPD for the CPA3 hospital in OD1,2,3,...77

¿

¿

The projected transport cost for the year 2013, 2014 and 2015 is calculated in the similar fashion.In some of the ODs (e.g., Mongkol Borei there are two RHs – one CPA1 and another CPA3). In this case the projected transport cost of targeted IPD7 is calculated in the following fashion:

( Targeted IPD beneficiaries for 2012 )×(Transport cost per IPD for CPA1 hospital+Transport cost per IPD 2

Same method is followed where there is more than one hospital in the OD.The projection of transport cost for IPD for the years 2013, 2014 and 2015 is made in the similar fashion.

RH-IPD Direct cost – non-food and grants

Note: The method of calculation is same as the method explained for food and transport cost. Therefore it is not repeated here.

Cost of deliveries at HC and RH:

As already mentioned that there is no separate baseline data that is available for the cost of deliveries in the ODs. Therefore the following assumptions are made:1. The approximate cost of deliveries in HC is USD 152. The cost of delivery is same as the cost of IPD in the RH and PRHs. The average cost of IPD at different category of hospitals is already explained in the table.Step 1: Target setting at HC level for 2012:1. The target setting for 2012 (70%, 80% 85%, 85%) of total expected poor

7 Note: Targeted IPD is the sum of General IPD, Surgical IPD and Delivery IPD

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Beneficiaries


deliveries:Therefore in this section we explain the method of calculating the projected cost of deliveries at HC and RH level for 2012. 2013, 2024 and 2015.

Assumptions: 30% of the Targeted deliveries conducted at RH Level 70% of the targeted deliveries are conducted at HC level

As assumed 70% of the deliveries will be conducted at HC levelEstimated cost at HC level for 2012=

(Total Population of OD1,2,3,…77 in 2012×Poverty rate of OD1,2,3,…77 during 2010

2012 × 26.91000

× Targeted Number of deliveries at HC in OD 1,2,3,…77during2012

×15 USD Per Person)

Estimated cost at RH Level for 2012=

(Total Population of OD1,2,3,…77 in 2012×Poverty rate of OD1,2,3,…77 during 2010

2012 × 26.91000

× Targeted Number of deliveries at HC in OD 1,2,3,…77during2012

×Average cost of IPD in RH1,2,3 ,… ,77 in OD1,2,3,…77 )Where 26.9 is the birth rate (number of live births out of 1000 populationThe estimated cost of deliveries for the RH and HC for the years 2013, 2014 and 2015 is calculated in the similar fashion.

Calculation of Indirect cost

The indirect cost is taken as the percentage of total direct cost. In other words, it is proportionate to the total direct cost i.e., if total direct cost in OD1 ,2,3 ,…77 increases , the indirect costs such as cost of administration, equipment, program development and pre-ID increases proportionately. The Following assumptions are made relating to indirect cost:1. The percentage of Indirect cost across the OD1,2,3,…77 remains same irrespective of level of rererral hospitals

Level of Hospitals CPA1 CPA2 CPA3Cost of Administration

= 17.97 17.97 17.97

Equipment = 0.05 0.05 0.05Others (TA & PGM Development)

= 5.29 5.29 5.29

Pre ID = 1.47 1.47 1.47Formulae:

1. The indirect cost for administration in OD1 ,2,3 ,…77 = (Total direct benefit cost in OD1,2,3,…77 × 17.9%)

2. The indirect cost for equipment in OD1 ,2,3 ,…77 = (Total direct benefit cost in OD1,2,3,…77 × 0.05%)

3. The indirect cost TA and program development in OD1 ,2,3 ,…77 = (Total direct benefit cost in OD1,2,3,…77 × 5.29%)

4. The indirect cost for Pre – ID in OD1 ,2,3 ,…77 = (Total direct benefit cost in OD1,2,3,…77 × 1.47%)

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Annexure Table 1: Expansion HEF 2012

Province No.

Operational District(s) Model Source of

Fuding Adjusted

Population 2012

Poor beneficiaries

estimated by ODPoverty rate by OD (prov.rate) Total RHs

Expansion HC with

HEFTotal HCs

Battambang 1 Thmor Koul Linkage CBHI & HEF HSSP2 211,387 63,628 30.1% 1 10 17Kg.Cham 2 Srei Santhor Linkage CBHI & HEF HSSP2 170,965 41,543 24.3% 1 8 13Kg. Speu 3 Korng Pisey Linkage CBHI & HEF HSSP2 181,149 54,526 30.1% 1 10 19Kg. Thom 4 Baray Santuk Linkage CBHI & HEF HSSP2 281,584 75,748 26.9% 1 10 19Kep 5 Kep Linkage CBHI & HEF HSSP2 39,058 11,756 30.1% 1 4 4Takeo 6 Bati Linkage CBHI & HEF HSSP2 182,761 55,011 30.1% 1 8 13Prey Veng 7 Svay Antor Linkage CBHI & HEF HSSP2 182,466 54,922 30.1% 1 10 17

Total 1,249,370 357,134 7 60 102Expansion plan 2014

Province No.


Fuding Adjusted

Population 2013

Poor beneficiaries

estimated by ODPoverty rate by OD (prov.rate) Total RHs

Expansion HC with

HEFTotal HCs

Kg.Cham 1 O Reang Ov Linkage HEF&CBHI HSSP2 78,497 19,075 24.3% 1 5 8

Kanhdal

2 Koh Thom Linkage HEF&CBHI HSSP2 170,991 51,468 30.1% 1 7 123 Ang Snoul Linkage HEF&CBHI HSSP2 122,926 37,001 30.1% 1 5 74 Ponhea Leu Linkage HEF&CBHI HSSP2 119,710 36,033 30.1% 1 7 75 Muk Kampoul Linkage HEF&CBHI HSSP2 96,519 29,052 30.1% 1 6 6

Prey Veng 6 Mesang Linkage HEF&CBHI HSSP2 93,652 28,189 30.1% 1 7 107 Kamchay Mear Linkage HEF&CBHI HSSP2 98,071 29,519 30.1% 1 8 11

Total 780,366 230,337 7 45 61

Expansion HEF 2014

Province No.


Fuding Adjusted

Population 2014

Poor beneficiaries estimated by

OD

Poverty rate by OD (prov.rate) Total RHs

Expansion HC with

HEFTotal HCs

Kg.Cham 1 Kroch Chhma Linkage HEF & HEF HSSP2 92,097 22,284 24.2% 1 11 11Kg.Speu 2 Oudong Linkage HEF & HEF HSSP2 241,300 72,631 30.1% 1 9 9

Kandal 3 Saang Linkage HEF & HEF HSSP2 179,618 54,065 30.1% 1 12 124 Kean Svay Linkage HEF & HEF HSSP2 291,588 87,768 30.1% 1 19 19

Prey Veng 5 Neak Loeung Linkage HEF & HEF HSSP2 146,589 441,123 300.9% 1 17 17

Total 951,192 5 68 68

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Annexure Table 2: Percentage Admitted out of total poor population (Cross Check)

Sl No Operational District 2012 2013 2014 20151 Mongkol Borei 6.57 7.88 7.88 7.882 Ou Chrov 2.27 3.03 3.78 4.543 Preah Net Preah 1.29 1.72 2.16 2.594 Thma Puok 1.66 3.32 4.15 4.975 Thma Koul 0.43 0.85 1.06 1.286 Mong Russei 5.60 5.96 5.96 5.967 Sampov Luon 1.54 2.05 2.56 3.078 Battambang 5.57 6.68 6.68 6.689 Sangkae 0.00 0.00 0.00 0.0010 Chamkar Leu - Stueng Trang 7.77 7.77 7.77 7.7711 Choeung Prey - Batheay 6.10 7.32 7.32 7.3212 Kampong Cham - Kampong Siem 11.74 14.09 14.09 14.0913 Kroch Chhmar - Stueng Trang 0.00 0.00 1.18 2.3514 Memut 12.03 12.03 12.03 12.0315 O Reang Ov - Koh Soutin 0.00 1.52 3.05 3.8116 Ponhea Krek - Dambae 8.77 8.77 8.77 8.7717 Prey Chhor - Kang Meas 7.08 7.08 7.08 7.0818 Srei Santhor - Kang Meas 1.05 2.09 2.62 3.1419 Tbong Khmum - Kroch Chhmar 3.46 4.33 5.19 5.1920 Kampong Chhnang 2.51 5.02 6.28 7.5321 Kampong Tralach 1.63 2.18 2.72 3.2622 Boribo 0.65 1.31 1.63 1.9623 Kg Speu (Including PRH) 1.74 2.32 2.90 3.4824 Kong Pisey 0.42 0.85 1.06 1.2725 Ou Dong 0.00 0.00 0.71 1.4126 Baray Santouk 1.79 3.57 4.47 5.3627 Kg Thom 4.24 4.24 4.24 4.2428 Stong 4.41 4.41 4.41 4.4129 Angkor Chey 4.45 8.89 11.11 13.3430 Chhouk 2.53 5.07 6.33 7.6031 Kampong Trach 3.35 6.70 8.38 10.0632 Kampot 18.66 18.66 18.66 18.6633 Ang Snuol 0.00 0.00 0.00 0.0034 Kean Svay 0.00 0.00 0.16 0.3235 Koh Thom 0.00 0.91 1.82 2.2836 Ksach Kandal 2.19 4.38 5.48 6.5737 Muk Kam Poul 0.00 0.19 0.38 0.4738 Ponhea Leu 0.00 0.00 0.00 0.0039 Saang 0.00 0.00 0.32 0.6340 Takhmau 1.64 3.28 4.10 4.9241 Kep 1.72 3.44 4.30 5.1642 Smach Mean Chey 7.04 7.04 7.04 7.0443 Srae Ambel 8.21 8.21 8.21 8.21

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Sl No Operational District 2012 2013 2014 201544 Chhlong 10.54 10.54 10.54 10.5445 Kratie 6.81 6.81 6.81 6.8146 Senmonorum 8.13 8.13 8.13 8.1347 Samraong 5.98 7.17 7.17 7.1748 Pailin 1.60 3.21 4.01 4.8149 Cheung 0.56 0.67 0.67 0.6750 Kandal 2.61 3.49 4.36 5.2351 Lech 1.38 1.38 1.38 1.3852 Tbong 2.01 2.01 2.01 2.0153 Tbeng Meanchey 5.44 5.44 5.44 5.4454 Kamchay Mear 0.00 0.30 0.61 0.7655 Kampong Trabek 1.49 2.98 3.73 4.4756 Mesang 0.00 0.57 1.14 1.4357 Neak Loeung 0.00 0.00 0.42 0.8558 Peareang 4.79 4.79 4.79 4.7959 Preah Sdach 7.05 7.05 7.05 7.0560 Prey Veng 0.78 1.56 1.95 2.3461 Bakan 4.82 4.82 4.82 4.8262 Sampov Meas 4.77 4.77 4.77 4.7763 Banlung 4.41 4.41 4.41 4.4164 Kralanh 4.22 4.22 4.22 4.2265 Siem Reap 6.62 7.94 7.94 7.9466 Sot Nikum 2.16 2.16 2.16 2.1667 Ankor Chhum 1.01 1.34 1.68 2.0168 Sihanouk Ville 6.09 6.09 6.09 6.0969 Steung Treng 12.06 12.06 12.06 12.0670 Chi Phu 2.58 5.15 6.44 7.7371 Romeas Hek 1.37 2.74 3.42 4.1072 Svay Rieng 6.68 8.02 8.02 8.0273 Bati 0.69 1.39 1.74 2.0874 Daun Keo 7.28 9.10 10.93 10.9375 Kirivong 4.94 5.92 5.92 5.9276 Prey Kabass 0.47 0.94 1.17 1.4177 Ang Rokar 4.57 5.71 6.85 6.85

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Section 4: Works carried out for Hospital Costing Study

4.1. IntroductionIt was realised that the cost data on deliveries and surgeries are not available with the URC. Therefore During the fourth phase of HEF estimates, it was proposed to conduct a hospital costing study in order to obtain the cost estimates for deliveries and surgeries separately. Therefore during this phase of the work the following activities were carried out related to hospital costing. The following activities were carried out on hospital costing study.

1. Preparation of costing templates for the hospital costing study. The results of the study is expected to set up PPM in different CPA levels of hospitals in Cambodia (Annex 4.1: Costing templates soft copy in CD)

2. Convincing the supervisor about the templates and methodology for the costing study3. Collaboration with development partners (Specifically: AFD, BTC and URC) to

investigate the requirements for the costing study and obtain a consensus on the methodology proposed, resources required etc. The meeting was held in URC office during the month of September 2011.

4. Preparation of proposal and tools for pilot study in Kampong Cham (Annex 4.2: Proposal for pilot study - hard copy inserted and soft copy in CD)

5. Travel to Kampong Cham for Pilot testing (one week)6. Helping URC in the production of draft report of pilot study (Annex 4.3: Results of

Pilot study- soft copy in CD) 7. Presentation of the initial findings of the pilot study (prepared by Annette (URC) with

the technical inputs from me) on 15th August 2011 and the comments received. . 8. Revised the proposal for hospital costing study and submitted to Dr Kanha for the

approval of the Project Director. During my period of annual leave (21st Sept. to 6th

October 2011) Dr Kanha modified the proposal a bit and submitted the proposal to the Project Director for issuing necessary letters to the hospitals regarding the study. The study has already been initiated. (Ref: Annex 4.4 – Soft copy of the final proposal and methodology in CD)

Annex 4.1: Costing template for hospital costing – soft copy for your reference

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Annex 4.2: Proposal for piloting – hard copy inserted and soft copy in CD)

Proposal for Hospital Costing Study in Cambodia

1. Introduction Agence Française de Développement (AFD), Belgian Development Agency (BTC), and University Research Company (URC) have agreed to support the Cambodia Ministry of Health (MOH) in designing a study to estimate the costs associated with delivering the Complementary Package of Activities (CPA) for referral hospitals. The partners along with MOH will leverage the study findings to develop recommendations on the effective and efficient use of limited health care resources. Please refer to Annex 1, “Hospital Costing Study Technical Team Members,” for a list of the team members involved in the study.

Prakas 296, the “National Charter on Health Financing” of 1996 provided a framework for the financing of hospitals and established the legal basis for the introduction of user fees. While the procedures related to spending user fee income and approving new user fees are well defined, little guidance is provided regarding the criteria and method for calculating or setting new user fees.

The annex to Prakas 296 refers to the charter as a rolling process and specifies the need for its periodic revision based on systematic and synthetic analysis of routine information and special studies. Component HCF 5.3 of the Second Health Sector Support Program (HSSP2) stipulates to perform on a regular basis the costing of CPA.

At present, a CPA1-3 hospital financing strategy which links hospital costs to income of different funding sources does not exist. Several hospital costing studies have been conducted in Cambodia over the last 10 years. As new health financing schemes have been established and capacity and utilization have changed, updated costing estimates are needed to inform the development of a hospital financing strategy.

2. Background and rationale Several hospital costing studies have been conducted in Cambodia over the last 10 years. This study draws upon the methodological approaches and lessons learned from these studies. Please refer to Annex 2, “Side-by-Side Comparison of Cambodia Hospital Costing Studies,” for a summary of the objectives and design of these costing studies. Numerous other studies also describe approaches to costing, although they focus primarily on the costs of national health programs, specific interventions, or health centers. These resources have been reviewed as part of the literature review, although are less relevant for informing the design of this study.

This study would build on prior studies in several ways, including:

Providing updated costs for CPA1-3 hospitals Utilizing multiple costing methods to triangulate costs and validate any one

estimation approach Identifying costs at the service level, rather than the inpatient / outpatient level Leveraging international benchmarks to revise prices and quantities for adjusted

cost estimates

3. Objectives of the study2.1. General Objectives

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The general objective for the costing study is to estimate historical costs expended to operate CPA1-3 hospitals to inform the development of a hospital financing strategy. HSSP2 included the development of a hospital financing strategy as a condition to continue Service Delivery Grants (SDGs) for provincial hospital Special Operating Agencies (SOAs). This study will inform discussions regarding MOH, donor, and out-of-pocket contribution expectations.

2.2. Specific ObjectivesThe specific objectives of the costing study are to:

Inform the development of a provider payment methodology to set rates for CPA1-3 hospitals

Inform the development a standardized benefit package

Inform cost projections for the Health Equity Fund (HEF) program

Revise the Health Financing charter on the basis of the present financing strategy of the hospitals

4. Scope of the studyThis study only relates to CPA1-3 hospitals and not the national hospitals, as they have mostly become autonomous as public enterprises. The scope does not include the costing of national health programs, Provincial Health Departments (PHDs), Operational District (OD) offices, or health centers.

The study will focus on both income and expense data to understand the full picture of hospital financial management. Historical costs will be estimated based on hospital, PHD, and OD financial records. Data on revenues and expenses generated from January 1 – December 31, 2010 will be collected and estimated as part of the study.

In a separate analysis, historical costs will be adjusted using revised quantities and prices based on validation studies and international benchmarks. A subsequent study may be explored to estimate costs based on utilization projections or costs associated with care delivery that complies with clinical practice guidelines.

The scope includes both inpatient and outpatient services, with the unit of analysis as an inpatient day or an outpatient equivalent. With this level of analysis, costs will be assigned to wards and departments (cost centers). As certain cost and utilization data is aggregated (e.g., administrative costs, utility costs), allocation statistics will provide the basis for assigning these costs to wards and departments, resulting in unit costs based on inpatient days or outpatient equivalents.

The study will focus on recurrent costs only and not capital assets, as capital and depreciation costs are carried in Ministry of Economy and Finance (MEF) asset books and are not typically subject to control at the hospital level. Recurrent costs associated with capital assets (e.g., minor maintenance, supplies) will be considered as these costs are paid by hospitals from their working capital funds.

Prior to initiating the costing study, AFD, BTC, and URC conducted site visits to understand hospital financial management systems and determine data availability. The partners and MOH agreed to conduct a pilot to pre-test the methodology and model for data collection and analysis to ensure it yields the required information to estimate costs. This paper provides background on the data collection and analysis activities for the pilot, in addition to planned activities for the costing study.

5. Expected outcomesThis study is intended to provide support to the MOH by informing discussions with different stakeholders regarding alternative financing mechanisms. The study will aim to

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provide MOH with recommendations regarding needed budget allocations from government, HEF, and out-of-pocket contributions. Updated cost estimates will inform hospital financing policy with the intention of achieving improvements in efficiency, \equity, quality of services, and sustainability. The study will determine hospital capacity to generate needed revenue. Additionally, the study will inform improvements to hospital administration and accounting management systems, essential for planning, budgeting, and monitoring hospital performance. The study also aims to explore cost recovery options for the HEF program.

6. Methodology and sampling (a) Study designThe study design is retrospective in nature, leveraging data from historical financial reports, utilization records, budgets, invoices, inventories, contracts, etc.

(b) Study population The pilot will be conducted with Kampong Cham Referral Hospital due to its strong contracting relationship history with BTC, its complexity as a CPA3 hospital, and its proximity to Phnom Penh to facilitate data collection. Additionally, Kampong Cham’s organizational structure and financial and operational management are considered representative of other provincial hospitals.

The costing study will rely on a purposive sample of hospitals. Hospitals will be selected due to their contracting arrangement based on the following assumptions: they have more adequate resourcing, their costs more likely reflect the quantities and prices of resources needed to provide services, and their data available for collection is likely more accurate and of higher quality. Additionally, access to stakeholders within the facilities will be easier from an operational standpoint than in facilities without a contracting relationship.

Nine hospitals are recommended for inclusion in the sample, including three facilities at each CPA level. The CPA3 provincial hospitals will be SDG recipients and the Level CPA1 and CPA2 hospitals will be the primary district referral hospital in ODs with SOA status. Political support and strong stakeholder involvement is likely within the SDG/SOA models. Generalization of the findings regarding hospital costs beyond the SDG/SOA population of hospitals will be taken with caution.

The nine hospitals will be selected to participate in the study. The lists of the provinces from which the hospitals are to be selected are given below. However, it must be remembered that the hospitals mentioned in the sample are tentative and subject to change after the result of the pre-testing.

Facility Name CPA Level Province Operational District Date Granted

SOAHospital 1 Level 1 Siem Reap KrolanhHospital 2 Level 1 Koh Kong Sre AmbelHospital 3 Level 1 Kampong Cham Chamkar Leu Stung TrungHospital 4 Level 2 Kampong Cham MemotHospital 5 Level 2 Takeo KirivongHospital 6 Level 2 Koh Kong Smach Meanchey ODHospital 7 Level 3 Battambang BattambangHospital 8 Level 3 Takeo DonkeoHospital 9 Level 3 Kampong Cham Kampong Siem

The study will use step down costing methodology for its purpose and the costing software (Cost-It for Hospitals) developed by WHO will be used for this. However, the software will be

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modified a bit depending on the availability of the necessary information at Cambodian Hospitals.Cost DefinitionsThe study team will leverage the widely accepted World Bank and USAID cost definitions specified in Designing and Implementing Health Care Provider Payment Systems: How To Manual. This resource is accessible at: http://siteresources.worldbank.org/HEALTHNUTRITIONANDPOPULATION/Resources/Peer-Reviewed-Publications/ProviderPaymentHowTo.pdf

(c) Conceptual framework

Note: The cost for each service would be the sum total of Labour and material cost. During data collection process it will be ensured that information on both the cost components are collected

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Indirect cost centers

(Administrative)

Ancillary

(Intermediate Cost Centers)

Clinical

(Direct Cost Centers)


(Administrative)

Ancillary


Clinical


Administration

Laundry

Security

Accounting

Kitchen


(Administrative)

Ancillary


Clinical


Total cost = Labor cost+ Material cost

Unit cost of service by Direct cost centres i.e., AC1, AC2, AC3…ACn (n = Number of direct cost centers)

Total cost of service by Direct Cost Centres C1, C2, C3…Cn (n = Number of direct cost centers)

Clinical(Direct Cost Centers)

Ancillary(Intermediate Cost Centers)


(Administrative)

Administration Laundry SecurityAccounting Kitchen TransportEtc…..

Cardiology Internal medicine Intensive care Mental health Neurology Ophthalmology Pediatrics Surgery TuberculosisGynecology Infectious diseases Maternity Neonatal Oncology Otolaryngology Substance abuse Trauma UrologyEtc…

Blood transfusion Diagnostic Operating theater PharmacyX-rayDental Laboratory Pathology Physiotherapy

The list provided in the flow chart above is exhaustive. However, the cost centres are subject to change depending on the level of hospitals and the type of services available.

(d) Data collection and validation – Piloting the methodologyDuring the pilot phase of the study the data collection team would comprised of Dr. Purna Chandra Dash (MoH), Dr. Him Phannary (BTC), Dr. Slot Rida (URC), and Ms. Annette Martin (URC). The team members have backgrounds in hospital budgeting, accounting, and finance and are familiar with hospital-level data sources. A larger team of experts including a team of trained investigators will be used for data collection during main survey.

During the pilot phase the team will emphasize on the data availability, and the usefulness of the available data for the study. The intention is not to audit or institute any punitive measures against Kampong Cham, rather to inform the development of a hospital financing strategy.

The team will collect data from various sources, including referral hospital departments (e.g., Administration, Accounting, Pharmacy, and Lab) and PHD and OD offices. The intention is for the full range of resources used to provide services, from all sources, to be included and costed. Rather than using either nominal budgets or historic expenditure records, data from both sources will be used, along with other hospital documents and direct observation in order to validate the data and triangulate costs.

Due to use of advance registers, irregular funding cycles, and payment for services rendered in prior accounting periods, a full calendar year of data will be collected, with some data items needed for targeted months only. Because of the resource intensive nature of the analysis, the team will estimate costs for four months rather than the full year. To capture potential seasonal variation in utilization, one month every quarter will be used for costing (January, April, July, and October).

Please refer to Annex 3, “Hospital Costing Data Collection Tool,” for the pilot data collection tool that specifies data items requested, including the preferred format, time period, and source, in addition to notes regarding how the data will be used.

Several onsite validation studies are proposed to verify the data collected from the above sources, including:

HIS Records: Reported HIS utilization data will be validated by reviews of the Cashier’s notebook where visits and discharges, services, and payment by patient type are recorded.

Staff Time Worked: Staff schedules will be validated by direct observation through three daily ward spot checks conducted at randomly selected times over the course of the site visit.

Operating Expense Purchases: A random sample of invoices (5 per month) will be validated by interviews with the local vendors regarding the market price for those goods and services. Requests will be made to review vendor records of those purchases (e.g., pharmacy, petrol, electricity).

Pharmacy Inventory Records: A random sample of 20 drugs and medical supplies from the RACHA database will be selected for a validation study. Onsite inventory counts will be conducted and cross-checked with invoices, request forms, ward delivery forms, consumption reports, and stock in / stock out records.

Following the pilot, the team will recommend a data collection approach for the costing study based on their understanding of the resource intensity of data collection and the level of effort required to organize and analyse the data. The team will explore working with available MOH staff and hiring data collectors. Data collectors will receive extensive training prior to initiating the site visits for the costing study.

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A 10-week effort is proposed to conduct the costing pilot, with the objective of analysing the results and recommending an approach for the costing study by mid-September. This timing will allow for data from the study to be available by the end of the calendar year to inform the Annual Operating Plan (AOP) budgeting process.

Following the pilot conclusion and Phchum Ben Holiday, the team proposes conducting site visits in October at all the hospitals in the sample for data collection. During November and December, the team will analyse the data and populate the model, targeting the end of December to present recommendations to MOH.

(e) Data analysisA brief description of how the data will be used follows. Step-down accounting and normative modelling will be employed to arrive at hospital costs. Step-down accounting will be used to allocate the total (direct and indirect) costs of the administrative and ancillary departments to the clinical wards. The intention is to arrive at the cost of an inpatient day or outpatient equivalent. Data from direct observation, interviews, and international benchmarks will be used to revise inputs to estimate normative costs. Below is a brief outline of the step-down method.

Step 1: Identify Hospital Services Determine which services will be assigned unit costs. Consider whether to cost services individually or to bundle them by ward or another factor (e.g., resource intensiveness).

Step 2: Standardize Cost CentresIdentify cost centres that correspond to the existing organizational structure of the hospitals in the sample. Organize cost centres into three tiers:

1. Clinical Departments (Direct Cost Centres)

2. Ancillary Departments (Intermediate Cost Centres)

3. Administrative Departments (Indirect Cost Centres)

Conceptual framework above gives the details on these cost centres.

Step 3: Assign Direct Costs to Cost CentresAssign direct costs (e.g., salaries, drugs and supplies, food) to each ward / department. Information from the staffing work time allocation analysis will facilitate assignment of staff to multiple departments.

Different approaches could be used to allocate drug and supply costs. As supplies contribute a small share to total costs, the assumption could be made that the intensity of

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the service drives the use of supplies. Therefore, supply costs can be apportioned according to number of inpatient days.

Allocation of drug costs could be done in different ways. Drugs could be considered its own cost center and allocations made towards based on their share of prescriptions, discharges, or patient days. Alternatively, drugs could be allocated to each ward based on an estimated weighting that assigns a value of drugs per inpatient day.

Step 4. Determine Allocation Basis for Apportioning Indirect Costs to Cost CentresBarring indirect cost data by department, several options exist for determining each department’s use of resources, including:

(a) Total user fee / HEF / CBHI revenue

(b) Total salary expense

(c) Total discharges

(d) Total patient days

(e) Total square feet

(f) Share of total hospital direct costs

Total number of discharges is recommended as an allocation basis, however, several methods will be explored and the outcome of the allocation compared.

Step 5. Perform Step-down Cost AccountingUsing allocation statistics, allocate the total (direct and indirect) costs of the administrative departments to the ancillary departments. Then allocate the total costs of the ancillary departments to the clinical departments.

Step 6. Compute Total and Unit Cost for Each Final Cost CenterCompute each department’s total cost by adding the costs allocated from each administrative and ancillary department to the individual department’s total (direct and indirect) costs. Using the department total number of inpatient bed days and outpatient visits; compute an average cost per bed-day and average cost per visit.

Calculate the cost per case for each discharge, by multiplying the cost per inpatient bed day of the department from which the patient was discharged by the actual length of stay for that case.

ModelA single model will be developed to estimate hospital costs, but assumptions will vary based on two different scenarios selected. The first scenario – Historical Cost Model – will estimate costs using HIS data and hospital, PHD, and OD records alone. The second scenario – Adjusted Historical Cost Model – will estimate costs using revised quantities and prices based on the validation studies conducted and international benchmarks. A third scenario – Rational Cost Model – may be explored in a subsequent study to estimate costs associated with care delivery that complies with clinical practice guidelines. The World Health Organization CostIT model will be leveraged for the study, tailored specifically for Cambodia’s country context. Please refer to Annex 5, “CostIt (Costing Interventions Template) Version 4.5,” for the WHO template that will be leveraged for the costing analysis.

RESULT AND ANALYSIS(To be completed following the study)

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DISCUSSION, CONCLUSION, POLICY IMPLICATION, AND RECOMMENDATION:(To be completed following the study)

REFERENCES1. Fabricant S. Cost Analysis of Essential Health Services in Cambodia. MOH/WHO

Health Sector Reform Phase III Project. Final Report of Data Analysis. WHO/USAID/POPTECH. 2002.

2. Fabricant S, Kanha S, and K Thavary. Cost Analysis (Part 2) of Essential Health Services in Cambodia. MOH/WHO Health Sector Reform Phase III Project. Final Draft 11 December 2003.

3. Collins D, Chhuong CK, and K Reth. Scaling Up Child Survival Interventions in Cambodia: Service Delivery Costs. The BASICS Project/USAID. 25 February 2008.

4. Collins D, Gupta P, and E Sovannarith. Cost Projections For The Complementary Package of Activities for Referral Hospitals: Ministry Of Health, Royal Government of Cambodia. Arlington, Va., USA: Basic Support for Institutionalizing Child Survival (USAID/BASICS) for the United States Agency for International Development (USAID). 2009.

5. Cleverly WO, Cleverly JO, and PH Song. Essentials of Health Care Finance. Jones & Bartlett Learning, LLC. 2011.

6. SmithMW, Barnett PG, Phibbs CS, and Wagner TH. Microcost Methods for Determining VA Healthcare Costs, 2010.

7. Ben-Gal I, Wangenheim M, and A Shtub. A New Standardization Model for Physician Staffing at Hospitals. The International Journal of Production and Performance Management 2010;59(8):769-791.

8. Langenbrunner JC, Cashin C, and O’Dougherty S. Designing and Implementing Health Care Provider Payment Systems: How-To Manuals. International Bank for Reconstruction and Development / The World Bank. 2009.

9. Demeerec N, Stouthuysena K, and F Roodhooftb. Time-driven activity-based costing in an outpatient clinic environment: Development, relevance and managerial impact. Health Policy, 2009.

10. Hendrich A, Chow M, Skierczynski BA, Lu Z. A 36-Hospital Time and Motion Study: How Do Medical-Surgical Nurses Spend Their Time? The Permanente Journal, 2008;(12):3.

11. Sartorius K, Eitzen C, and P Kamala. The design and implementation of Activity Based Costing (ABC): a South African survey. Meditari Accountancy Research 2007;15(2):1-21.

12. Canby JB. Applying activity-based costing to healthcare settings. HealthcareFinancial Management, 2005

13. Conteh L and D Walker. Cost and unit cost calculations using step-down accounting. Health, Policy and Planning 2004;19(2):127–135.

14. Hildebrand S and A Telyukov. Cost Centers and Step-down Cost Allocation: Adjusting Hospital Cost Accounting in Issyk-kul Oblast, Kyrgyzstan. AID/ENI/HR/HP. 2004.

15. Adapted from Player S. Activity-based analyses lead to better decision making: costmanagement strategies in the health care industry. Healthcare Financial Management, 1998.

16. Shepard DS, Hodgkin D, and Y Anthony. Analysis of Hospital Costs: A Manual for Managers. Prepared for the Health Systems Development Program, World Health Organization. 1998.

17. Discussions with Hospital and OD staff during visit to Chamkar Lue Referral Hospital, July 4, 2011.

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18. Discussions with Hospital and PHD staff during visit to Siem Reap Referral Hospital, July 5, 2011.

19. Discussions with Hospital and OD staff during visit to Kralagn Referral Hospital, July 6, 2011.

Annexure 1: Hospital Costing Study Technical Team Members and responsibilities Dr. Sok KanhaDeputy Director, Department of Planning and Health InformationCambodia Ministry of Health

Responsible for overall coordination and providing technical inputs to the study

Dr. Purna Chandra DashHealth Financing Advisor, Department of Planning and Health InformationCambodia Ministry of Health

Commissioning the study, technical support, ensuring appropriate data collection and data analysis

Dr. Dirk HoremansHealth AdvisorBelgian Development Agency

Technical and financial support for commissioning the study

Dr. Him PhannaryPublic Health AdviserBelgian Development Agency

Technical support during the field work

Dr. Chan SoryaProject OfficerAgence Française de Développement

Technical and financial support for commissioning the study

Dr. Chris GrundmannChief of PartyUniversity Research Co., LLC

Technical support. Financial support in terms of organizing the manpower and resources required for commissioning the study

Ms. Annette MartinHealth Financing and Health Systems ConsultantUniversity Research Co., LLC

Technical support, Coordination of data collection, Report writing and analysis, presentation of the methodology and findings

Dr. Slot RidaSenior ResearcherUniversity Research Co., LLC

Technical support, Coordination of data collection and training of field staff.

Dr. Bun Sam NangBHEF, DPHI, MoH

Support during data collection

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Annexure 2: Side-by-Side Comparison of Cambodia Hospital* Costing Studies

Cost Analysis (Part 1)of Essential Health Services (2002)


Scaling Up Child SurvivalInterventions (2008)

Cost Projections for theComplete Package of Activities (2009)

Sponsors The World Bank, DfID, WHO Cambodia, USAID

WHO Cambodia USAID/BASICS USAID/BASICS

Objective To estimate costs for the proposed CPAHospital output was considered a proxy for the CPA to develop a first approximation for budgeting

To complement the first study by more fully determining CPA costs through estimating costs of National Health Programs, national hospitals, PHDs and ODsTo capture additional funding sources (user fees and external donor funding)

To complement the 2006 study by estimating service delivery and management costs (prior study covered commodity and program costs)To estimate the costs of scorecard activities (12 interventions) within the context of the CPA and project coverage targets and costs through 2015

To prepare a standard cost model of the package of services that estimate resources required to implement the CPA in line with HSP2 targetsTo assist the MOH with the preparation of hospital budgets that can be used in the 3-year Rolling Plans and AOPs

Sample 4 provincial (Kampong Cham PH, Pursat PH, Takeo PH, Siem Reap PH) and 8 district/referral hospitals (Choueng Prey DH, Kroch Chhmar DH, Memut RH, Kralanh DH, Sotr Nikum RH, Kirivong RH, Ang Roka DH, Bakan DH)Selected by type of contracting arrangement

4 national hospitals: Preah Bat Norodom Sihanouk Hospital, National TB Hospital, National Pediatric Hospital, and National Maternal and Child Center

2 district/referral hospitals: Ang Roka Hospital, Kirivong HospitalSelected due to their contracted OD status with costs likely reflecting the quantities and prices of resources needed to provide services in the future

4 referral hospitals (CPA1-3): Ang Roka Hospital, Kirivong Hospital, Kampong Cham Provincial Hospital, and Prey ChhorSelected due to their support under SRC and BTC contracting programs, more complete data, and more adequate resourcing for operations

Data Collection

Data was collected in late 2001 by MOH staffCost data was based on nominal budgetsData on staffing and costs were obtained from MOH salary data, NGO records of bonuses and incentive payments, and user fee reportsStaff worktime allocation was measured by direct observation and interviewsCost of drugs and supplies was

Data was collected in August 2003 by MOH staffMOH staff received one week of training prior to data collectionData reflects actual expenditures from the previous year (vs. nominal budgets as used in Part I of the study)Data on staff costs were obtained from the hospital accounting offices, which incorporate MOH salary data, NGO

Hospital costs were based on 2006 figures and were obtained in collaboration with the Swiss Red CrossThe figures collected do not include capital or depreciation costs and only reflect costs to the government or donor agencies (e.g., volunteer time and patient OOP costs are not included)Figures do not include costs included under the national program costing study

2007 data was collected through several hospital visits and use of national level data sourcesCosts reflect expenditures made on resources provided and are thus limited by the funds provided to, and generated by, each hospitalData collected included:# of services (from HIS with validation by hospitals of some data, such as # of beds)

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determined from monthly CMS reports (consumption of items supplied was recorded separately)Other direct and indirect costs came from facility recordsBuildings were measured and their construction type (concrete/wood) notedVehicle and equipment lists were compiled by observationOutputs by type or service were derived from HIS records for Jan/Apr/Sept 2001 (validated through field audits of reported HIS data)

records of bonuses and incentive payments, and user fee reportsCost of drugs and supplies and other operational costs were derived from internal hospital accounting sourcesOutputs by type or service were available from the hospitals

(e.g., per diems) Income and expenditures (from routine reports prepared by hospitals)Staffing details (from staffing reports and conversations with hospital managers)Resources used for key interventions (from information from a small sample of patient records)Additional resources needed (verbal estimates from hospital directors)

Outputs Inpatient days, categorized into surgical cases, medicine / emergency cases, maternity / ob-gyn cases, paediatrics, TB/leprosy inpatients, and ‘other’ inpatientsOutpatient activity was collected according to curative vs. specialty clinic visits

Inpatient days categorized into inpatient cases and surgery / ICU casesOutpatient visits

Inpatient days categorized into deliveries, surgical interventions, and inpatient admissionsOutpatient visits

Hospital-level outputs rather than service-level outputs due to data limitationsAll inpatient departments were grouped together

Costing Method and Allocation

Direct costs: Medical staff, drugs and supplies, other (outpatient staff, inpatient food, and miscellaneous items such as ice)Indirect costs: Electricity, office and cleaning supplies, and non-medical staffStaffing costs: Allocated to outputs by step-downStaff time allocation was observed and recorded during field data collection and combined with data on staff compensationAncillary staff costs were allocated to inpatient service categories on basis of

Step-down method:Direct costs were calculated for hospital and paraclinical services by adding labor costs to the cost of drugs and suppliesIndirect costs were calculated as the sum of admin staff labor, operating costs, maintenance, and “other operating costs”Indirect costs were allocated among the four cost centers on the basis of the relative share of direct labor costs for each serviceParaclinical service costs were calculated

General approach:Developed unit costs and multiplied them by coverage targets to determine total annual service delivery costsUnit cost per inpatient admission, staff and operating cost was apportioned over the different services using weights obtained from a SRC study of the contracted districtsUnit cost was calculated for weighted visits (outpatient equivalent)Cost of drugs was excluded from unit cost

Step 1: Estimation of Hospital Costs and Additional Resource NeedsStaff, drug, and clinical supply cost allocation was done at the hospital level rather than inpatient department level for the following reasons:Information on staff allocations by department was not specific enough, particularly where employees worked in multiple departmentsSufficient information on the cost of drugs and medical supplies issued to each

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inpatient-daysDrug and supply costs: Costs of CMS drugs and supplies could not be directly attributed to specific service outputs (with the exception of TB drugs)Allocated to the inpatient services according to an estimated weighting to assign a value of drugs per inpatient-day: Surgical cases (0.4), Medical/ Emergency cases (0.3), Delivery/Ob-Gyn, Paediatric, Other (0.1)Average drug cost at health centres per visit was assumed to be the drug cost per outpatient visit at district hospitals, and increased for provincial hospitalsOther direct and indirect costs and depreciation: Allocated to outputs on the basis of inpatient-daysAssumption that these costs are proportional to activity level for each service, and outpatient activity uses a negligible amount of overheadCapital depreciation: Costs were presented with and without depreciation as they are carried in the MOH asset books at their original cost and are often not subject to management controlStandard construction cost of $180/square meter and standard life of 30 years was used for concrete buildings; $100/square meter and 20 years life for wood buildingsVehicle replacement costs were estimated and a lifetime of 5 years used to calculate depreciation regardless of age

by adding direct paraclinical staff costs, costs of paraclinical supplies (reagents, films, chemicals, blood bank) and the paraclinical proportion of indirect costsParaclinical costs were allocated to general inpatients, surgical inpatients, and outpatients according to the proportion of tests performed for eachTotal costs for general inpatients, surgical inpatients, and outpatients were calculated as the sum of their direct costs (labor and supplies), allocated indirect costs, and allocated paraclinical costsDepreciation was allocated proportionally to each cost center’s total of direct and indirect costs

Capital depreciation:Calculated same as in Part I with a few exceptionsCost of some buildings was unknown, so an estimate of $200/square meter was used, proportional to the estimated $180/square meter for concrete buildings in rural areas used in Part IFor vehicles, annual depreciation was calculated by the recorded purchase cost of cars, pickups, and ambulances which were less than 10 years old, divided by the expected 10-year lifespanFor motorbikes, a 5-year expected life was used, and only the purchase cost of those less than 5 years old was usedFor major equipment, the total cost

calculations since they were included under the 2006 program costing study

Step 1: Determined hospital total costsStep 2: Allocated total costs to each type of service, providing unit cost per serviceStep 3: Multiplied cost / inpatient bed-day by estimated LOS required for each scorecard intervention to obtain average weighted cost per admissionScorecard interventions included malaria, pneumonia, and diarrheaLOS was estimated based on expert opinion of ideal ALOSArrived at average admission cost for malaria, pneumonia treatment, and diarrhea treatmentStep 4: Multiplied unit service costs by the numbers of services in the first year to provide a total cost for each intervention for the yearStep 5: Divided total costs by total target coverage figures for the year to provide a unit cost per person coveredStep 6: Multiplied unit costs per person covered by the target coverage figures for each subsequent year to provide total costs for the scorecard interventions (projections were inflated by 2% per year)

department was not suppliedTotal pay was estimated (salary, overtime, shares of user fees, and incentives) for each staff member as complete records of total pay are not keptCapital costs, depreciation, and expenditures for upgrading facilities were excluded because these costs are typically not included in recurrent budgets and they are time consuming to prepare

Step 2: Development of Normative Cost ModelsUsing # of beds, BOR, and # of outpatient services, separate models were developed based on CPA level to estimate normative costThe # of services was considered the cost driver of the # of staff and cost of drugs and suppliesAverage cost per inpatient day for drugs and supplies was estimated using data for each hospital level from the RACHA database and taking into account need for additional drugs identified by the hospital directorsFor # of each type of staff, norms were derived from the CPA guidelines rangesAverage compensation was produced for staff of similar type (e.g., MDs and MAs; admin staff and general support staff)Operating costs were derived using actual hospital costs and additional costs needed as identified by the hospital directors

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Equipment costs were estimated, and a life of 10 years applied for medical equipment and 15 years for non-medical equipment

obtained from asset records was divided by 10 years

Treated operating costs as fixed for CPA 1 and 2 hospitals because the range of beds is smallTreated a portion of operating costs as fixed for CPA 3 hospitals and set the remainder to vary in proportion with the numbers of services

Unit Costs Cost / inpatient-dayAverage cost / service areaAverage staff compensationMean per capita costLabor cost / direct costsLabor cost / drug costCapital / recurrent costsDirect costs / indirect costsDirect costs / total costsMarginal cost / inpatient-dayMarginal cost / inpatient service

Cost / inpatient bed-day (calculated on a basis of assumed 100% utilization)Cost / admission (calculated on the basis of actual utilization)Cost / outpatient visitTotal hospital cost per capitaLabor cost / bedLabor cost / staff memberLabor cost / direct costsDirect patient costs / total costs% of total costs contributed by donors% of labor costs contributed by user fees

Cost / inpatient-day (excluding drugs)Cost / weighted contact (OPD equivalent)Average admission cost for malaria treatment, pneumonia treatment, and diarrhea treatment

# of inpatient days (# of official beds x BOR)assumed BOR of 85% (optimal rate)# of outpatient services (actual count)Normative cost / service (cost per inpatient day equivalent (IDE) – a ratio of outpatient costs to inpatient costs – plus inpatient days)Staff cost / IDEDrug and medical supply cost / IDEOperating costs / IDECost / discharge and cost / outpatient serviceCost per capita (total and for each input type: staff, drugs and clinical supplies, operating costs)Funding source as a % of total funding

Limitations and Recommend-ations

Data may be unrepresentative due to hospital contracting relationships and data collection over only 2-3 monthsCosts of drugs / medical supplies were allocated according to assumptions, so may warrant another study to confirm assumptions usedIt is not always valid to compare unit cost results without information on service

Data may be unrepresentative due to using costing data based on accounting records which may not accurately represent 2002 expenditures as funding actually received by hospitals may not coincide with the expenditure periodStep-downs are based on allocations according to available data, and may not be as accurate as costings in which actual

None provided Staffing norms were developed from CPA ranges and drug and supply costs were based on actual amounts provided to hospitals, which do not account for differences in patient mix and may not reflect accurately the needs of the hospitalsActual cost figures represent expenditures made on resources provided to hospitals

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delivery strategies and treatment guidelinesFurther studies are needed to determine the relationship of facility costs to other factors (e.g., service delivery strategies, treatment guidelines, staff motivation, local population factors)Additional variables to study could include contracting arrangements, population density, accessibility, and the socio-economic environment

resource use is measuredExtrapolating or projecting the costs of CPA to higher utilization levels should be the objective of a further study

and not necessarily costs that should have been incurredFigures used for staff remuneration were based on averages of actual payments at hospitals and may need to be adjustedDetermination of standard clinical practice should be carried out to develop more accurate staffing norms and standard drug / clinical supply needsA more detailed analysis of the operating costs is advisable as it is possible that some aspects, such as maintenance, are underfundedAdjusted costs reflecting additional needs estimated by hospital directors may not reflect the real resource needs of the hospitals

* Several Cambodia costing studies include approaches for costing health centers, national programs, specific interventions, etc. These methods are not addressed here.

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Annexure 3: Hospital Costing Data Collection Tool

Data Category No. Data Item Data Description Preferred

Format Time Period How Will This Be Used? Data Source

General Informatio

n

1 Staff Contact Information

Full name, telephone, and email of accountant, cashier, RH director, OD and PHD Director, and others involved in the hospital costing pilot

Electronic Current To obtain clarity on data and request additional information if necessary

Hospital Administration

2 Departments / Ward List

List of all hospital departments / wards Electronic Calendar Year 2010

To identify all cost centers and assign costs to departments / wards


3 Service List Information on bundled services (e.g., lab test bundled with delivery) and ancillary services should also be collected

Electronic Calendar Year 2010

To cost specific services and assign drugs and supplies to services


4 Payment Contracts

User fee schedule, HEF MOU, CBHI scheme details, and other insurance arrangement details

Electronic and paper

Calendar Year 2010

To understand funding sources and fees associated with service delivery


Utilization 5 Population Population statistics and hospital catchment area


To estimate costs per capita

Hospital Administration, HIS

6 IPD Utilization

Number of inpatient discharges by service (or ward / department)


Jan/Apr/July/Oct 2010

To calculate number of inpatient bed-days by ward


7 LOS Days of care by service (and / or ward) Electronic Jan/Apr/July/Oct 2010

To calculate average length of stay by ward

HIS

8 Bed Count Number of beds (recognized and unrecognized) by ward

Electronic Jan/Apr/July/Oct 2010

To calculate bed occupancy rate


9 Outpatient Visits

Number of visits by service Electronic and paper


To calculate outpatient equivalent of inpatient bed-days


10 Request Form for Specialized Ward

Information on ward, date, bed number, diagnosis, drug, quantity


Calendar Year 2010

To assign drug and supply costs to wards (and / or services) and detemine consumption

Pharmacy

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11 Order / Delivery Forms by Ward

Information on ward, date, description, unit, request quantity, provided quantity, observation


Calendar Year 2011


Pharmacy

12 Daily Consumption Records by Ward

Information on code, commodity name, form, strength, day, and quantity



Pharmacy

13 Drugs and Consumables Consumption Report

Information on code, commodity name, form, strength, int stock, incoming, total, outgoing, balance, req quantityObservation



Pharmacy

14 OPD Prescriptions

Information on date, prescription, strength, form, payment


Calendar Year 2014


Pharmacy

15 RACHA Database

Database of invoices and hospital consumption records


Calendar Year 2015


Pharmacy, RACHA

16 Lab Case Book

Information on date, name, age, sex, ward, test, results



To assign ancillary costs to wards

Lab

17 Lab Stock Cards

Information on date, # of invoice, supplier / destination, incoming, outgoing, adjustment, balance, expiry date, observation



To determine consumption

Lab

18 Other Ancillary Department Forms

Ambulance logs, blood bank records, radiology tests, pathology records, etc.



To assign ancillary costs to wards / departments

Relevant Ancillary Departments

Personnel 19 Staff List Information on staff type, department / ward assignments, full time / part time status, government salary levels

Electronic Current and Jan/Apr/Jul/Oct 2010

To calculate labor costs by department / ward

Hospital Administration, PHD Office, OD Office

20 Non-traditional Staff List

List of floating staff / external consultants, roles, and department / ward assignments


To identify (and cost) additional staff that may not be captured


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on the official staff list21 Unpaid Staff

ListList of assisting staff (e.g., student, volunteers) and their payment arrangements


To include labor inputs into patient care which may not be accounted for in staff lists


22 Staff Schedule and Attendance Records

Staff schedule, worktime allocation by department / ward, and attendance records


Current and Jan/Apr/Jul/Oct 2011

To calculate Full Time Equivalent (FTE) status


23 Incentive / Bonus Contracts

Contracts and / or details on incentive / bonus compensation plans



To estimate the full labor cost above salaries


24 Incentive Payout Invoices

Information on name, position, incentive category, level, amount





25 PHD Staff Payments

Information on salary, duty allowance, midwife incentive payments




PHD Office

Drugs and Medical Supplies

26 Procurement Requests Issued to PHD / OD

Information on quantities of drugs and supplies requested

Paper Jan/Apr/July/Oct 2010

To determine quantities of drugs and supplies requested

Pharmacy

27 Pharmacy Invoices from CMS / PHD / OD

Information on date, code, description, strength, form, supply, unit price, total price, expiry date


To determine quantities and prices of drugs and supplies received

Pharmacy

28 Stock In / Stock Out Reports

Information on incoming, outgoing, adjustment, balance, expiry date


To verify invoice records of items received

Pharmacy

Financials

29 Monthly Financial Reports

Documenting income and expenses for user fee, HEF, CBHI, other income sources


To determine how non-government funds are spent


30 Monthly Financial

Documenting income and expenses for national budget, SOA, PBB sources


To determine how government funds are

Hospital Administration,

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Reports spent OD Office, PHD Office

31 AOP / SOA / PBB Budget

Budgets with line-item detail and any supporting documents on budget-to-actual comparisons


To determine amount budgeted for hospital use

Hospital Administration, OD Office, PHD Office

32 AOP / SOA / PBB Disbursement Records

Monthly and quarterly records of MOH and provincial treasury disbursements by line item


Calendar Year 2010

To determine amount disbursed for hospital use

Hospital Administration, OD Office, PHD Office

33 Audited Financial Statements

MOH, MEF, PwC reports Electronic Calendar Year 2010

To understand audit methodology and findings


34 Bank Statements and Advance Registers

Records relating to each hospital account Electronic Calendar Year 2010

To reconcile bank accounts with financial reports


35 Cashier Patient Payment File

Patient payments for services and prescriptions by fee type (self pay, HEF, CBHI, partial pay, exempt, other)


Calendar Year 2010

To validate amounts recorded in financial statements


36 Funding / Donations from Other Sources

Information by ward / department if available (e.g., student fees, parking, donated supplies, etc.)


Calendar Year 2010

To identify all additional sources of funding and supplies received


37 Cash (Case?) Book

Daily income and expense tracking with information on item, date, income, expense, balance


Calendar Year 2010



38 Payment Vouchers

Information on amount, item, and payment to Paper Calendar Year 2010



39 Request Forms

Information on request objective, amount, reason

Paper Calendar Year 2010



40 Itemized Request Lists

Information on item, quantity, unit price, total amount




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41 Invoices Information on vendor, item, quantity, unit price, total




Annex 4: Sample Department Assignment to Cost CentersDepartment Category Department

Administrative(Indirect Cost Centers)

AdministrationLaundrySecurity

AccountingKitchenTransport

Ancillary(Intermediate Cost Centers)

Blood transfusionDiagnosticOperating theaterPharmacyX-ray

DentalLaboratoryPathologyPhysiotherapy

Clinical(Direct Cost Centers)

CardiologyInternal medicineIntensive careMental healthNeurologyOphthalmologyPediatricsSurgeryTuberculosis

GynecologyInfectious diseasesMaternityNeonatalOncologyOtolaryngologySubstance abuseTraumaUrology

Source: Langenbrunner JC, Cashin C, and O’Dougherty S. Designing and Implementing Health Care Provider Payment Systems: How-To Manuals. International Bank for Reconstruction and Development / The World Bank. 2009

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Section 5: Works carried out on Health Financing – PMR

5.1. IntroductionAs mentioned earlier a part of my work was to prepare the health financing report for the PMR that is submitted to development partners to have detailed idea on health financing in Cambodia. As a part of this responsibility I was asked to:

1. Prepare Health Financing Chapter for PMR. I was initially requested to make an analysis of HEF for the report which I submitted earlier (Ref: Annex 3.9). However the development partners wanted a detailed health financing report. I was assigned this task during May 2011 and it took nearly a month to gather the information, preparation of the draft version of the report, incorporating the comments from the HSSP secretariat staff and finally revising the report to final version. I completed this work successfully (Ref: Annex 5.1 hard copy inserted in the text and the soft copy in CD)

2. Preparation of bi-annual progress report on health financing: During second week of September I was asked to prepare the biannual progress report. Since I was on leave during September 21st onwards I could not complete the report in time. I have completed the report (Ref: Annex 5.2 Hard copy inserted in text and soft copy in CD) and sent to secretariat staff for comments (Ref: Annex 5.2 Hard copy inserted in text and soft copy in CD)

Annexures

Annex 5.1 – Health Care Financing in Cambodia – Progress during 20105.1. Budgetary Allocation Process: Before the end of each financial year the Ministry of Health (MoH) is required to submit its tentative budget to the Ministry of Economy and Finance (MEF). MoH prepares its tentative budget based on their annual operational plan for the forthcoming year and submits it to MEF. The MEF, in turn, presents the budget in the National Assembly for its approval and finalisation. On the basis of the final decisions and recommendations made in the parliament, the MEF adjusts the budget upward/downward depending on the availability of resources under its disposal. The approved budget is communicated to Department of Budget and Finance (DBF) of MoH.

On the basis of the communication from MEF on final allocated figures, the Department of Budget and Finance (DBF) of MoH sends the request for the release of funds. Since National Treasury is responsible for any government receipts and payments, the MEF issues necessary instructions to Treasury for the release of the requested funds by the ministry. Annex Table 5.1 presents the detailed financial data pertaining to financial year 2010 (January – December 2010)

5.2. Analysis of the Government expenditure for 2010A detailed analysis of the table reveals that out of the total budget allocated to MoH during 2010, 73 per cent was spent at the central level and 27 per cent at the provincial level. The share of salary in the total budget was around 17 per cent. A further breakup of the figures indicates that out of total allocation to the central level (i.e., program and non-program components), 5 per cent was allocated for salary. A significant chunk, (50 per cent) of the

75 | P a g e

total allocation to the provincial level was spent on salary and other allowances. Pharmaceuticals and procurements, (chapter 60) constituted around 19 per cent of the total budget allocated to MoH. Out of the total budget of MoH, the spending on pharmaceuticals and procurements at the central level was around 13 per cent and 6 per cent at provincial level.

It must be highlighted that a major chunk (around 48% of the total budged allocated to MoH) of expenditure during 2010 was incurred on Chapter 65 (i.e., financial support to public administrative institutions, assistance to poor patients, food supply, scholarships and financial support to social and cultural organisations such as support to orphan centres, support to Red Cross etc.).

5.3. HSSP2 disbursement and expenditure by sources of fundThe budget for the financial year 2010 from HSSP was around $ 33.3 million. This included the budget allocation for the year 2010 i.e., $26.1 million plus the previous carry forward budget. The actual expenditure was around $21.9 million (66 per cent).

As is indicated in the table, the majority of expenditure was on operational costs which include salary, equipment and other operational expenses (25 per cent), training (22 per cent), Services Delivery Grants (19 per cent) and Health Equity Fund (19 per cent). (Annex Table 5.2)5.3.1. Health Equity Fund – A detailed analysisThere were a total of 53 health equity funds (HEFs) operating in the sector, including 9 subsidized directly by Government (excluding the 6 national hospitals), with the rest being supported by a variety of health development partners including USAID and HSSP2 partners. It is estimated that coverage of HEFs amounted to 73% of the total population of the country or 9.7 million people. Pre-identified beneficiaries included 980,431 persons, while post-identified persons amounted to 1.3 million. The total number of cases directly supported by HEFs has shown an increase from 2007 through this reporting period as of 16 September 2010, with the greatest increase occurring from 2007 to 2008 when the number of HEF schemes that were operational increased due to JFPR/ADB funded HEFs coming on stream.

Overall, during this reporting period, $2.99 million was incurred as total benefit costs (user fees, transport costs, food costs, and non-food costs), and $427,751 as total administration and program development costs. Utilization included a total of 202,121 OPD visits, 45,524 IPD cases, and 9,986 deliveries. Of the total benefit costs of $1,449,748, payments for transport costs are $189,262.

The graphs below show the patterns of utilization and costs incurred for groups of HEFs by source of funding for the year 2010.8

5.3.1a. Utilisation by Pre and Post - ID The HEF beneficiaries are usually poor people identified through a Pre-ID process which is usually done by Ministry of Planning (MoP). However, the MoP is not able to identify all the poor people and sometimes it so happens that a patient arriving at the hospital does not have the ability to pay for the cost of care. There is a process of identifying these poor by the HEF operator. The people identified through this process are called Post-ID patients. The utilisation by pre and post ID HEF beneficiaries is depicted in Figure 1. As the figure shows, there is an overall increase in utilisation by pre and post -ID beneficiaries, with a slight fluctuation during 2009 and 2010.

Figure 1: Comparison of cases Pre and Post ID during 2007-2010

8 Source: Bureau of Health Economics and Financing, Department of Planning and Health Information.

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A detailed look at the Figure 1 gives a clear idea on the number of HEF beneficiaries during the year 2007 – 2010. During 2007 the number of Health Equity Fund beneficiaries (Pre-ID and Post-ID) were around 1000 each. Over a period of 4 years number of beneficiaries has increased substantially. By the end of year 2010 it is around 7000. However it could be observed that there is a sharp decline in the number during early 2009. This is because of delay in the release of fund during January and February 2009.

Figure 2: Cost per Pre-ID Poor Individual 2007-2010.

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Figure 2 shows the average monthly cost for Pre-ID poor. As could be seen from the figure, the average cost per Pre-ID poor has declined over the years. This is mostly due to increased utilisation by the poor. Moreover the indirect cost component has not increased compared to the direct cost component.

5.3.1b. Utilisation by IPD – cost implications As may be expected, the cost of utilisation of HEF by IPD is much higher than OPD. In addition the cost also varies across different level (i.e., CPA1, CPA2 and CPA3) of hospitals. The cost per IPD in Provincial Referral Hospitals (PRH), which are usually CPA3 level, is much higher compared to CPA1 and CPA2 hospitals. However for the present analysis we have taken the average IPD cost of all three levels of hospitals and made an attempt to analyse the cost and utilisation.

Figure 3: Percent of HEF IPD Beneficiaries to total IPD in HEF supported RHs

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Jan-0

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)

Figure 3 shows the percentage of HEF-IPD beneficiaries out of total IPD in the HEF supported referral hospitals. Though the overall trend is upward, the trend is not consistent across the reporting period. The percentage of beneficiaries varies from a minimum of 20 to a maximum of 55. It is observed that the percentage of HEF IPD beneficiaries has increased over the years, especially from the 2nd quarter of 2009. During the first quarter the number of beneficiaries is very low because of the delay in the release of fund. However, the overall increase is mostly due to the efforts of the implementers on IEC/BCC activities that has increased the awareness of the community about the health equity fund. However, much needs to be done in this regard to enhance the utilisation by poor. (Figure 3)

As mentioned earlier, overall utilisation of HEF by IPD as well as OPD has increased substantially over the period from 2007 – 2010. As a result of increased utilisation, the direct benefit cost such as user fees, food, transport, non-food and grants has also increased. There is a steep increase in average direct benefit cost from 2009 onwards. The indirect benefit cost such as program development etc., and the administrative cost shows a declining trend over the years (Figure 4).

Figure 4: Average cost per IPD – Direct cost, indirect cost and Administrative costJan

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5.3.1c. Dynamics between utilisation and cost reimbursement

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Figure 5 depicts the dynamics between utilisation and cost reimbursement in HEF supported hospitals. It is observed that the Average Length of Stay (ALOS) for the HEF beneficiaries is much higher than the patients not supported by HEF. Among several factors, two could be considered important. It is possible that the case complexity (and the consequent high ALOS) is one of the reasons. On the other hand the possibility of keeping the patients longer for getting more user fees from the HEF beneficiary patients could not be ruled out. However, the exact reason for higher ALS for HEF beneficiaries needs to be studied carefully by taking the case mix and case complexity issues into consideration.

As was just observed from Figure 4, the direct benefit cost has been increasing consistently over the years. The higher ALOS may be one of the contributing factors for the rise in direct benefit cost. However, the gap between ALOS of HEF beneficiaries and non-beneficiaries appears to be consistent over the years.

Figure 5: Comparison of Trends in ALS for HEF Beneficiaries versus Non-Beneficiaries

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S (

in d

ays)

As already known, increase in direct benefit cost indicates higher utilisation, thus better program implementation. As the number of beneficiaries increases, the direct cost components increase. As could be seen from figure 6, the direct benefit cost has been increasing constantly. One can easily observe that the direct benefit cost component has suddenly increased during the period 2009 and 2010. This is due to expansion of the program during 2008-09 and greater awareness among the people on HEF over the years.

Figure 6: Trends in Direct Benefit Costs

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5.3.1d. Administrative cost and economies of scale As it is already known that administrative cost, (i.e., cost related to the management of program by HEF operators and implementers) usually remains fixed till it is utilised to an optimal level. After that point if the program has to expand, then the management cost need to be increased. As could be observed from the graph at the initial level this cost component consumed 25-30 per cent of the total fund allocation. During the initial phases of the program the cost remained high because of low utilisation of the health care facilities. From 2009 onwards there is a sharp decline in this component. (Figure 7)

Figure 7: Administrative costs/total Costs

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st

5.4. Global FundApart from RGC, HSSP, and HEF, Global Fund is also a major source of those funds for the programs related to the diseases like HIV/AIDS, Tuberculosis and Malaria. The fund is channelled through MoH’s Principle Recipient’s Office. The total expenditure for 2010 was around $21.9 million, out of which 67 per cent was disbursed for HIV/AIDS, 24 per cent for s Malaria, 4 per cent for Tuberculosis and 5 per cent was for Health System Strengthening.

5.5. Community Based Health Insurance (CBHI)Apart from the above sources of funding for the health sector, another source of funding is Community Based Health Insurance (CBHI). Under this scheme, the health care is purchased by a third party (may be an NGO, called insurer), and the same is provided for free to the persons who are the member of the scheme. To be the member of the scheme the households/individuals have to pay a fixed premium to the insurer. The community members those who pay the premium can only derive the benefits out of the scheme. The amount of premium is fixed by the NGO. Becoming the member of the scheme is purely voluntary.

SKY was the first NGO to start CBHI in Cambodia. The pilot was done in Takhmao OD of Kandal province during 1997. As the scheme was found be successful, SKY expanded the scheme to Ang Roka and Kirivong ODs of Takeo province during 2001. Since then CBHI has been gaining popularity among the community and the coverage has increased from 81 health centres, 12 primary referral hospitals and 6 secondary referral hospitals in 2008 to 164 health centres, 13 primary referral hospitals and 9 secondary referral hospitals during 2010. As per the information the numbers of CBHI schemes have expanded from 12 during 2008 to 18 in 2010. Out of total 18 schemes, 9 of them are managed by SKY. A list of schemes as of 2010 is given in Annex Table 5.3. 5.5.1. Number of beneficiaries during 2008-2010

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Figure 8 shows the number of CBHI beneficiaries during the year 2008 and 2010. As the data for the year 2009 (the reported data was for the period January-September 2009) was not completely reported by GRET/SKY, we are unable to include the year 2009 for the analysis. As could be observed from the figure, the number of CBHI beneficiaries has increased substantially over the period of two years. For some of the ODs the CBHI has started during the year 2010. Therefore the value of the number of beneficiaries for the year 2008 is “0”. It is also noted that for the OD Sampov Meas, the dropout rate is extremely high. The numbers of current beneficiaries / members have come down by nearly 50 per cent compared to 2008. This is mostly due to the change of the insurer from RACHA to PFD/URC. Previously RACHA used to run a micro finance scheme in the OD. The interest earned through the scheme was used to be utilised for the health care of the community. After URC has entered into the scene, the premium is being charged to the members. At present very few people are able to afford for it.

However, there is a significant growth in CBHI membership Thmar Pouk, Kampot and Ang Roka. (Annex Table 5.4)Figure 8: Total number of CBHI Beneficiaries during 2008-2010

Phno

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Rok

a

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vong

Kom

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5.5.2. Utilisation of OPD and IPD facilities 2008-2010As is observed from Figure 9, the utilisation of OPD facilities by the CBHI members was abysmally low during the year 2008. The contact rate was below .20 for many of the ODs except Thmar Pouk, Kirivong and, Sampov Meas. However, the utilisation of OPD has increased substantially and the contact rate per beneficiary is more than one during the year 2010. This may be due to better awareness among the communities to utilise the facilities.

Figure 10 depicts the utilisation of inpatient services by CBHI members. As far as utilisation of IPD facilities is concerned, it still remains extremely low as in most of the ODs the IPD admissions are less than 5 per cent of the total CBHI members. The scenario for Phnom Penh, Thmar Pouk, Ang Roka and Odder Meanchey is slightly better. The overall utilisation of IPD has improved during 2010 with most of the beneficiaries utilising IPD facilities. Details on the utilisation of facilities during 2010 are given in Annex Table 5.5.

Figure 9: Utilisation of the CBHI Scheme 2008 and 2010 - OPD81 | P a g e

Ph

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Figure 10: Utilisation of the CBHI Scheme 2008 and 2010 - IPD

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5.5.3. Income and expenditure of CBHI Schemes 2008-2010Figures 11-12 gives a detailed overview of the income and expenditure of CBHI schemes for the year 2008. It is could be observed that the expenditure is always higher than the income obtained through premium collection and other sources. Interestingly, when we compare the income and the direct benefit cost that is reimbursed by the insurer, we could find that the direct benefit cost to the patient is close to the income that the insurers earn from different sources. Sometimes the income is bit higher in some of the ODs.

Figure 11: CBHI Scheme – Income and Expenditure 2008

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Figure 12: CBHI Scheme – Income and Expenditure on direct benefit cost 2008

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Figure 13-14 gives a detailed overview of the income and expenditure of CBHI schemes for the year 2010. It is observed that the gap between total income and expenditure is bit wider compared to year 2008. When we compare the income and the direct benefit cost (expenditure by the insurer for the direct medical benefit of the patient), it is observed that the direct benefit cost to the patient is close to the income that the insurers earn from different sources and for some of ODs like Thmar Pouk, Samrong and Sampov Meas, the income is at a much higher level compared to the expenditure. It may be possible that at the initial stages of the program/scheme, the overhead expenses are likely to be higher, but over a period of time, when more number of people join the scheme, the overhead and. administrative costs is expected to get reduced to a large extent. Finally, it may be pointed out that the CBHI scheme has not been expanded country wide. The benefits of the scheme could only be realised when it is expanded to the entire nation. Annex Table 5.6

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Figure 13: CBHI Scheme – Income and Expenditure 2010

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Figure 14: CBHI Scheme – Income and Expenditure on direct benefit cost 2010

Phnom Penh

Ang Roka

Kirivong

Kompong Thom

Ta Khmoa

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Daun Keo

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AnnexuresAnnex Table 5.1: Budget and the disbursement for the financial year ended in December 2010 (figures are given in millions of USD).

ChapterBudg

et plan ($)

Adjusted

budget ($)

Requested

budget ($)

Commitment

($)

Mandated

Request ($)

Mandated ($)

Disbursement

($)

% % Amount % % Amount % % % %

1 2 3 4 5=4/3 6 7=6/3 8 9=8/3 10=8/4 11 12=11/3 13=11/6 14 15=14/3 16=14/11

Grand Total (Central + Provincial)

150.01 161.28 154.91 96% 154.13 96% 153.83 95% 99% 153.60 95% 100% 152.84 95% 99.5%

1‐ Central level (Non Pgm +Pgm) 104.93 115.17 112.39 98% 111.63 97% 111.36 97% 99% 111.36 97% 100% 111.36 97% 100%

1.1‐ Non-Program BudgetTotal 94.43 104.68 102.35 98% 101.86 97% 101.62 97% 99% 101.62 97% 100% 101.62 97% 100%

60 Purchases 17.18 20.68 20.35 98% 20.32 98% 20.31 98% 100% 20.31 98% 118% 20.31 98% 100%

61 Outside Services 1.47 1.43 1.31 91% 1.31 91% 1.28 89% 98% 1.28 89% 98% 1.28 89% 100%

62 Other outside services 1.45 1.49 0.80 54% 0.82 55% 0.79 53% 98% 0.79 53% 96% 0.79 53% 100%

64 Staff remuneration 6.55 6.80 6.05 89% 6.05 89% 6.04 89% 100% 6.04 89% 100% 6.04 89% 100%

65Financial

support and social Aids

67.74 74.24 73.80 99% 73.33 99% 73.16 99% 99% 73.16 99% 100% 73.16 99% 100%

63 Taxation 0.04 0.04 0.04 94% 0.04 94% 0.04 94% 100% 0.04 94% 100% 0.04 94% 100%1.2‐ Budget by Program

Total 10.50 10.50 10.05 96% 9.77 93% 9.74 93% 97% 9.74 93% 100% 9.74 93% 100%60 Purchases 0.74 0.74 0.74 100% 0.74 100% 0.74 100% 100% 0.74 100% 100% 0.74 100% 100%

61 Outside Services 0.44 0.44 0.42 95% 0.42 95% 0.41 94% 100% 0.41 94% 100% 0.41 94% 100%

62 Other outside services 2.93 2.93 2.56 88% 2.50 85% 2.48 85% 97% 2.48 85% 99% 2.48 85% 100%

65Financial

support and social Aids

6.39 6.39 6.33 99% 6.12 96% 6.11 96% 97% 6.11 96% 100% 6.11 96% 100%

85 | P a g e

ChapterBudg

et plan ($)

Adjusted

budget ($)

Requested

budget ($)

Commitment

($)

Mandated

Request ($)

Mandated ($)

Disbursement

($)

63 Taxation 0.00 0.00 0.00 0% 0.00 0% 0.00 0% 0% 0.00 0% 0% 0.00 0% 0%2‐ Provincial level 45.09 46.11 42.52 92% 42.50 92% 42.48 92% 100% 42.25 92% 99% 41.48 90% 98%60 8.51 8.51 8.44 99% 8.43 99% 8.42 99% 100% 8.36 98% 99% 8.28 97% 99%61 6.14 6.14 6.07 99% 6.06 99% 6.04 99% 100% 6.03 98% 100% 5.99 98% 99%62 3.99 3.99 3.69 93% 3.69 93% 3.69 93% 100% 3.69 92% 100% 3.65 91% 99%64 23.32 24.35 21.35 88% 21.35 88% 21.35 88% 100% 21.25 87% 100% 20.73 85% 98%65 3.07 3.07 2.96 96% 2.95 96% 2.95 96% 100% 2.90 95% 98% 2.83 92% 97%63 Taxation 0.06 0.06 0.01 26% 0.01 26% 0.01 26% 100% 0.01 26% 100% 0.01 26% 99%

Note: 60: Purchases: - It includes supplies, supplies for administration, clothes and decorations, furniture and equipment, utilities, medical equipment and supplies and other supplies 61: Outside Services: - It includes Contract with enterprises, vehicle rental, fare and charges, training cost (contracting experts), repair and maintenance, insurance, research and experimentation62: Other outside services:- It includes outside staff, publicity, newspaper and documentation, overseas mission expenses, communication cost, banking and other charges 63: Taxation: - It only includes taxation64: Staff: - It includes remuneration and allowances for permanent and non-government and temporary staff, other allowances65: Financial support and social Aids: - This includes financial support to public, contribution to international organisations, donors and allowances, financial support to social and cultural organisations Annex Table 5.2: HSSP Disbursement by sources of fund - 2010

Cat. Pooled Fund Counterpart UNICEF UNFPA BTC AFD Total Pool and CATEGORY Budget Actual Budget Actual Budget Actua Budget Actual Budget Actua Budget Actual Budget ActualService Delivery 1 4.513 3.082 0.501 0.342 0.803 0.710 5.818 4.135HEF Grants 2 2.125 2.806 0.394 0.701 0.100 0.084 0.200 0.241 0.300 2.819 4.132MBPI & related 3Others- Goods 4A 5.504 0.882 0.010 0.011 0.002 0.000 5.515 0.893- Civil Works 4B 0.092 0.279 0.092 0.279- Consultant 4C 3.907 1.487 0.213 0.201 0.095 0.101 0.486 0.423 4.702 2.212- Operating Costs 4D 7.092 4.782 0.195 0.044 0.603 0.538 0.048 0.056 0.109 0.041 8.047 5.460- Training 4E 5.532 3.975 0.195 0.290 0.354 0.312 0.142 0.093 0.076 0.109 6.299 4.779Total 28.765 17.014 0.895 1.044 0.490 0.419 1.371 1.292 0.295 0.261 1.477 1.861 33.293 21.890

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Annex Table 5.3: CBHI Schemes in Cambodia

No. Scheme Start date Province OD HC Payment Model

Primary Referral Hospital Payment Model

Secondary Referral Hospital

1 SKY Dec, 2006 Phnom Penh Phnom Penh 3 Fee Chamkar Morn, Pochentong, Tuo Svay Prey,Samdch Ov, Khmer Soviet Hosp.

Fee, Lumpsum

Kosamak

2 SKY 2001 Takeo Ang Roka 10 Capitation AR RH Capitation Takeo Hospital3 SKY by BFH January, 2006 Takeo Kirivong 20 Capitation Kirivong Referral Hospital Capitation Takeo RH4 AFH January, 2010 Kompong Thom Kompong Thom 9 Capitation Kompong Thom Provincial

HospitalCase based + User fees

5 SKY 1998 Kandal Ta Khmoa 1 Capitation Chey Chum Neah Hospital Capitation6 SKY 2008 Kampot Kampot 12 Capitation Kampot Hospital Capitation7 SKY 2008 Kandal Koh Thom 6 Capitation Koh Thom Referral Hospital Capitation Chey Chum Neah

Hosp8 SKY 2008 Takeo Daun Keo 15 Case Takeo Hospital Case9 SKY 2010 Takeo Bati 13 Capitation Takeo Hospital Case10 SKY 2010 Takeo Prey Kabass 13 Capitation Takeo Hospital Case11 CAAFW Feb, 2005 Banteay Mean

CheyThmar Pouk 10 Case Thmor Pouk Referral Hospital Case Monkol Borey

Hospital12 CAAFW January, 2009 Oddar Meanchey Samrong 11 Case Anlong Veng Referral hospital Case Samrong13 PFD/URC Apr-10 Pursat Sompov Meas 8 Capitation Pursat Referral Hospital Capitation14 CHHRA August, 2005 Oddar Meanchey Samrong 3 Case Oddar Meanchey15 CHO October,2009 Battambang Battambang 7 Case 0 Case Battambang SRH16 CHO January, 2010 Battambang Sanke 3 Case 0 Case Battambang SRH17 RACHA/HN July, 2010 Prey Veng Pearaing 3 Capitation Pearaing Referral Hospital Case based Khmer So Viet18 STSA9 August,2010 Siem Reap Ang Kor Chum 17 Case Angkor Chum and Puok RH Case Siem Reap RH,

Khmer Soviet Total 11 17 164 13 9

9 STSA: Sahakum Theanearabrong Sokhapheap (The scheme being managed by the commune council)87 | P a g e

Abbreviations

SKY : Sokhapeap Krousa YeungBfH : Buddhism for Health CAAFW : Cambodian Organisation for Assistance to families and WidowsPFD : Poor Family Development CHHRA : Cambodia Health and Human Rights Alliance CHO : Cambodian Health Organisation RACHHA : Reproductive and Child health Alliance HN : Health Net International URC : University Research Company STSA : Sahakum Theanearabrong Sokhapheap (The scheme being managed by the commune council)Annex Table 5.4: CBHI Coverage expansion 2010

No Scheme OD Total Beneficiaries (Individuals)

%OD Population Covered

New beneficiaries in 2010

Drop out in 2010 % beneficiaries covered by social assistance scheme

(HEF)1 SKY Phnom Penh 5,906 NA 3,470 3,362 0%2 SKY Ang Roka 10,706 8.67% 5,986 3,878 0%3 SKY by BfH Kirivong 10,624 5% 981 308 0%4 AFH Kompong Thom 4,833 71.08% 4,337 456 28.92%5 SKY Ta Khmoa 857 11.00% 395 191 0%6 SKY Kamport 25,608 19.08% 16,211 8,214 75%7 SKY Koh Thom 3,178 3.74% 3,252 2,816 0%8 SKY Daun Keo 8,600 3.89% 8,512 7,734 0%9 SKY Bati 2,487 1.25% 2,805 313 0%10 SKY Prey Kabass 2,263 1.42% 2,541 280 0%11 CAAFW Thmar Pouk 40,299 32.00 11,847 1,503 0.00%12 CAAFW Samrong 25,683 14.26 16,128 4,401 0.00%13 PFD/URC Sompov Meas 5,036 3% 672 4,531 0%14 CHHRA Odor Mean Chey 5,571 0.03 1,735 1,24415 CHO Battambang 2,235 0.60 580 161 016 CHO Sanke 566 0.29 115 15 017 RACHA/HN Pearaing 2,283 0.01 2,283 018 STSA AngKor Chum 13,755 10.94% 13,755 0 81.62%

Total 1,70,490 95,605 39,407

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Annex Table 5.5. Utilisation of the Schemes

NoScheme OD OPD visits IPD admissions Deliveries at

facilityTotal Male Female Child Total Male Female Child

1 SKY Phnom Penh 6,749 2,465 3,555 729 503 161 232 56 542 SKY Ang Roka 31,791 9,662 15,709 6,420 630 231 269 112 183 SKY by BfH Kirivong 6,596 N/A N/A N/A 172 N/A N/A N/A 514 AFH Kompong Thom 11,257 3,650 6,534 1,073 505 226 221 58 375 SKY Ta Khmoa 287 99 163 25 29 14 9 1 56 SKY Kampot 38,469 11,045 22,357 5,067 1,862 617 889 297 597 SKY Koh Thom 12,421 4,128 6,346 1,947 447 160 211 70 78 SKY DounKeo 28,409 8,646 14,014 5,749 573 167 301 105 09 SKY Bati 3,435 714 1,763 958 140 27 74 36 310 SKY Prey Kabass 5,100 1,367 2,408 1,325 52 22 16 11 311 CAAFW Thmar Pouk 1,10,878 25,878 78,827 6,173 2,198 695 722 781 1,01112 CAAFW Samrong 38,345 9,620 22,142 6,583 2,102 623 1,073 406 88713 PFD/URC Sompov Meas 12,191 2,536 6,009 3,646 98 15 49 34 5814 CHHRA Oddar Meanchey 11,430 1,593 6,668 3,169 218 56 92 70 17615 CHO Battambang 1,332 283 726 329 48 14 27 7 16

16 CHO Sanke 216 57 100 53 21 5 12 4 8

17 RACHA/HN Pearaing 3,085 N/A N/A N/A 94 20 47 27 1118 STSA AngKor Chum 2,076 696 1,380 431 155 48 107 39 24

Total 3,24,067 82,439 1,88,701 43,677 9,847 3,101 4,351 2,114 2,428

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Annex Table 5.6.: Financial report for 2010

No

Scheme OD Income in USD Expenditures in USD

PremiumOther

IncomeTotal

IncomeTotal direct

medical benefits paid

Total non-medical

benefits paid

Administrative

costs

Outreach and social

marketing costs

Other costs

Total

1 SKY Phnom Penh 82,572 952 83,524 68,795 1,287 40,228 7,212 0 1,17,5212 SKY Ang Roka-Zone2 32,803 801 33,604 27,886 6,125 48,733 11,470 0 94,2143 SKY by BfH Kirivong 22,649 99 16,748 24,313 1,083 35,342 19,043 0 79,7814 AFH Kompong Thom 15,868 10,213 26,080 17,208 2,838 81,730 6,645 2,662 1,37,1635 SKY Ta Khmoa-Zone 1 1,196 19 1,215 3,326 59 2,777 674 0 6,8366 SKY Koh Thom-Zone 7 13,067 898 13,965 12,159 1,323 32,456 8,191 0 54,1287 SKY Kampot-Zone 6 72,487 1,068 73,555 78,942 6,914 53,809 12,505 0 1,52,1708 SKY Daun keo-Zone 8 34,718 2,030 36,748 33,293 3,786 52,622 19,027 0 1,08,7279 SKY Bati-Zone 9 1,542 4 1,546 1,402 92 34,692 8,254 0 44,440

10 SKY Prey Kabas-Zone10 1,529 5 1,534 883 198 27,097 10,435 0 38,61311 CAAFW Thmar Pouk 68,690 79,330 1,48,020 83,003 12,059 7,455 10,876 34,627 1,48,02012 CAAFW Samrong 48,111 1,85,693 2,33,804 44,491 17,847 12,320 31,883 79,153 1,85,69313 PFD/URC Sompov Meas 8,201 0 8,201 17,318 0 11,949 0 0 29,26714 CHHRA Oddar Meanchey 7,362 6,605 13,967 7,648 6,411 1,979 0 0 16,03815 CHO Battambang 6,958 450 7,408 2,456 1,077 1,027 329 98 4,98716 CHO Sanke 1,570 306 1,876 643 816 526 329 98 2,41217 RACHA/HN Pearaing 9,357 10 9,367 2,492 1,106 unclear unclear unclear18 STSA Ang Kor Chum 11,340 5,600 16,940 6,830 1,672 7,388 0 9 15,899

Total 4,40,020 2,94,084 7,28,104 4,33,085 64,695 4,52,128 1,46,874 1,16,646 12,35,910

90 | P a g e

Annex 5.2 – Text given below and soft copy in CD

Health Care Financing in Cambodia – Bi-annual Progress 2011 (for PMR)5.1. Budgetary Allocation during January – June 2011 5.1.1a. Allocation and disbursement at the central levelTotal allocated budget to Ministry of Health (MoH) for the financial year 2011 is around $172.23 million. During the period from January-June 2011, the disbursed amount is $51.82 million, which is just 30.1 per cent of the total allocation to the health sector. Out of total disbursement of $51.82 million, over 98 per cent has already been spent on different activities. Out of the total budget the allocation 70.5 per cent ($121.4 million) is for the central level and 29.5 per cent is for provincial level. (Annex Table 5.1)The central level budget is allocated among non-programme and programme activities. Out of the total central budget allocation of $121.4 million, 91.7 per cent (i.e., $111.3 million) is being spent on non-programme activities and rest 8.3 per cent on programme activities. The distribution of expenditure on non-programme activity budget ($111.3 million) is: 77 per cent towards the contribution to international organisations, donors, allowances and financial support social and cultural organisations, followed by contractual services, vehicle maintenance and repair (15 per cent) and staff remuneration (6.2 per cent) (Annex Table 5.1)5.1.1b. Allocation and disbursement at the provincial levelThe total provincial allocation is nearly 29.5 per cent ($50.8 million) of the total budget of $172.2 million. The distribution of the allocation for provincial budget is: 52.1 per cent towards salaries and remuneration, followed by 17.1 per cent for supplies, 12.7 per cent for outside services such as vehicle rent and maintenance etc. (Charter 61). The financial support and social aid is just around 10 per cent of the provincial allocation for the year 2011. (Annex Table 5.1)5.1.1c. Disbursement and expenditureAs far as the disbursement is concerned only 30.1 per cent of the total budget was disbursed and 98.2 per cent of it is spent during the reporting period. Out of the total budget ($33.06 million) disbursed at the central level; the total amount has already been spent on different activities. It may be noted that out of total disbursement to the provinces ($18.8 million), 95.3 per cent has already been spent. As far as the distribution of provincial disbursement is concerned, the highest level of disbursement ($10.7 million) was on staff remuneration, out of which 94.7 per cent has already been spent. (See Annexure Table 4.1.1 for details).

5.2. Health Equity Fund – A detailed analysis

5.2.1. Utilisation by Pre and Post - ID The HEF beneficiaries are usually poor people identified through a Pre-ID process which is usually done by Ministry of Planning (MoP). However, the MoP is not able to identify all the poor people and sometimes it so happens that a patient arriving at the hospital does not have the ability to pay for the cost of care. There is a process of identifying these poor by the HEF operator. The people identified through this process are called Post-ID patients. The utilisation by pre and post ID HEF beneficiaries is depicted in Figure 1. As the figure shows, there is an overall increase in utilisation by pre and post -ID beneficiaries.

91 | P a g e

Figure 1: Comparison of cases Pre and Post ID during Jan-June 2011

Jan

-10

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Nu

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A detailed look at the Figure 1 gives a clear idea on the number of HEF beneficiaries during

Figure 2: Cost per Pre-ID Poor Individual January-June 2011.

Jan-1

0

Feb-1

0

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Ap

r-10

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6Cost/Pre-ID Poor Individual

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$

the period January-June 2011. During Jan-June 2010 the number of Health Equity Fund beneficiaries (Pre-ID and Post-ID) were around 2000 and 2300 respectively. During January-June 2011 the number of pre ID cases shows a slight increasing trend compared to the same period during 2010. No significant improvement is observed in the number post ID cases.

Figure 2 shows the average monthly cost for Pre-ID poor. As could be seen from the figure, the average cost per Pre-ID poor has declined over the reporting period. This may be due to increased utilisation by the poor. Moreover the indirect cost component has not increased compared to the direct cost component over the year 2010.

5.2.2. Utilisation by IPD – cost implications As may be expected, the cost of utilisation of HEF by IPD is much higher than OPD. In addition the cost also varies across different level (i.e., CPA1, CPA2 and CPA3) of hospitals. The cost per IPD in Provincial Referral Hospitals (PRH), which are usually CPA3 level, is much higher compared to CPA1 and CPA2 hospitals. However for the present analysis we have taken the average IPD cost of all three levels of hospitals and made an attempt to analyse the cost and utilisation.

92 | P a g e

Figure 3: Percent of HEF IPD Beneficiaries to total IPD in HEF supported RHs Jan-June 2011

Jan-1

0

Feb-1

0

Mar-1

0

Ap

r-10

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0%

10%

20%

30%

40%

50%

60%

70%Percent HEF

HEF

IPD

Be

ne

fici

arie

s (%

)

Figure 3 shows the percentage of HEF-IPD beneficiaries out of total IPD in the HEF supported referral hospitals. During the reporting period no significant improvement in the utilisation by HEF-IPD is observed compared to the situation in 2010 during the same reference period. It may be noted that during May and June of 2010 the percentage of HEF-IPD were much higher compared to the reporting period. However, it should be pointed out that the HEF-IPD beneficiaries have almost close to the target set under HEF expansion plan for 2012-2015. This is certainly a positive symbol, implying that the IPD facilities are mostly utilised by the poor people. (Figure 3)

The overall utilisation of HEF by IPD as well as OPD has increased substantially over the years. As a result of increased utilisation, the direct benefit cost such as user fees, food, transport, non-food and grants has also increased. There is a steep increase in average direct benefit cost during January – June 2011 compared to the same reference period during 2010. The indirect benefit cost such as program development etc., and the administrative cost has also increased during the 2011 compared to the same reference period during 2010. Surprisingly the administrative cost has remained at the same level (with minimal fluctuations) during the reporting period (Figure 4).

Figure 4: Average cost per IPD – Direct cost, indirect cost and Administrative cost Jan-June 2011

Jan-1

0

Feb-1

0

Mar-1

0

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93 | P a g e

5.2.3. Dynamics between utilisation and cost reimbursement

Figure 5 depicts the dynamics between utilisation and cost reimbursement in HEF supported hospitals. It is observed that the Average Length of Stay (ALOS) for the HEF beneficiaries is much higher than the patients not supported by HEF. Among several factors, two could be considered important.

1) It is possible that the poor cases are admitted in the hospital when their condition is more severe i.e., case complexity (and the consequent high ALOS)

2) Deliberate action of the hospital authorities to keep the poor cases longer: On the other hand the possibility of keeping the patients longer for getting more user fees from the HEF beneficiary patients could not be ruled out.

However, the exact reason for higher ALS for HEF beneficiaries needs to be studied carefully by taking the case mix and case complexity issues into consideration.

Figure 5: Comparison of Trends in ALS for HEF Beneficiaries versus Non-Beneficiaries Jan-June 2011

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8ALOS HEF Beneficiaries

ALOS Non Beneficiaries

ALO

S (i

n d

ays)

As was just observed from Figure 4, the direct benefit cost has been increasing consistently over the months. The higher ALOS may be one of the contributing factors for the rise in direct benefit cost. However, the gap between ALOS of HEF beneficiaries and non-beneficiaries appears to be consistent over the years. (Figure 5)

As already known, increase in direct benefit cost indicates higher utilisation, thus better program implementation. As the number of beneficiaries increases, the direct cost components increase. As could be seen from figure 6, the direct benefit cost has increased substantially during the reporting period (January- June 2011) compared to the same period during 2010.

94 | P a g e

Figure 6: Trends in Direct Benefit Costs Jan-June 2011

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Dir

ect

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st in

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$

5.2.4 Administrative cost and economies of scale As it is already known that administrative cost, (i.e., cost related to the management of program by HEF operators and implementers) usually remains fixed till it is utilised to an optimal level. After that point if the program has to expand, then the management cost need to be increased. As could be observed from the graph, the administrative cost as percentage of total cost has declined substantially during January – June 2011. This is mostly due to high direct benefit cost to for covering the cost of treatment. As a matter of fact this is a major issue and needs to be examined carefully. (Figure 7)

Figure 7: Administrative costs/total Costs Jan-June 2011Jan-10

Feb-10

Mar-10

Apr-10

May-10

Jun-10

Jan-11

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Apr-11

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Adm

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ost

as %

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otal

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t

5.3. Global FundApart from RGC, HSSP, and HEF, Global Fund is also a major source that funds for the programs related to the diseases like HIV/AIDS, Tuberculosis and Malaria. The fund is channelled through MoH’s Principle Recipient’s Office. The total funds spent during January-June 2011 were around $4.3 million on TB, HIV/AIDs and health system strengthening and on different programs during January to June 2011 is given below:

95 | P a g e

5.4. Community Based Health Insurance (CBHI)Apart from the above sources of funding for the health sector, another source of funding is Community Based Health Insurance (CBHI). Under this scheme, the health care is purchased by a third party (may be an NGO, called insurer), and the same is provided for free to the persons who are the member of the scheme. To be the member of the scheme the households/individuals have to pay a fixed premium to the insurer. The community members those who pay the premium can only derive the benefits out of the scheme. The amount of premium is fixed by the NGO. Becoming the member of the scheme is purely voluntary. During the reporting period there are 18 CBHI schemes out of which 9 are managed by SKY. A list of schemes as of 2010 is given in Annex Table 5.2. 5.4.1. Number of beneficiaries during January-June 2011 Figure 8 shows the number of CBHI beneficiaries during the January-June 2011. As could be observed from the figure, the number of CBHI beneficiaries is highest in Angkor Chum OD in Siem Reap province (67,628), followed by Thmar Pouk OD in Banteay Mean Chey province (44,264), Samrong OD in Oddor Meanchey province (28,609), Kampot OD in Kampot Province (25,352), Kirivong OD in Takeo province (10,789) and Ang Roka OD in Takeo province (10,404). For other ODs the members are less than 10,000 with minimum number of members in Ta Khmoa OD in Kandal province (993). (Annex Table 5.3)Figure 8: Total number of CBHI Beneficiaries during Jan-June 2011

Phno

m P

enh

Ang

Roka

Kiriv

ong

Daun

Keo Ba

ti

Prey

Kab

ass

Ta K

hmoa

Kam

port

Koh

Thom

Thm

ar P

ouk

Sam

rong

Odo

r Mea

n Ch

ey

Som

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s

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aing

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e

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or C

hum

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404

1078

9

8150

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993

2535

2

4192

4426

4

2860

9

1153 43

39

5759

6516

4286

1332

6762

8

2011

Num

ber o

f HEF

Ben

eficia

ries

5.4.2. Utilisation of OPD and IPD facilities January-June 2011 The utilisation of OPD and IPD facilities by CBHI members is depicted in Figures 9 and 10. As could be observed, the OPD as well as IPD facilities were mostly utilised by the members of Thamar Pouk, Samrong and Kampot ODs. The figures are self-explanatory and do not need further analysis. Annex Table 5.4.

Figure 9: Utilisation of the CBHI Scheme January-June 2011 - OPD96 | P a g e

Ph

no

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An

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oka

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oa

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05,000

10,00015,00020,00025,00030,00035,00040,00045,00050,000

2,6

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12

4,7

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17

0

13

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7

2,4

99 7,7

37

3,5

48

5,1

07

44

,40

7

29

,87

6

66

4 3,0

85

4,5

64

1,6

60

36

2 5,6

42

24

,08

4

2011 - OPD UtilisationN

um

be

r o

f O

PD

be

ne

fici

arie

s

Figure 10: Utilisation of the CBHI Scheme January-June 2011 - IPD

Phno

m P

enh

Ang

Rok

a

Kiri

vong

Ta K

hmoa

Kam

pot

Koh

Thom

Dou

nKeo

Bati

Prey

Kab

ass

Thm

ar P

ouk

Sam

rong

Odd

ar M

eanc

hey

Som

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Mea

s

Kom

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Tho

m

Batt

amba

ng

Sank

e

Pear

aing

Ang

Kor

Chum

0

200

400

600

800

1000

1200

1400

1600

234

182

392

19

396

77 106

127

63

1408

985

22 69

197

40 11

138

663

2011 Utilisation of IPD

Num

ber

of IP

D b

enefi

ciari

es

5.4.3: Income and expenditure of CBHI Schemes January-June 2011Figure 11 gives a detailed overview of the income and expenditure of CBHI schemes for the reporting period. It is observed that for most of the ODs the expenditure is higher than the income obtained through premium collection and other sources. Interestingly, when we compare the income and the direct benefit cost that is reimbursed by the insurer, we could find that the direct benefit cost to the patient is close to the income that the insurers earn from different sources. Sometimes the income is bit higher in some of the ODs. Figure 12 (Annex Table 5.5)

97 | P a g e

Figure 11: CBHI Scheme – Income and Expenditure January- June 2011

Phnom Penh

Ang Roka-Zone2

Kirivong

Ta Khmoa-Zone 1

Koh Thom-Zone 7

Kampot-Zone 6

Daun keo-Zone 8

Bati-Zone 9

Prey Kabas-Zone 10

Thmar Pouk

Samrong

Oddar M

eanchey

Sompov M

eas

Kompong Thom

Battam

bang

Sanke

Pearaing

Ang Kor Chum

0

20000

40000

60000

80000

100000

120000

140000

2011 Income

2011 Expendi-ture

Inco

me

and

Expe

ndit

ure

in U

S $

Figure 12: CBHI Scheme – Income and Expenditure on direct benefit cost January- June 2011

Ph

no

m P

enh

An

g Ro

ka-Zon

e2

Kirivo

ng

Ta Kh

mo

a-Zon

e 1

Ko

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om

-Zon

e 7

Kam

po

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Dau

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Bati

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Prey K

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0

Thm

ar Po

uk

Samro

ng

Od

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Som

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Ko

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ang

Sanke

Pearain

g

An

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r Ch

um

0

20000

40000

60000

80000

100000

120000

140000

2011 Income

2011 Expenditure on direct benefits

Inco

me

an

d E

xpe

nd

itu

re in

US

$

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Annexure Annex Table 5.1: Budget and the disbursement for the financial year 2011 (January-June 2011) (figures are given in millions of USD).

Chapter Description Budget Plan

Adjusted

Requested budget

Commitment

Mandated request Mandated DisbursementAmount

% Amount % Amount

% % Amount

% % Amount

% %1 2 3 4 5=4/3 6 7=6/3 8 9=8/3 10=8/4 11 12=11/

313=11/6

14 15=14/3 16=14/11Grand Total 172.20 172.23 131.28 76.2

%123.94 72.0% 56.15 32.6

%42.8% 52.75 30.6% 42.6% 51.82 30.1% 98.2%

1. Central Level

121.39 121.39 107.73 88.7%

102.57 84.5% 35.97 29.6%

33.4% 33.06 27.2% 32.2% 33.06 27.2% 100.0%1.1‐ Non- Program Budget

Total 111.26 111.26 99.97 89.9%

96.18 86.4% 31.42 28.2%

31.4% 30.18 27.1% 31.4% 30.18 27.1% 100.0%60 Purchases 16.69 16.69 14.42 86.4

%13.51 80.9% 2.79 16.7

%19.3% 2.59 15.5% 19.2% 2.59 15.5% 100.0%

61 Outside Services

1.26 1.26 0.84 66.9%

0.03 2.1% 0.05 3.7% 5.6% 0.02 1.4% 65.7% 0.02 1.4% 100.0%62 Other

outside 1.02 1.02 0.28 27.9

%0.05 5.0% 0.13 12.3

%43.9% 0.05 5.0% 100.0% 0.05 5.0% 100.0%

64 Staff remuneratio

6.91 6.91 2.39 34.6%

2.24 32.4% 2.37 34.4%

99.5% 2.24 32.4% 100.0% 2.24 32.4% 100.0%65 Financial

support and 85.33 85.33 82.03 96.1

%80.35 94.2% 26.09 30.6

%31.8% 25.28 29.6% 31.5% 25.28 29.6% 100.0%

63 Taxation 0.05 0.05 0.00 0.0% 0.00 0.0% 0.00 0.0% 0.0% 0.00 0.0% 0.0% 0.00 0.0% 0.0%1.1‐ Budget by Program

Total 10.13 10.13 7.76 76.6%

6.39 63.1% 4.55 44.9%

58.6% 2.88 28.4% 45.1% 2.88 28.4% 100.0%60 Purchases 0.64 0.64 0.38 60.1

%0.22 34.3% 0.20 30.7

%51.1% 0.01 1.8% 5.1% 0.01 1.8% 100.0%

61 Outside Services

0.40 0.40 0.37 93.5%

0.37 93.3% 0.00 0.2% 0.2% 0.00 0.0% 0.0% 0.00 0.0% 0.0%62 Other

outside 2.80 2.80 1.75 62.3

%1.16 41.5% 1.17 41.7

%66.9% 1.12 39.9% 96.3% 1.12 39.9% 100.0%

65 Financial support and

6.29 6.29 5.26 83.6%

4.64 73.7% 3.18 50.6%

60.6% 1.75 27.8% 37.7% 1.75 27.8% 100.0%63 Taxation 0.00 0.00 0.00 0.0% 0.00 0.0% 0.00 0.0% 0.0% 0.00 0.0% 0.0% 0.00 0.0% 0.0%

2‐ Provincial Total 50.81 50.84 23.55 46.3

%21.37 42.0% 20.18 39.7

%85.7% 19.69 38.7% 92.1% 18.76 36.9% 95.3%

60 Purchases 8.68 8.68 4.94 57.0%

4.29 49.5% 3.92 45.2%

79.3% 3.84 44.2% 89.4% 3.65 42.1% 95.1%61 Outside

Services6.46 6.46 3.55 54.9

%2.15 33.3% 1.45 22.4

%40.8% 1.32 20.5% 61.6% 1.32 20.4% 99.5%

62 Other outside

4.07 4.07 1.74 42.6%

1.69 41.6% 1.69 41.6%

97.5% 1.60 39.2% 94.3% 1.50 36.9% 94.2%64 Staff

remuneratio26.43 26.46 11.37 43.0

%11.37 43.0% 11.37 43.0

%100.0

%11.24 42.5% 98.9% 10.65 40.3% 94.7%

65 Financial support and

5.08 5.08 1.95 38.3%

1.87 36.7% 1.75 34.5%

90.0% 1.68 33.1% 90.2% 1.64 32.2% 97.1%63 Taxation 0.09 0.09 0.00 0.0% 0.00 0.0% 0.00 0.0% 0.0% 0.00 0.0% 0.0% 0.00 0.0% 0.0%

Note: 60: Purchases: - It includes supplies, supplies for administration, clothes and decorations, furniture and equipment, utilities, medical equipment and supplies and other supplies

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61: Outside Services: - It includes Contract with enterprises, vehicle rental, fare and charges, training cost (contracting experts), repair and maintenance, insurance, research and experimentation62: Other outside services: - It includes outside staff, publicity, newspaper and documentation, overseas mission expenses, communication cost, banking and other charges 63: Taxation: - It only includes taxation64: Staff: - It includes remuneration and allowances for permanent and non-government and temporary staff, other allowances65: Financial support and social Aids: - This includes financial support to public, contribution to international organisations, donors and allowances, financial support to social and cultural organisations

Annex Table 5.2: CBHI Schemes in Cambodia January-June 2011

No. Scheme Start date Province OD H.C Payment Model Primary Referral Hospital Payment

ModelSecondary Referral

Hospital

1 SKY Dec, 2006 Phnom Penh Phnom Penh 3 FeeChamkar Morn, Pochentong, Tuo Svay Prey,Samdch Ov, Khmer Soviet Hosp.

Fee, Lumpsum Kosamak

2 SKY 2001 Takeo Ang Roka 10 Capitation AR RH Capitation Takeo Hospital3 SKY by BFH January, 2006 Takeo Kirivong 20 Capitation Kirivong Referral Hospital Capitation Takeo RH4 SKY 2008 Takeo Daun Keo 15 Case Takeo Hospital Case5 SKY 2010 Takeo Bati 13 Capitation Takeo Hospital Case6 SKY 2010 Takeo Prey Kabass 13 Capitation Takeo Hospital Case7 SKY 1998 Kandal Ta Khmoa 1 Capitation Chey Chum Neah Hospital Capitation8 SKY 2008 Kampot Kampot 12 Capitation Kampot Hospital Capitation

9 SKY 2008 Kandal Koh Thom 6 Capitation Koh Thom Referral Hospital Capitation Chey Chum Neah Hosp

10 CAAFW Feb, 2005 Banteay Mean Chey Thmar Pouk 10 Case Thmor Pouk Referral Hospital Case Monkol Borey

Hospital

11 CAAFW January, 2009 Oddar Meanchey Samrong 11 Case Anlong Veng Referral hospital Case Samrong

12 CHHRA August, 2005 Oddar Meanchey Samrong 3 Case Provincial hospital OMC Case Oddar Meanchey

13 PFD/URC Apr-10 Pursat Sompov Meas 8 Capitation Pursat Referral Hospital Capitation

14 AFH January, 2010 Kompong Thom

Kompong Thom 18 Formula

linkage Kompong Thom Provincial Hospital Case based + User fees

15 RACHA/HN July, 2010 Prey Veng Pearaing 9 Capitation Pearaing Referral Hospital Case based Khmer So Viet16 CHO October,2009 Battambang Battambang 7 Case 0 Case Battambang SRH17 CHO January, 2010 Battambang Sanke 3 Case 0 Case Battambang SRH18 STSA August,2010 Siem Reap Ang Kor Chum 17 Case Angkor Chum and Puok RH Case Siem Reap RH,

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No. Scheme Start date Province OD H.C Payment Model Primary Referral Hospital Payment

ModelSecondary Referral

HospitalKhmer Soviet

Total 11 17 179 13 9

Abbreviations

SKY : Sokhapeap Krousa YeungBfH : Buddhism for Health CAAFW : Cambodian Organisation for Assistance to families and WidowsPFD : Poor Family Development CHHRA : Cambodia Health and Human Rights Alliance CHO : Cambodian Health Organisation RACHHA : Reproductive and Child health Alliance HN : Health Net International URC : University Research Company STSA : Sahakum Theanearabrong Sokhapheap (The scheme being managed by the commune council)Annex Table 5.3: CBHI Coverage expansion January-June 2011

No Scheme Province OD Total Beneficiaries (Individuals)

% OD Population

Covered

New beneficiaries

in 2011

Drop out in 2011

% beneficiaries covered by social assistance scheme

(HEF)1 SKY Phnom Penh Phnom Penh 6,536 NA 1,128 530 0%2 SKY Takeo Ang Roka 10,404 8.42% 988 1,363 0%3 SKY by BfH Takeo Kirivong 10,789 5% 1,142 1,026 0%4 SKY Takeo Daun Keo 8,150 3.68% 1,470 1,839 0%5 SKY Takeo Bati 3,669 1.84% 838 609 0%6 SKY SKY Prey Kabass 3,699 2.31% 845 518 0%7 SKY Kandal Ta Khmoa 993 0.41% 81 74 0%8 SKY Kampot Kamport 25,352 18.89% 730 1,915 75%9 SKY Kandal Koh Thom 4,192 4.94% 1,839 689 0%

10 CAAFW Banteay Mean Chey

Thmar Pouk 44,264 35 13,007 29.82%

11 CAAFW Oddar Meanchey Samrong 28,609 16.73 12,077 0.00%12 CHHRA Odor Mean Chey Odor Mean Chey 1,153 40 N/A 0

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13 PFD/URC Pursat Sompov Meas 4,339 5% 31 133 0%14 AFH Kompong Thom Kompong Thom 5,759 71.78% 1,310 203 28.92%15 RACHA/HN Prey Veng Pearaing 6,516 3.23% 6,516 N/A16 CHO Battambang Battambang 4,286 1,17% 2,051 159 017 CHO Battambang Sanke 1,332 0,7% 766 21 018 STSA Siem Reap AngKor Chum 67,628 29.97% 24,265 NA 24.63%

Total 2,37,670

Annex Table 5.4: Utilisation of the Schemes January-June 2011

NoScheme OD OPD visits IPD admissions Deliveries

at facility ALOSDNumber

of referrals

Total Male Female Child Total Male Female Child1 SKY Phnom Penh 2,624 840 1,440 344 234 87 120 27 26 6.692 SKY Ang Roka 8,612 1,941 3,978 2,693 182 61 80 41 44 3.313 SKY by BfH Kirivong 4,749 4,749 392 348 44 54 SKY Ta Khmoa 170 32 110 28 19 2 11 1 5 7.615 SKY Kampot 13,957 3,436 7,632 2,889 396 91 213 92 122 4.606 SKY Koh Thom 2,499 723 1,179 597 77 17 44 16 10 7.507 SKY DounKeo 7,737 1,898 3,557 2,282 106 29 56 21 32 3.158 SKY Bati 3,548 761 1,817 970 127 27 62 38 45 3.769 SKY Prey Kabass 5,107 1,217 2,473 1,417 63 14 32 17 2 2.64

10 CAAFW Thmar Pouk 44,407 10,632 27,675 6,100 1,408 575 833 302 329 3.5 31511 CAAFW Samrong 29,876 4,403 12174 3,571 985 153 286 88 227 3 9012 CHHRA Oddar Meanchey 664 84 450 130 22 6 11 5 21 4 0

13 PFD/URC Sompov Meas 3,085 638 1,440 1,007 69 9 56 4 61 1.2

202

14 AFH Kompong Thom 4,564 1,608 2,917 39 197 65 85 47 11 4 715 CHO Battambang 1,660 435 817 408 40 10 24 6 22 7,2 1316 CHO Sanke 362 98 201 63 11 3 7 1 7 3,2 417 RACHA/HN Pearaing 5,642 N/A N/A N/A 138 39 54 45 56 3.85 274

18 STSA AngKor Chum 24,084

9,629 14,455 6,985

663 246

417 94 292 5.03 546.00

Total

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Annex Table 5.5: Financial report for January-June 2011

No

Scheme OD Income Expenditures

Total Premiums

Other Income

Total Income

Total direct

medical benefits

paid

Total non-

medical benefits

paid

Administrative

costs

Outreach and

social marketing

costs

Other costs Total

1 SKY Phnom Penh 26,035 147 26,182 18,411 144 9,355 1,913 420 30,2432 SKY Ang Roka-Zone2 9,648 8 9,656 8,097 1,207 11,298 2,154 6 22,761

3 SKY by BfH Kirivong 25,872.10

$ 19 25,891 7,484 529 9,452.65 6,153.40 2,675.00 26,293

4 SKY Ta Khmoa-Zone 1 672 0 672 1,135 49 759 0 0 1,9435 SKY Koh Thom-Zone 7 4,099 2 4,102 3,016 61 8,587 3,230 2,313 17,2076 SKY Kampot-Zone 6 26,778 47 26,824 26,209 1,833 12,480 3,349 8,549 52,4217 SKY Daun keo-Zone 8 9,174 27 9,201 9,426 548 12,444 3,136 0 25,5558 SKY Bati-Zone 9 5,501 2 5,502 5,168 196 10,216 2,410 0 17,9909 SKY Prey Kabas-Zone 10 5,171 9 5,180 4,843 299 10,031 3,118 0 18,292

10 CAAFW Thmar Pouk 46,202 49,460 95,662 43,150 6,743 4,896 8,726 16,768 80,28311 CAAFW Samrong 47,683 79,865 1,27,548 29,965 6,053 9,895 33,952 0 79,86512 CHHRA Oddar Meanchey 860 1,966 2,826 1,326 25 1,120 0 0 2,47113 PFD/URC Sompov Meas 1,869.20 0.00 1,869.20 2,400.71 0.00 5,339.99 0.00 0.00 7,740.70

14 AFH Kompong Thom 7,325.82

615.69

7,941.51

4,904.39

538.22 16,496.30 12,831.

39 3,651.7

2 38,422.

0315 CHO Battambang 5,842.00 0.00 5842.00 6026.00 330.00 425.00 625.00 0.00 7,406.0016 CHO Sanke 2,205.00 0.00 2205.00 634.00 179.00 136.00 507.00 0.00 1,456.00

17 RACHA/HN Pearaing 7,562 13 7,575 6,160 1,819 unclear unclear unclear

18 STSA Ang Kor Chum 18,683.95

50,265.12

68,949.07

43,141.68

14,132.23 15,250.12

Total

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consultancy report on health financing - cambodia

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