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REPUBLIC OF KENYA
Report on the Review of EMR Systems
Towards Standardization
Kenya Ministries of Health, 2011
MINISTRY OF MEDICAL SERVICES
AFYA HOUSE
P.O. BOX 30016 – 00100
NAIROBI
MINISTRY OF PUBLIC HEALTH & SANITATION
AFYA HOUSE
P.O. BOX 30016 – 00100
NAIROBI
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TABLE OF CONTENTS
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ACKNOWLEDGEMENTS This Review Towards Standardization process was the first of its kind to be done in Kenya and was based on the Ministry of Health’s Standards and Guidelines Document for EMR Systems in Kenya. Coordination of the activity was provided by the EMR Technical Working Group through the Ministry of Public Health and Sanitation and the Ministry of Medical Services. The following people are acknowledged in their participation in steering forward this activity: HIS Dr. C. Nzioka Onesmus Kamau NASCOP Dr. D. Kimanga Julius Mutiso Cecilia Wandera Naomi Shiyonga Catherine Njogu PARTNER INSTITUTIONS T. Oluoch CDC J. Kwach CDC Dr. P. Odawo I-TECH S. Wanyee I-TECH J. Wesonga I-TECH Dr. B. Lober I-TECH
A. Barsigo Futures Group A. Karisa Futures Group K. Wamathaga Futures Group Dr. R. Mpazanje WHO G. Owiso EDARP J Kariuki AMPATH S. Kanga UNITID S. Ochungo Aga Khan Dr. A. Hassan KEMRI, Kilifi J. Kuria FHI 360 Dr. M. Aluda FHI 360 Dr. W. Siganga FHI 360 M. Osumba Abt Associates F. Ndichu NPHL R. Omollo Consultant O. Magana Consultant
Special acknowledgement to the management and staff of the health facilities at which the various systems were reviewed. Additionally, we acknowledge other participants and representatives from the following organizations, whose input, albeit intermittent, was key to the development of these guidelines. Participating organizations: Ministry of Public Health and Sanitation Ministry of Medical Services Centre for Disease Control (CDC) United States Agency for International Development (USAID) International Training and Education Centre for Health (I-TECH) Family Health International 360 (FHI) Futures Group International Centre for AIDS Care and Treatment Programs (ICAP) Eastern Deanery AIDS Relief Program (EDARP) The World Health Organizations (WHO)
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LIST OF ACRONYMS
ART Anti-Retroviral Therapy CPAD Comprehensive Patient Application Database EDARP Eastern Deanery AIDS Relief Program EMR Electronic Medical Record ESG EMR Standards and Guidelines FACES Family AIDS Care and Education Services FG Futures Group FHI 360 Family Health International 360 HIS Health Information System HL7 Health Level Seven HR Human Resource I-TECH International Training & Education Centre for Health ICD-10 International Classification of Diseases Version 10 KEMRI Kenya Medical Research Institute MDS Minimum Data Set MOH Ministries of Health MOMS Ministry of Medical Services MOPHS Ministry of Public Health and Sanitation MTRH Moi Teaching and Referral Hospital NASCOP National AIDS & STI Control Programme OpenMRS Open Medical Records System SDMX-HD Statistical Data and Metadata eXchange – Health Domain SNOMED Systematized Nomenclature Of medicine TCO Total Cost of Ownership TWG Technical Working Group XML Extensible Mark-up Language
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LIST OF EMR’s REVIEWED Name Full Name AMS 2000 Alliance Medical System Access Based System Kenyatta National Hospital EMR database
system developed using Microsoft Access database application
C-PAD Comprehensive Care Centre Patient Application Database
CARE 2000 COMPACT EDARP HMIS Eastern Deanery AIDS Relief Program Hospital
Management Information System EHospital EPICENTRE FUCHIA FUNSOFT HEALTH SOFT IQ CARE KEMRI/Wellcome Trust Kenya Medical Research Institute/Wellcome
Trust EMR System MEDBOSS OPENMRS AMPATH Open Medical Records System (Academic Model
Providing Access to Health, Eldoret) OPENMRS FACES Open Medical Records System (Family AIDS
Care and Education Services, Kisumu) TRIMED BOMU BOMU Hospital EMR System
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FOREWORD The use of information technology in health is quickly gaining global popularity with many health persons adopting electronic health record management systems. Kenya is not to be left behind in this revolution. Several initiatives in the country are currently looking at improving health care reporting and outcomes using IT. These initiatives include the adoption of the DHIS, and the use of Electronic Medical Record Systems in the country. The Kenya Ministries of Medical Services and Public Health and Sanitation developed and disseminated the Standards for Electronic Medical Record Systems in Kenya. These standards are aimed at ensuring appropriate implementation of functional systems in the country’s health facilities, with an aim of having sustainable implementations that result in improved quality of patient care. It is the expectation of the Ministries that all systems implemented and used in the Kenya health facilities shall meet the standards that have been defined. This Review Towards Standardization report represents the initial efforts of the Ministries towards ensuring the standardization of electronic medical record systems, and by extension, all IT systems used in the Kenya health sector. The review process was an elaborate and consultative process that involved the Ministries and all stakeholders. This process forms precedence for future reviews that will be institutionalized within the Ministries to provide for continuous reviews towards standardization. This report, together with the standards and guidelines for EMR systems, provide good reference material for the country’s health managers to support their decisions around the selection and implementation of systems that will add value to health care. It is our hope that, from the results shown in this report, owners of electronic medical record systems will make strides towards ensuring that the systems they are supporting meet the standards set by the Ministries of Medical Services and Public Health and Sanitation to qualify for implementation in the Kenya health facilities.
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FOREWORD The Ministries of Medical Services and Public Health and Sanitation are quickly adopting the use of information technology in health. Standardization of these systems – functionality and deployment – is key to ensuring sustainable implementations. The Ministries are happy to have supported the first review towards standardization of electronic medical record systems in Kenya, culminating in this report. Through this report, the Ministries emphasize their resolve in ensuring that all systems in operation in the country meet the minimum standards set for the health system. This review process is just a first in a series that the Ministries will plan and conduct, while expanding the process to include other systems in use in the health sector. It is the expectations of the Ministries that only systems meeting standards will be implemented in health facilities in Kenya. It is also the hope that systems not meeting standards will be upgraded by the supporters so as to add value in the Kenya health sector.
Dr. N. Muraguri Dr. I. Mohammed Head – NASCOP Head - NASCOP Ministry of Public Health and Sanitation Ministry of Medical Services
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EXECUTIVE SUMMARY This report is the culmination of a review of the progress towards standardization and the state of use of electronic medical record (EMR) systems in selected facilities under Kenya’s Ministries of Health. The review was carried out by 6 teams comprising health sector stake-holders including the Ministries of Health (Ministry of Medical Services [MOMS] and the Ministry of Public Health and Sanitation [MOPHS]) represented by the National AIDS and STI Control Programme (NASCOP) and the Division of Health Information Systems (HIS) during the period 15-26 August 2011. The review was carried out at 28 facilities across 6 regions in Kenya - Nairobi, Central, Nyanza, Coast, Western and the Nairobi-Nakuru Highway.
The overarching objective of this report is primarily to provide the Ministries of Health with an understanding of the capabilities and usage of EMR systems in Kenya and provide implementers with information sufficient to inform the upgrade of systems to meet Ministry defined standards. It will also provide health sector stakeholders and EMR systems developers with a framework for the provision of technical assistance to enable the upgrade of existing EMR systems to meet the functional requirements defined by the Ministries of Health in the EMR Standards and Guidelines (ESG) document. Secondarily, the Ministry will use this report to help them select and recommend system(s) to be deployed in public health care faciltieis, and supported directly by MoH.
Background
Prior to this review, different government and multi-lateral organizations had undertaken three assessments. This was, however, before the development and adoption of national EMR Standards and Guidelines (ESG) for Kenya. Some of the systems covered in those assessments did not address the 6 minimum functional requirement categories which the ESG identified as important for defining standards for EMR systems in Kenya. However, these assessments, which were commissioned by NASCOP and the HIS, were important both in identifying systems and classifying challenges with the software reviewed, including:
1. Variable levels of functionality and data security;
2. Unpredictable vendor/technical support;
3. Long term sustainability issues;
4. Variable reporting functionality;
5. Limited feedback on EMR systems data for patient care; and
6. Limited ability to exchange information between systems.
According to the ESG, EMR systems must address the following 6 key functional areas:
i. Basic Demographic and Clinical Health Information;
ii. Clinical Decision Supporting;
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iii. Order Entry and Prescribing;
iv. Health Information and Reporting;
v. Security and Confidentiality; and
vi. Exchange of Electronic Information.
Some of the systems considered during the NASCOP and the HIS reviews did not meet the above functional requirements.
Justification
This survey is particularly important given that the Ministries of Health have recently launched the Kenya National eHealth Strategy 2011-2017. The automation of patient records in the form of EMR will play a crucial role in support of the operationalization of the National eHealth Strategy. In particular, the effective implementation of EMR systems will at a minimum:
1. Enable the capture of demographic and clinical health information;
2. Foster clinical decision support;
3. Enable order entry and medication prescribing;
4. Increase data security and confidentiality; and
5. Enable exchange of electronic information between practitioners, facilities and providers.
Methods
The review entailed visits by 6 survey teams to facilities in 6 different regions. The regions were Nairobi, Central, Coast, Nyanza, Western provinces and the Nairobi-Nakuru Highway. The sites were selected purposively through the EMR implementing partners, who were also asked to nominate facilities that they considered important for the review teams to visit as part of the review process. The TWG recommended the sites with optimal and sub-optimal EMR system implementation to enable the review process derive useful lessons by comparing the implementations. The systems selected for review by the TWG were those available in an EMR systems inventory that had been populated over time by the EMR TWG task force after collecting data from EMR systems stakeholders. The review was guided by a structured questionnaire, featuring functionalities selected from the ESG.
Recommendations
On the basis of the key findings, we recommend that the MOH with its partners through the TWG mechanism and other appropriate structures:
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1. Discuss system specific findings and collaboratively develop system specific upgrade plans with the respective developers and implementers in order to provide each with a chance to upgrade their system and meet defined standards;
2. Develop a framework within which continuous system reviews against standards can be done; and
3. Define criteria for on-going measurement of the impact of electronic medical records in Kenya; through specific metrics designed to measure the use of EMR systems, not simply their implementation, with an aim of ensuring that the systems impact health care.
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1 BACKGROUND AND INTRODUCTION The Ministries of Health are working towards establishing a standardized environment for the implementation and operationalization of EMR systems across all clinical facilities in Kenya. In order to achieve this, a Standards and Guidelines for EMR Systems in Kenya document has been developed and adopted with the participation of all the relevant health-sector stakeholders as identified by the Technical Working Group (TWG) on EMR. The document outlines the standards and guidelines with which EMR systems must comply.
1.1 Goal and Objectives of the Review
The primary goal of the exercise was to review EMR systems implemented at selected health facilities in Kenya in order to ascertain the extent to which the 6 functional areas described in the ESG had been met and to guide the development of plans upon which the systems would be upgraded to meet MOH requirements. In addition, the information collected in this exercise will help the MOH select and recommend the EMR system(s) to be rolled out at MOH supported health facilities. Specific objectives of the review were to:
1. Develop a framework for the provision of technical assistance to upgrade existing EMR systems to enable them meet the functional requirements defined in the EMR Standards and Guidelines Document;
2. Provide an evidence basis for the Ministries of Health to select appropriate EMR systems for implementation at various MOH sites;
3. Define a framework for future systems review to help ensure that systems meet evolving EMR requirements as the national eHealth architecture in Kenya becomes more developed;
4. Define initial criteria for the meaningful use of electronic medical records in Kenya; and
5. Initiate and institutionalize within MOH a process that will evolve into an established certification mechanism for EMRs in Kenya, in compliance with national and international standards.
1.2 Past Reviews
Previous assessments of EMR systems in the country identified multiple electronic health data systems in use. Some of these systems were Excel sheets and statistical analysis software, typically developed primarily to address reporting, clinical trials, or other research applications. These systems did not qualify as EMR systems according to the basic functional requirements of an EMR system as defined in the Standards and Guidelines for EMR Systems in Kenya(ESG) document. Consequently, these spreadsheets and statistical analysis software were excluded from this analysis. The review focused on assessing EMRs according to the definitions provided in the ESG document. The goal of this review was to establish the completeness of compliance with
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the set standards and suitability of EMR systems reviewed, rather than to focus on their inadequacy. This would enable the MOH to work with the various implementing partners to develop upgrade plans, where required, to ensure that all systems being used in health facilities meet MOH requirements.
2 JUSTIFICATION Since the year 2006, Kenya has conducted 3 assessments of EMR systems used in the country. These assessments focused on: general system characteristics of EMR’s, hardware and infrastructure requirements, human capacity and perceptions, data use for clinical and managerial decision making, data reporting and output capabilities, data security and quality, and linkages with other systems.
The assessments exposed several challenges to the implementation and use of EMR systems in Kenya. These challenges included: varying functionalities amongst systems, inability to share clinical information, inability to generate MOH defined reports and lack of supportive structures for successful implementations.
Following the realization of these challenges, the MOH developed a roadmap to guide the implementation of systems in Kenya. This roadmap emphasized on the development of standards for EMR systems. This, in November 2010, culminated in the launch of the first version of the Standards and Guidelines for Electronic Medical Record Systems in Kenya by the MOH. This document defines the minimum functional requirements of EMR systems and provides guidance on the appropriate implementation to ensure sustainability.
In line with the EMR roadmap, a review of systems against these standards was conducted in August 2011 to ascertain gaps between the standards and the systems as they are currently deployed. In some cases, systems in use presently have capabilities which are not used at specific facilities. The main aim of this review was to identify the strengths and gaps of the systems and subsequently draft upgrade plans with an overall aim of ensuring that all EMR systems primarily meet minimum functional standards and additionally, and explore factors affecting their implementation.
This review is, additionally, an important step towards enabling the attainment of the policy objectives of the Ministries of Health articulated in Kenya Vision 2030 (KV 2030) and article 43 (1) of the Constitution of Kenya which states in part that ‘Every person has the right to the highest attainable standard of health, which includes the right to healthcare services, including reproductive healthcare.’
To help operationalize this, the Ministries of Health have recently launched the Kenya National eHealth Strategy 2011-2017. The automation of patient records through the use of Electronic Medical Records will play a crucial role in supporting the realization of the National eHealth Strategy.
It is expected that, following this review, and after the implementation of all developed upgrade plans, EMR systems recommended for use in Kenya will all meet the defined
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minimum MOH standards resulting in the realization of the benefits of using systems in supporting improvement in delivery of quality health services. In particular, the effective implementation of EMRs will:
1. Enable the capture of demographic and clinical health information;
2. Foster clinical decision support;
3. Enable order entry and medication prescribing;
4. Increase data security and confidentiality; and
5. Enable exchange of electronic information between providers, facilities and policy makers.
3 METHODS The review process officially commenced with the formation of a task force by the EMR Technical Working Group in April 2011. The core of the task force primarily comprised of members from the MOH (NASCOP and HIS), and select implementing partners. (See appendix I for a list of task force members)
The mandate of the task force was to ensure successful implementation of the entire review process and provide results to the EMR TWG. Specific responsibilities of the task force were:
1. To develop technical guidelines to steer the entire review process;
2. To provide guidance to the TWG to enable them facilitate formation of competent teams of reviewers;
3. To develop tools and review methodologies to ensure adherence to an efficient process as well as collection of high quality data.
4. Production of a report describing the review process and its results.
The task force created 6 teams of reviewers, each comprising of 3-4 members. (Appendix 2 – Review teams and membership)
3.1 Selection of functionalities against which to conduct the review
The Standards and Guidelines document provided the basis for reviewing EMR systems.
3.2 Selection of systems for review
The Ministries of Health convened a meeting of stakeholders during which a listing of EMR systems implemented in the country was made. In addition, the task force members were tasked with creating an inventory of EMR systems. The systems selected for review thereafter were derived from this inventory.
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3.3 Selection of health facilities for the review
The facilities were selected purposively through the task force. The EMR implementing partners were asked to nominate the facilities that the teams ought to visit as part of the review process. The TWG recommended the sites with optimal and sub-optimal EMR implementations to enable the review process derive useful lessons by comparing the implementations.
All facilities were informed of the review in advance to enable them prepare to participate in it effectively and were encouraged to conduct self-attestation as well. Where possible, sample data and use cases were provided to the institution, to be used during system walk-throughs.
3.4 The Review Team
To assure objectivity, the process was led by the MOH (represented by NASCOP and HIS) through the EMR TWG appointed task force chaired by NASCOP. Representation on the review team comprised of stakeholders and partners of the MOH who are also members of the EMR TWG.
The composition of the review team was as follows:
i. A member well versed in review of I.T. systems ii. A member with good understanding of the health sector and medical terminologies iii. A member with a good comprehension of HIV/AIDS programming based on tenets
of the NASCOP.
The team’s mandate was to:
i. Review selected EMR systems in order to come up with an objective system review report;
ii. Compile a report of the available and missing functionalities and agree with the EMR systems developer institutions on the best approach towards upgrade of the systems;
3.5 The Review Process
The review was carried out in 3 phases:
Phase 1: Review of relevant EMR reports to gather information contained in the assessment reports.
The reviewers started by carrying out desk review of existing reports, to get an understanding of the functionality of systems to be reviewed. This gave them access to already documented information and informed the subsequent review to be undertaken in phase 2.
The reports reviewed included:
1. The CDC Assessment report.
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2. Review of Software in the Health Sector, Kenya (2009) report
3. The EMR Systems Assessment Harmonized report.
Phase 2: Review of the actual EMR systems, features and functionalities of the systems as defined in the standards document.
The Review of actual EMR systems was undertaken to have a clear and detailed overview of the functions of each EMR system in line with the minimum functional requirements outlined in the ESG. The review tool that had been developed and adopted guided this phase. (See appendix 6 for the tool).
The review team visited each EMR implementing facility, and together with the facility staff and system developers / implementers where available, carried out a system walk through in order to review its functionalities.
Each criterion had detailed EMR use cases, inputs, expected behaviour under various conditions, and expected outputs. Standardized criteria were used for all EMR systems.
Phase 3: Review of reference site(s) for each selected system in depth to understand its implementation under favourable and optimal circumstances.
For each of the identified systems, a review was carried out at selected reference sites to understand:
D6 The minimum infrastructure needed to successfully implement and operate the system at the facility;
E6 Models of implementation;
F6 Patient volumes;
G6 The level of support for the system, where the support comes from, and the quality of support as defined in the standards document;
H6 The HR needs to have the EMR system fully functional at the health facility;
I6 Work load and workflows.
In addition, the review team documented the levels and type of facilities in which each system is implemented e.g. level 1, 2, 3, 4, 5, or referral facilities.
3.6 Analysis of Review Results
Analysis of results was based on the 17 systems reviewed rather than on the 28 health facilities in which the review was conducted. Where the same system was reviewed in multiple facilities, the results were merged and the best score selected to take care of
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situations where functionality existed but was not demonstrable at one facility unlike the other.
Results were analysed across each functional area as described in the review tool (appendix 6).
Each system was given a total percentage score based on the total functionalities met.
For each functional area, a percentage score was calculated as the number of functionalities met divided by the total number of functionalities assessed. In order to score the total extent to which systems met the defined standards, each of the 7 functional areas was equally weighted (14.29%).
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4 RESULTS
4.1 Facilities and Systems Reviewed
There were 17 different EMR systems reviewed in 28 health facilities. The table below shows the distribution of the 17 systems across the facilities. C-PAD and IQ Care were reviewed in 4 facilities whereas OpenMRS AMPATH was reviewed in 3 facilities. Appendix 3 provides a listing of all health facilities at which the review was done.
Table 1: Frequencies of EMR Systems Implementation EMR System(s) No.Of Facilities
reviewed (n=28) AMS 2000 1 Access Based System 1 C-PAD 4 CARE 2000 2 COMPACT 2 EDARP HMIS 1 EHospital 1 EPICENTRE FUCHIA 1 FUNSOFT 2 HEALTH SOFT 1 IQ CARE 4 KEMRI/Wellcome Trust 1 MEDBOSS 1 OPENMRS AMPATH 3 OPENMRS FACES 1 TRIMED 1 BOMU 1
4.2 General System Information Table 2: General System Information Summary Review Area Result Total No. Of Distinct EMR Systems 17 No. Of Years for EMR Operation (Range) 2 months - 7 Years No. Of facilities using the System (Range) 1 - 80 Health Facilities Client Supported Platforms
Windows 17 Linux 3 Macintosh 3
Server Supported Platforms Windows 15 Linux 5
Database Software Used
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MySQL 3 MS SQL 6 Oracle 2 MS Access 4 Postgre SQL 2 Unknown 1
System Design Desktop Application 11 Web Application 6
System Specialization Disease specific 7 Primary Health Care only 1 Both Dx Specific and Primary Health Care 1 Full HMIS 7 HMIS & Primary Health Care 1
System Ownership Proprietary 9 Open Source 8
System Data Entry Point of Care Support 5 Retrospective Only 9 POC & Retrospective 3
System Implementation Standalone 3 LAN 13 WAN 1
Available Documentation No documentation available 5 Only Technical Documentation available 2 Only User documentation available 9 Both Technical and User documentation available
1
Interface Customization Ability None 3 Developer 9 “Requires both” Developer & User 5
Systems Support Location In Country 13 In country & Community 2 Vendor Agreement 1 Unknown 1
The 17 systems reviewed had been in operation in the health facilities for periods ranging from 2 months to 7 years. The total number of health facilities reported to be using the
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systems (for each system) varied from 1 to 80 facilities. All the systems supported a Microsoft client operating system. 16 systems supported server operation. Variable database back ends were supported by the systems; My SQL – 3 systems, MS SQL – 6 systems, Oracle – 2 systems, MS Access – 4 systems, Postgre SQL – 2 systems. In looking at the user interfaces supported, none of the systems supported both a desktop and a web interface, whereas 11 were exclusively desktop applications and 6 were exclusively web applications. None of the systems supported a mobile application interface. 7 systems were full HMIS applications and 7 supported specific disease domains. Notably, majority of the disease domain systems supported HIV care and treatment. 9 systems reviewed supported retrospective data entry. Only 5 could be used as point of care or efirst systems.3 systems supported both retrospective and point of care data entry. 5 systems had no documentation, 2 systems had technical documentation, 9 systems had user documentation and 1 system had both technical and user documentation. Local or in-country support was available for 13 systems. 2 systems, in addition, had in-country and a international community of support available.
4.3 Findings by EMR functional area
The following section presents the findings by, functional area, of the 17 EMR systems reviewed.
4.3.1 System Details and Standards (SDS)
Even though the ESG does not include SDS among the minimum functional requirements for an EMR as a distinct functional area, the review tool included a section labelled SDS. As described earlier, the SDS was crafted by the TWG task force to hold functional elements extracted from the 6 functional areas as described in the ESG that logically could be grouped together to enable their efficient review. This further enabled analysis of specific details at implementing facilities, such as naming protocols and user specific features.
Significant variation was observed in this area of investigation ranging from a high of 82.4% on customizable user interface (F) to a low of 29.4% on data verification and validation (E) and use of standard drug coding system. The low implementation of verification and validation processes is concerning since this is an important feature in assuring data integrity and accuracy.
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Key: A. Uses a standardized naming protocol e.g. ICD10 or SNOMED B. Uses a standard drug coding / listing system C. Uses a standard lab test coding / listing system D. User friendly system prompts and appropriate error messages with clear corrective action E. Data verification and validation implemented F. Customizable user interface (forms and fields) G. Built-in backup and restore feature
4.3.2 Basic Demographic and Clinical Health Information
This entailed an assessment of the minimum information regarding patient identification and management of patient information including information on encounter events.
Whereas majority of the systems reviewed supported the use of a unique patient identifier (94.1%), and were able to adequately record patient demographics (88.2%) and generate patient lists (94.1%), none of the systems provided for patient education materials. 1 system was able to manage drug interactions and adverse drug reactions. 4 systems (23.5%) provided for biometric and bar code support while another 4 supported patient referrals.
Key: A. Unique patient identification system B. Multiple Patient Identifiers Supported C. Supports patient search for patients using one or multiple identifiers D. System captures defined Minimum Data Set E. Biometric, Bar Code support F. Supports patient referral G. Records patient demographics H. Maintains up-to-date problem lists I. Maintains medication lists J. Maintains allergy lists K. Records vital signs L. Incorporates lab test results M. Generates Patient lists N. Patient Education Materials
available O. Generates clinical summaries P. Provides a longitudinal view of a patient’s medical history Q. Captures historical medical history / information R. Manages drug interactions S. Manages adverse drug reactions T. Implements persistent patient records allowing for rollback in case of Deletion of Patient/Patient Records U. Supports Appointment scheduling set up, update and management 4.3.3 Order Entry and Prescription
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Systems that support order entry and prescribing have been demonstrated to reduce errors and adverse events reduce treatment cost while maintaining quality and supporting a refined and desired care process based on approved clinical guidelines. The review assessed whether systems supported order entry and prescribing.
59% of the systems reviewed supported the generation of prescription orders and 52% could generate lab orders.
Table 3: Order Entry and Prescription
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This entailed establishing the capabilities of an EMR system to provide active and passive support to health workers to enable them make correct clinical decisions and thus improve quality of health services. Decision support was assessed as either ability to provide proactive alerts or generate reports that can be used to make clinical decisions.
Of the 17 systems reviewed, availability of this functionality was way below expectations. Only 3 systems (17.6%) incorporated clinical decision guidelines and could generate alerts or provide reports that could support clinical decisions
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4.3.5 Health Information and Reporting
The review assessed whether systems implemented were able to fulfil reporting requirements to various stakeholders, including the Ministry of Health.
Most of the systems had the components needed for health information reporting, with 13 (76.5%) capable of generating facility specific reports. Worryingly, however, only 10 systems (58.9%) were able to generate MoH required reports, a fundamental requirement by the Ministry of Health.
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Key: A. Customizable Reports B. Export/import of external reports C. Generates MoH required reports D. Generates Patient level reports E. Generates facility specific reports
4.3.6 Security and Confidentiality
The security and confidentiality section assessed the ability of the systems to protect patient information through the implementation of access control features (passwords, access levels) and lockouts. It further addressed issues ranging from health data protection to audit logs for access and data manipulation.
15 systems (88.2%) supported user authentication during system access. 13 (76.5%) were able to back up patient data either via an automated backup system or a manual system requiring a user intervention. Only 5 systems (29.4%) had implemented an audit trail to track the user operations on the system.
Key: A. Supports user authentication B. Encryption Matrix implemented for User Passwords C. Supports role based access control D. Audit trail / log supported E. Supports analysis of audit trails reports F. Automatic logoff implemented G. Manual and automated database back up H. Data Encryption within the Database
4.3.7 Exchange of Electronic Information
Exchange of electronic information is important to ensure interoperability between different health systems. This review assessed the capability of the systems to exchange information using recognized standards, notably HL7 and SDMX. The focus was around the exchange of information between clinical systems and pharmacy and laboratory
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systems and between clinical systems and the DHIS2. The review not only focused on the ability of the systems to electronically exchange information, but also assessed the readiness of the systems to do this.
Only 4 systems were able to electronically exchange patient summary information and transmit prescriptions. 3 systems (17.6%) supported HL7, a standard protocol for the exchange of patient level data between systems. None of the systems could transmit data to the DHIS2 nor were they DHIS2 ready with SDMX support.
Key: A. Exchanges clinical information and patient summaries B. Electronically transmits prescriptions C. Electronically transmits and receives laboratory orders and results D. Electronically transmits aggregate information to DHIS2 E. Supports HL7 messaging F. Supports XML generation and messaging G. Supports SDMX-HD
4.4 Overall Scoring for System
The 17 EMR systems were scored with each functional area carrying equal weight. This was done to rationalise scoring across all the functional areas to alleviate the impact of those areas that may have, otherwise, had an inordinate contribution to variation within systems with only a few items under review (e.g. Order Entry with only 2 items). The functional areas were considered equally important with the systems. The aggregated results of the 7 functional areas per system reviewed are as shown in table 5 below.
Of the systems reviewed, the EMR systems with the highest weighted scores over the seven functional areas were OPENMRS AMPATH, IQ Care and C-PAD at 95.2%, 90.3% and 77.1% respectively.
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5 EMR System Use at the Facilities The review process, through the review of implementations in different health facilities, demonstrated that, even though required functionalities are implemented in some systems, their use at facility levels vary. This was particularly demonstrated where the same EMR system was reviewed in more that one facility. In some cases, users were not aware of functionality even though it already existed in the system, and were therefore not able to demonstrate it. This is indicative of a training need to make the users competent in exploiting the full potential of EMR systems.
The following table demonstrates the variable use of CPAD and IQ Care across selected functional areas in different health facilities.
System Implementation Select Functional Areas
Records vital signs Captures the Minimum Dataset
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In as much as the selected functionalities have been implemented in both CPAD and IQ Care and were demonstrable in one or more facilities, other facility users were not able to demonstrate their use. This makes for a case for more standardized training approaches for all systems and for the monitoring of use of EMR systems at health facilities so as to ensure that the systems are actually used to support care services.
1. Developing a criteria for monitoring use of EMR systems
A key output of this review process was to recommend criteria for monitoring the use of EMR systems in Kenya. It is acknowledged from the data gathered that implementing systems is one thing and ensuring their adequate use is another. Only well used EMR systems will result in the improvement of clinical care in the health sector. This monitoring can either be based on quantitative measures or quality measures as customized by the country.
A sample criterion for monitoring the use of EMR systems is provided in appendix 4. At the writing of this report, however, discussion were still on going, under the leadership of the Ministries of Health, to develop more comprehensive and conclusive criteria for monitoring and evaluating the use of EMR systems in Kenya.
6 CONCLUSIONS AND RECOMMENDATIONS On the basis of the foregoing findings, we recommend that the MOH with its partners through the TWG mechanism:
1. Discuss system specific findings and collaboratively develop system specific
upgrade plans with the respective developers and implementers in order to provide each with a chance to upgrade their system and meet the defined standards;
2. Develop a framework within which continuous system reviews against standards can be done; and
3. Define criteria for on-going measurement of the impact of electronic medical records in Kenya, through specific metrics designed to measure the use of EMR systems, not simply their implementation, with an aim of ensuring that the systems impact health care.
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Appendices
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Appendix 1: Statistical Tables Table 1: System Details and Standards Functionality N Meeting
Requirement (%) Uses a standardized naming protocol e.g. ICD10 or SNOMED
17 10 (58.8)
Uses a standard drug coding / listing system 17 6 (35.3) Uses a standard lab test coding / listing system 17 7 (41.2) User friendly system prompts and appropriate error messages with clear corrective action
17 13 (76.5)
Data verification and validation implemented 17 6 (35.3) Customizable user interface (forms and fields) 17 14 (82.4) Built-in backup and restore feature 17 12 (70.6) Table 2: Baseline Demographic and Clinical Health Information Functionality N Meeting
Requirement (%) Unique patient identification system 17 16 (94.1) Multiple Patient Identifiers Supported 17 13 (76.5) Supports patient search for patients using one or multiple identifiers
17 15 (88.2)
System captures defined Minimum Data Set 17 9 (52.9) Biometric, Bar Code support 17 4 (23.5) Supports patient referral 17 4 (23.5) Records patient demographics 17 15 (88.2) Maintains up-to-date problem lists 17 10 (58.8) Maintains medication lists 17 10 (58.8) Maintains allergy lists 17 10 (58.8) Records vital signs 17 10 (58.8) Incorporates lab test results 17 9 (52.9) Generates Patient lists 17 16 (94.1) Patient Education Materials available 17 0 (0) Generates clinical summaries 17 12 (70.6) Provides a longitudinal view of a patient’s medical history 17 12 (70.6) Captures historical medical history / information 17 11 (64.7) Manages drug interactions 17 1 (5.9) Manages adverse drug reactions 17 1 (5.9) Implements persistent patient records allowing for rollback in case of Deletion of Patient/Patient Records
17 12 (70.6)
Supports Appointment scheduling set up, update and management
17 11 (64.7)
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Table 3: Clinical Decision Support (order) Functionality N Meeting
Requirement (%) Incorporates clinical decision guidelines 17 3 (17.6) Generates alerts to support clinical decision 17 3 (17.6) Table 4: Exchange of Electronic Information Functionality N Meeting
Requirement (%) Exchanges clinical information and patient summaries 17 4 (23.5) Electronically transmits prescriptions 17 4 (23.5) Electronically transmits and receives laboratory orders and results
17 3 (17.6)
Electronically transmits aggregate information to DHIS2 17 0 (0) Supports HL7 messaging 17 3 (17.6) Supports XML generation and messaging 17 3 (17.6) Supports SDMX-HD 17 0 Table 5: Health Reporting Functionality N Meeting
Requirement (%) Customizable Reports 17 11 (64.7) Export/import of external reports 17 12 (70.6) Generates MoH required reports 17 10 (58.8) Generates Patient level reports 17 15 (88.2) Generates facility specific reports 17 13 (76.5) Table 6: Order Entry Functionality N Meeting
Requirement (%) Generates prescriptions orders 17 10 (58.8) Generates lab orders 17 9 (52.9) Table 7: Security and Confidentiality Functionality N Meeting
Requirement (%) Supports user authentication 17 15 (88.2) Encryption Matrix implemented for User Passwords 17 14 (82.4) Supports role based access control 17 11 (64.7) Audit trail / log supported 17 5 (29.4) Supports analysis of audit trails reports 17 5 (29.4) Automatic logoff implemented 17 7 (41.2)
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Manual and automated database back up 17 13 (76.5) Data Encryption within the database 17 9 (52.9)
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Appendix 2: Task Force and Review teams membership Task Force
1. Julius Mutiso – Chair (NASCOP)
2. Onesmus Kamau – Co-Chair (DivHIS)
3. Steven Wanyee – Overall coordinator (I-TECH Kenya)
4. Sam Kanga – member (UNITID)
5. Ali Karisa – member (FG)
6. Cecilia Wandera – member (NASCOP)
7. Naomi Shiyonga – member (NASCOP)
Review Teams
Nairobi Team
Karisa Ali, FG Naomi Shiyonga, NASCOP Philip Musina, KNH Stanley Mwikya, HIS
Nyanza Team
George Owiso, EDARP Lance Ndumari, NASCOP Peter Wamae, KNH Samuel Kang'a, I-TECH
Western Team
Julius Mutiso, NASCOP Daniel Cheruiyot, MOH Kemboi, MOH Dr. Amin, Kilifi Wellcome Trust
Central Team
Onesmas Kamau, HIS Dr. Githuka, MOH
Francis Ndichu, NPHL Peter Kungu Kamau, HIS Coast Team
Steven Wanyee, I-TECH Jackson Mulungye, NASCOP Rose Nzioka, I-TECH
Nairobi-Nakuru Highway Team
Dr. M. Aluda, FHI Cecilia Wandera, NASCOP Kiminta, MTC
Activity Oversight Team
Dr. Nzioka, MOH-HIS Dr. Kimanga, MOH-NASCOP Dr. Odawo, I-TECH Kenya Anne Barsigo, Futures Group
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Appendix 3: Health Facilities Selected for System Review
HEALTH FACILITY LEVEL SYSTEM IN USE 1 Bomu Hospital, Mombasa BOMU EMR 2 Kenyatta National Hospital Access based system (Modular) 3 AIC Kijabe Hospital ALLIANCE MEDICAL SYSTEM
(AMS 2000) 4 The Nairobi Hospital Care 2000 5 The Aga Khan University Hospital Care 2000 6 Coast Provincial General Hospital COMPACT 7 Rift Valley Provincial General Hospital COMPACT 8 Athi River Health Center CPAD 9 Muhoroni Sub- District Hospital C-PAD
10 Thika District Hospital CPAD SYSTEM 11 Gatundu District Hospital CPAD V2.0 12 EDARP Komarock Health Center EDARP HMIS 13 Gurunanak Hospital EHospital lite 14 Maragua District Hospital EPICENTRE FUCHIA V1.6.0.32 15 Rift Valley Provincial General Hospital FUNSOFT 16 Kisii Level 5 Hospital FUNSOFT 17 St. Joseph’s Migori Mission Hospital Health Soft 18 St. Luke’s Hospital, Kaloleni IQ Care 19 St. Joseph’s Migori Mission Hospital IQ CARE 20 AIC Kijabe Hospital IQ CARE 21 Baraka Health Centre IQ-Care V3.0a 22 KEMRI/Wellcome Trust District Hospital KEMRI/Wellcome Trust EMR
system 23 Naivasha District Hospital MEDBOSS 24 Lumumba Health Center OPEN MRS-FACES
25 Rabuor Health Center OPEN MRS-FACES
26 Busia District Hospital OpenMRS – Busia D.H - CCC 27 Mosoriot RHDC OpenMRS – Mosoriot RHDC 28 Moi Teaching And Referral Hospital OpenMRS – MTRH 29 Avenue Hospital TRIMED (TRIFOR Web based
system)
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Appendix 4: Monitoring the Use of EMR Systems in Kenya
Year 2011 targets Year 2012 targets Year 2013 targets
50% of patients have their records in the EMR system
50% of all patient summaries electronically generated by EMR system and available in HL7 format
100% of patient visits captured in EMR system
80% of patient visits are captured in the EMR system
100% of monthly reports electronically transmitted to DHIS2
50% of patient visits captured via efirst
75% of all laboratory tests recorded in the EMR system
100% of diagnostics derived from an ICD-10 coding scheme within the EMR system
50% of drug to drug interactions are identified using the EMR system
75% of all prescriptions generated from the EMR system.
75% of treatment failures identified using the EMR system
25% of prescriptions and lab orders electronically transmitted to the next service point
NOTE: This table is provided as an example and not as targets already set by the Kenya Ministries of Health. As at the time of writing of this report, discussions were still on-going on setting targets for the use of EMR systems in Kenya.
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Appendix 5: Developing Upgrade Plans for Systems
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Appendix 6: Review Tool
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Background and Introduction
31
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32
GENERAL SYSTEM INFORMATION This section collects general information regarding the system.
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34
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GENERAL FACILITY INFORMATION $!"'.$.#70')4$6'1.$0)$845#%.0645$0"#$'123#1#4060')4$#4&'%)41#40$)*$0"#$.6'5$+,-$./.0#1>$
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Factor Facility Comments Number of days without power in last month?
Primary source of power
Power grid Solar Generator Other:_____________________
Backup source of power
Power grid Solar Generator Other:_____________________
Voltage stabilizers?
Yes No
!##J 51/,'#&(!
What physical security has been implemented for the computer(s) in this facility? Lockable Cabinets Grills on doors Bars on Windows Lockable Doors Security Guard Computer lock chain
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$SECURITY AND CONFIDENTIALITY
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645$'47385'4:$)0"#%$600%'=80#.$('33$=#$2%#.#%$'4$0"#'%$)%':'463$2%#d=67@82$.060#>$
2%#.#%$0"#'%$)%':'463$.060#$645$'*$=67@$82$*'3#$"6.$0)$=#$84N'22#5A$26/$.2#7'63$600#40')4$0)$7/73'7$%#5845647/$7"#7@$#%%)%.$5#4)0'4:$*'3#$5616:#$)%$163*8470')4$)*$84d7)12%#..')4$2%)7#..>$
45
D. BASIC DEMOGRAPHIC INFORMATION $!"'.$ .#70')4$ 0#.0.$ 0"#$ ./.0#1.$ *8470')463'0'#.$ 0)$ 7)33#70$ 5#*'4#5$ 5#1):%62"'7$ '4*)%160')4>$ ?4$ 0"'.$ .#70')4A$ X$ 260'#40$ %#7)%5.$ *)%$M#4'46"$SQ)@'$96168$645$M#4'46$a64:8'$96168$6%#$7%#60#5$645$0"#$5#1):%62"'7$%#7)%5.$#40#%#5$645$164'28360#5>$!"#$*)33)('4:$'.$6$5#1):%62"'7$2%)*'3#$)*$+1$#$23!MR)S#!@2?2,>$
• -#*#%%63$.)8%7#B#40%/$2)'40G$M,!J!$$• S61#G$M#4'46"$SQ)@'$96168$• D#<G$F#163#$• I60#$)*$H'%0"G$X\0"$,6%7"$R_^b$• M367#$)*$H'%0"G$9'61=8$• !#3#2")4#G$b]bbk$bbbbb[Z$• ,6%'063$D0608.G$D'4:3#$• L778260')4G$H8.'4#..$a)164$• S#<0$)*$9'4G$d$E365/.$a6'0"#%6O$D'.0#%$
• I68:"0#%G$-#:'46$96168A$R/%$\$1)40".$)35$• I'.0%'70G$S6'%)='$• e)760')4G$H6=6$I):)$• D8=de)760')4G$964/61(6$• M"/.'763$`55%#..G$H6=6$I):)A$S6'%)='$• J3).#.0$e64516%@G$H6=6$I):)$J60")3'7$7"8%7"$
$
!"#$*)33)('4:$'.$6$5#1):%62"'7$2%)*'3#$)*$+1$#$2!T2$C,#!@2?2,>$• -#*#%%63$.)8%7#B#40%/$2)'40G$jJ!$$• S61#G$M#4'46"$a64:8'$96168$• D#<G$F#163#$• I60#$)*$H'%0"G$\0"$,6/$R_]\$• M367#$)*$H'%0"G$,8%64:C6$• !#3#2")4#G$b]bbk$bbbbb[[$• ,6%'063$D0608.G$,6%%'#5$
• L778260')4G$!#67"#%$• S#<0$)*$9'4G$d$S)4#$• I'.0%'70G$S6'%)='$• e)760')4G$I645)%6$• D8=de)760')4G$I645)%6$• M"/.'763$`55%#..G$I645)%6$• J3).#.0$e64516%@G$I645)%6$M%'16%/$
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46
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5&2$42'4!81*1'1$/1! N1$1'2.!M)&1%!*)'!816#191'!
1d Login as a user and create patient records for Peninah Njoki Kamau and Penina Wangui Kamau using the demographic profiles provided above.
Login successful; Patient record selected.
11.1 System supports secure log into the EMR system.
2d Demonstrate the use of a unique identifier in the system. Demonstrate the patient identifiers collected by the system and how these identifiers are used in patient searches.
System is able to capture multiple identifiers for every patient
3d Look up for patient records by the last name ‘KAMAU’
2 records retrieved for Peninah Njoki and Peninah Wangui using a name search.
47
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5&2$42'4!81*1'1$/1! N1$1'2.!M)&1%!*)'!816#191'!
4d Re-do the search; look up patient by another method, using a different identifier
Patient records returned as per the given identifier.
5d Search for Peninah Njoki’s record using her unique patient number.
Only Peninah Njoki’s record is retrieved using her number.
6d Update patient history for Peninah Njoki with the following information: • Patient reports that she got
married • Her partner has not been tested
for HIV. • Patient reports that her mother
just diagnosed with breast cancer Display patient history.
Patient history displays with update.
3.8 System collects and stores family history, including, but not limited to history of chronic diseases such as hypertension, diabetes and cancers including date of diagnosis
48
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5&2$42'4!81*1'1$/1! N1$1'2.!M)&1%!*)'!816#191'!
7d Show how the system captures and displays the social history elements of the patient.
Social History displayed: d Marrie
d d Busine
ss woman
3.3 The system captures and stores, at minimum, the following social history elements: marital status, occupation, socioeconomic status, and education
The elements may either be in a coded form or as free text.
8d Print out / display a list of patients in the system
List generated and displayed/ printed
49
E. CLINICAL HEALTH INFORMATION, CLINICAL DECISION SUPPORT, AND ORDER ENTRY AND PRESCRIBING
$!"'.$.#70')4$0#.0.$0"#$6='3'0/$)*$0"#$./.0#1$0)$164'28360#$73'4'763$'4*)%160')4$645$.822)%0$73'4'763$5#7'.')4$16@'4:$58%'4:$260'#40$76%#>$?4$655'0')4A$0"#$.#70')4$0#.0.$0"#$)%5#%$*8470')463'0'#.$*)%$2%#.7%'20')4.$645$36=)%60)%/$)%5#%.>$!"#$*)33)('4:$"'.0)%'763$1#5'763$'4*)%160')4$'.$2%)&'5#5G$P"+G$!#.0$560#$1'48.$Yb$(##@.$UB,'"(%#",(C(&,7+,@(%#",V$+2%&!"14#/2.!0#%&)'(!Q!+')-.1?!P#%&I!M#4'46"$ '.$2%#:4640$645$63.)$%#7#'&'4:$0%#601#40$*)%$.1#6%$2).'0'&#$2831)46%/$08=#%783).'.$*%)1$"#%$ 3)763$"#630"$7#40%#$UH6=6$I):)$I'.2#4.6%/V>$D"#$"6.$=##4$)4$0%#601#40$*)%$08=#%783).'.$*)%$0"#$26.0$Z$1)40".>$D"#$(6.$'4'0'633/$ .06%0#5$ )4$ -'*612'7'4A$ ?.)4'6N'5A$ M/%6N'461'5#$ 645$ +0"61=80)3$ U-Kl+V$ 645$ '.$ 78%%#403/$ )4$ 0"#$ 7)40'4860')4$ 2"6.#$ )*$ "#%$0%#601#40$('0"$-'*612'7'4$645$?.)4'6N'5$U-KV>$K#%$.28081$.1#6%$%#.830.$6%#$6.$*)33)(.G$?4'0'63$k$2).'0'&#$UmmmVA$,)40"$X$k$2).'0'&#$UmVA$,)40"$Z$k$4#:60'&#>$D"#$"6.$63.)$0#.0#5$2).'0'&#$*)%$K?j>$K#%$26%04#%$5)#.$4)0$@4)($"#%$K?j$.0608.$/#0A$645$."#$'.$4)0$6(6%#$'*$"#$"6.$=##4$0#.0#5$*)%$K?j$0))>$D"#$'.$63.)$)4$0%#601#40$*)%$"/2#%0#4.')4$'4$2%#:4647/$645$'.$)4$`35)1#0$[bb1:$0"%##$0'1#.$6$56/>$M#4'46"$"6.$=##4$%#7)%5'4:$"#%$=3))5$2%#..8%#$%#65'4:.$*)%$0"#$26.0$Y$56/.>$K#%$%#65'4:.$"6&#$=##4G$140/90 mmHg, 150/90 mmHg and 140/80mmHg.$D"#$"6.$4)$"'.0)%/$)*$5'6=#0#.$)%$64/$)0"#%$7"%)4'7$'334#..>$N($1/).)C#/! Q!F-%&1&'#/!0#%&)'(I!M6%6$R$m$b$E%6&'56$X>$ e6.0$5#3'&#%/$(6.$R>[$/#6%.$6:)$&'6$ 7#.6%#64$ .#70')4>$S)$"'.0)%/$)*$8.#$)*$*61'3/$23644'4:$1#0")5.>$L..1'C#1%I$M#6480.$
Procedure Expected Result
Actual Result Requirement met (!) Not met (")
Standard Reference General Notes for Reviewer
9d Record into the system the above historical medical information for Peninah Njoki Kamau. The following information should be
The indicated historical information is recorded.
3.1 System allows capture and entry of past medical history 3.2 System has the
50
Procedure Expected Result
Actual Result Requirement met (!) Not met (")
Standard Reference General Notes for Reviewer
recorded and displayed: i. Pregnancy status with the LMP
and EDD ii. Tuberculosis status, treatment
(historical and current), and historical smear test results
iii. HIV status iv. Hypertensive status, treatment
and historical readings for the past 3 days
v. Obs/Gynae history vi. Allergies vii. Indication of no DM
Patient summary displays/prints the historical information
capability to manage and present current and historical test results to appropriate clinical personnel for review, with ability to filter and compare results with previous tests.
10d Review allergies. Allergy to peanuts displayed The indication that the patient has a known allergy must be in discrete data.
3.6 System documents all existing allergies, intolerance and adverse reactions to drugs and interactions, including dietary and environmental triggers
51
Procedure Expected Result
Actual Result Requirement met (!) Not met (")
Standard Reference General Notes for Reviewer
11d Start a new encounter record for Peninah: Demonstrate how the system is designed to capture data required by MoH.
4.1 System supports the capture / entry of all clinical events, encounters and/or episodes relevant to the care of a patient.
4.2 System includes forms for data capture as well as patient and treatment forms as defined by Ministry of Health data requirements.
The system forms may not necessarily look like MoH defined forms but capture the required data sets. Data capture forms will depend on the type of EMR being assessed, e.g. disease specific systems will have forms relevant to that department in the MoH.
52
Procedure Expected Result
Actual Result Requirement met (!) Not met (")
Standard Reference General Notes for Reviewer
12d Enter Peninah’s vital signs data: BP 140/90
Height 136cms
Weight 64kgs
Temperature 36.8 C
Pulse 80 beats/min
Respiratory Rate 16 breaths/min
Vital signs as captured as discrete data elements.
4.4 System has the capability to capture vital signs. At minimum height, weight, pulse rate, respiratory rate, BP, BMI, MUAC for children
13d Enter diagnosis: i. High Risk Pregnancy ii. Stage 2 HIV disease Use whatever coding scheme is appropriate for the system.
System accepts data as entered. High Risk Pregnancy and HIV are added to the problem list. Date of diagnosis is captured
5.4 The system shall provide the ability to maintain a coded list of problems / diagnoses.
5.3 When capturing problem information, the system captures at minimum the diagnosis date and
Various systems may use different coding schemes for diseases such as ICD-10 and SNOMED. Examples of ICD-9 codes provided: 648.8 (gestational diabetes); V23.9 (high risk pregnancy). Some systems may capture data in a own-defined scheme/reference tables.
53
Procedure Expected Result
Actual Result Requirement met (!) Not met (")
Standard Reference General Notes for Reviewer
severity of illness.
14d Display Problem List. Problem List displays (onset date of each problem indicated): • Pregnan
cy • Hyperten
sion • HIV • High
Risk
5.1 The creates, maintains and reports all active problems associated with the patient.
The system shall provide the ability to maintain the onset date of the problem / diagnosis.
Pregnant state could be captured someplace other than in the Problem List. Examples of ICD-9 include 648.8 (gestational diabetes). The problem list generated should be logically related to the diagnoses
15d Place laboratory test orders for Peninah: Select order set for antenatal profile
System records the test orders. At minimum,
18.1 System supports the recording and tracking of clinical orders and requests
Order sets will only be checked if the system supports them. If not, the orders can be
54
Procedure Expected Result
Actual Result Requirement met (!) Not met (")
Standard Reference General Notes for Reviewer
(Hemoglobin, VDRL, Blood Group, Rhesus Factor). Additionally, order for:
d CD4 counts d ALT levels d Creatinine Levels
the system records: d The test
requested d Date
requested
such as prescriptions and other treatment orders, laboratory investigation requests, and referrals
entered individually.
16d Access patient educational materials for Hypertension in pregnancy or HIV and print to provide for patient.
Patient educational materials accessed and printed.
8.2 System has the capability to create, review, update and delete patient education materials.
8.1 System has the capability to create, review, update and delete patient education plans and materials as defined by disease programs such as NASCOP. DLTBLD, and Malaria
17d Create a referral to a nutritionist as part of the encounter. Referral date is today.
Referral order can be reviewed to ensure
4.6 System enables the documentation and tracking of referrals between care
Adequate detail includes but is not limited to: • Referral date
55
Procedure Expected Result
Actual Result Requirement met (!) Not met (")
Standard Reference General Notes for Reviewer
adequate detail is present: • Referral
date • Patient
name and identifier
• Name of referring provider
• Reason for referral
• Name of referred-to provider
providers or healthcare organizations. The following is captured for every referral: reason for referral, date, referring provider and referred-to provider.
• Patient name and identifier
• Name of referring provider
• Reason for referral • Name of referred-to
provider
18d Give Peninah a next appointment date to return in 2 weeks. Print out an appointment diary showing the patients expected on a particular day Logout clinician/Dr. Muguna
19d Login as a different clinician/Dr. Kariuki
Insert access control reference to test for shared privileges
20d Show active orders for Peninah Njoki Active orders 18.1 System supports
56
Procedure Expected Result
Actual Result Requirement met (!) Not met (")
Standard Reference General Notes for Reviewer
Kamau. for Peninah display: • Laborator
y orders; • Nutritionis
t referral; • Prescribe
d medication
the recording and tracking of clinical orders and requests such as prescriptions and other treatment orders, laboratory investigation requests, and referrals
21d Review her expected date of delivery (EDD). Start a new encounter/visit episode for Peninah Njoki Kamau. Enter her vital signs:
d BP 130/80 d Height 136cms d Weight 65kgs d Temperature 37o C d Pulse 80 beats/min d Respiratory Rate 16
breaths/min Enter her general and obstetric examination findings:
d Fundal height 32 weeks.
EDD automatically calculated given the LMP. Vital signs and examination findings captured. Examination findings entered Gastritis
4.4 System has the capability to capture vital signs. At minimum height, weight, pulse rate, respiratory rate, BP, BMI, MUAC for children 4.5 System has the capability to capture and edit health data regarding the patient’s current health status, including (as applicable): chief complaint, onset and duration of symptoms,
57
Procedure Expected Result
Actual Result Requirement met (!) Not met (")
Standard Reference General Notes for Reviewer
d Fetal heart rate 140/min d Mild tenderness at the
epigastrium. Enter her chief complaint for today as ‘Epigastric pains’. Diagnosis is ‘Gastritis’
added to problem list Ask to generate a problem list that should now include gastritis
examination findings, diagnosis, planned/performed lab procedure, medications prescribed, patient education, non-prescriptions such as exercise and diet, follow up plans, including dates of next visit. 17.3 System records fetal heart rate, fundal height, weight, urine analysis and blood pressure at each visit, along with antenatal profile results. 17.5 System displays the Estimated Date of Delivery (EDD) given the patients last menstrual period (LMP)
22d Demonstrate how the system maintains clinical practice guidelines
Clinical guidelines demonstrated with ability to
6.1 System includes and maintains evidence-based clinical guidelines published
58
Procedure Expected Result
Actual Result Requirement met (!) Not met (")
Standard Reference General Notes for Reviewer
revise and demonstrate changes
and maintained by credible sources such as MoH, NASCOP, Malaria and TB program. The guidelines incorporate alerts and reminders. 6.3 System has the capability to allow revision of clinical practice guidelines.
23d Generate a report of all HIV positive pregnant women not on ART or prophylaxis OR Demonstrate an alert reminding the provider that Peninah should be receiving some prophylaxis.
Peninah identified as HIV +ve and listed as not receiving prophylaxis or ART
12.5 System triggers alerts to providers when individual data indicates that interventions may be required
The alerts may be in a report form or an on-screen alert indicating that the patient should be on some prophylaxis according to clinical guidelines.
24d Enter laboratory results for Peninah for the orders previously made. The results are as follows: CD4 count – 280 cells/mm3 Hemoglobin – 12.6 g/dl VDRL – Negative
Laboratory results accepted as discrete elements. System alerts the user that
9.2 System is capable of receiving test results from laboratory. 9.5 System uses visual cues to highlight abnormal results
The implementation of range checks may differ from system to system. Some may provide real time alerts while others will print outlying laboratory
59
Procedure Expected Result
Actual Result Requirement met (!) Not met (")
Standard Reference General Notes for Reviewer
Blood group O Rhesus Positive ALT – 120 IU/L Creatinine – 70 umol/l Demonstrate how the system alerts the user to the abnormal ALT results. Append a comment to the CD4 count: “Result below normal CD4 range. Client for ART initiation”
the ALT level is above normal range. OR User is able to print a report of laboratory reports outside the normal range System alerts the user that Peninah is eligible for ART based on national treatment guidelines for HIV (CD4 cut-off of 350) OR User is able to generate a
6.1 System includes and maintains evidence based Clinical Guidelines. 6.2 System includes decision support prompts to support clinical guidelines and protocols. 12.4 System identifies trends that may lead to significant problems and provides prompts e.g. worsening laboratory results 9.6 System allows the provider/data entry personnel to comment on received results lab
values in a report. The units in which the laboratory results are reported may differ from system to system. E.g. hemoglobin may be reported as mg/dl, and creatinine as mg/dl.
60
Procedure Expected Result
Actual Result Requirement met (!) Not met (")
Standard Reference General Notes for Reviewer
report of patients eligible for ART but not on ART
results.
25d Initiate Peninah on anti-retroviral treatment (eligible by CD4 counts) on the ART regimen indicated below: The following information must be captured on initiation:
d Date eligible for treatment d Eligible through d Date started on treatment d Cohort group (may be
automatically calculated) d Weight and Height at start of
treatment d WHO dx staging d Regiment started
Prescribed ART regimen: d Zidovudine (AZT) 600mg/twice
daily/for 2 weeks d Lamuvidine(3TC) 150mg/twice
daily/for 2 weeks d Efavirenz(EFV) 600mg/every
night/for 2 weeks
Initiation details are entered as per the Minimum Dataset. Prescription drug options provided for selection. Check for drug coding system. Systems alerts the user as to the use of Efavirenz in pregnancy.
10.1 System creates prescription orders with detail adequate for correct filling and administration, and captures the identity of the prescriber. At minimum, system should capture: name of drug, the dose and frequency of administration. 10.3 System presents the user with a list of medications to be administered 10.5 System provides the capability to select the drug from pull down
61
Procedure Expected Result
Actual Result Requirement met (!) Not met (")
Standard Reference General Notes for Reviewer
The user should override this alert and document a reason for the override. Prescription information captured with, at minimum, date, drug, dosage and route prescribed and identity of prescriber.
menus. 18.1 System supports the recording and tracking of clinical orders and requests such as! prescription orders.
26d Retrieve and review (display or print) a current medication listing for Peninah.
Current medication list shows: d AZT d 3TC d EFV d Aldomet d Rifampicin
10.6 System has the capability of creating and maintaining a current medication list for each patient
62
Procedure Expected Result
Actual Result Requirement met (!) Not met (")
Standard Reference General Notes for Reviewer
d Isoniazid 27d Show how drug interactions are
setup in the system. Change Peninah’s prescription information from Efavirenz to Nevirapine 200mg twice daily.
Applicant demonstrates process of setting up drug interactions. System alerts the user to the interaction between Nevirapine and Rifampicin.
10.4 System identifies drug interaction warnings at the point of medication ordering.
28d Demonstrate how adverse drug reactions are set up in the system Indicate that Peninah has developed a grade 1 reaction to efavirenz. Retrieve and display the adverse reaction list.
Adverse Drug Reaction entered into the system. System generates a list of adverse drug reactions for the patient.
10.6 System maintains patient-specific adverse reaction lists and allows on reporting from such lists.
63
Procedure Expected Result
Actual Result Requirement met (!) Not met (")
Standard Reference General Notes for Reviewer
29d Display all encounters for this patient. Filter encounters by: • date of service; and • provider.
Encounters display, and are first filtered by date of service and then filtered by provider. Note that this is two separate filters of the same information.
14.1 System supports chronic disease management by:
d Allowing patient tracking and follow-up
d Integrating all patient information within the system
d Providing a longitudinal view of patient medical history
d Providing access to patient treatments and outcomes
30d Create an electronic patient summary report for Peninah Njoki Kamau that shows: • Problem lists • Medication lists • Adverse reactions • Care history Show a print preview of this report, to demonstrate that hardcopy output can be generated.
An electronic patient summary report is generated. The report should display the patient encounters or
13.3 System creates and maintains patient-specific summary views and reports that include at minimum: problem list, medication list, treatment interruptions and restart dates, adverse drug reactions, care history, and
Any electronic file format is acceptable.
64
Procedure Expected Result
Actual Result Requirement met (!) Not met (")
Standard Reference General Notes for Reviewer
visits but does not need to include the notes from those visits. A print preview is also displayed.
missed appointments.
31d Does the system receive HL7 patient messaging? If so, demonstrate its functionality. (Patient record in HL7 format sample provided).
Standard interface for patient data demonstrated. Record the standard used e.g. HL7
4.3 System has the capability to receive clinical documentation and notes via a standard MOH HL7 interface.
HL7 interfaces will be assessed but will not be scored to allow for further development of this feature in systems.
32d Does the system generate and transmit electronic prescriptions? If yes, demonstrate this functionality
Standard interface demonstrated. Record the standard used e.g. HL7
10.7 System provides the capability of electronic transmission of prescription information to a selected pharmacy for dispensing
65
Procedure Expected Result
Actual Result Requirement met (!) Not met (")
Standard Reference General Notes for Reviewer
33d Does the system accept laboratory results via HL7 messaging? If yes, demonstrate this functionality.
Standard interface for lab results demonstrated. Record the standard used e.g. HL7, LOINC, SNOMED
9.3 Laboratory and radiology results are received via a standard MoH HL7 interface.
HL7 interfaces will be assessed but will not be scored to allow for further development of this feature in systems.
66
F. DATA VALIDATION
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$ $ M6:#$YR$)*$D06456%5.$W$E8'5#3'4#.$5)781#40$
K)($5)#.$0"#$./.0#1$"6453#$5606$&638#.$0"60$"6&#$7"64:#5$6=%8203/c$+>:>$5%6.0'7$(#':"0$'47%#6.#$)&#%$6$.")%0$2#%')5c$D)1#$./.0#1.$16/$"6&#$0"'.$'123#1#40#5$60$5606$#40%/$3#$645$.)1#$16/$5)$0"'.$%#0%).2#70'/$=/$%844'4:$.7%'20.$
Y*$ !"'%5$)%5#%$('33$2%)=6=3/$=#$&63'560'4:$=6.#5$)4$'45'760)%.A$#>:>$M,!J!A$)%$481=#%$)4$`-!$&#%.8.$#4%)33#5$'4$76%#$
$ $ $ M6:#$YR$)*$D06456%5.$W$E8'5#3'4#.$5)781#40$
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67
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68
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69
• 8).1%!
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Nurse: 1. Can access patient clinical
information 2. Can add a new patient’s
clinical information 3. Can edit patient’s
demographic data.
Receptionist: 1. Can register a patient 2. Denied access to
clinical details 3. Denied modification of
patients demographic details
Data Clerk: 1. Can access patient’s clinical
information 2. Can add new patient’s clinical
information
70
SYSTEM REVIEW SUMMARY $
FEATURE/DESCRIPTION References Check (!) if implemented REVIEWERS COMMENTS SCO
RE 1. SYSTEM DETAILS AND STANDARDS
Uses a standardized naming protocol e.g. ICD10 or
SNOMED
13d
Uses a standard drug coding / listing system 25d
Uses a standard lab test coding / listing system 15d User friendly system prompts and appropriate error messages with clear corrective action
Data verification and validation implemented 1f – 4f Customizable user interface (forms and fields) General section Built-in backup and restore feature 1c – 2c 2. BASIC DEMOGRAPHIC AND CLINICAL HEALTH
INFORMATION
Unique patient identification system 2d
Multiple Patient Identifiers Supported 2d
Supports patient search for patients using one or multiple
identifiers
3d, 4d
System captures defined Minimum Data Set 1d – 5d, 25d
Biometric, Bar Code support
Supports patient referral 17d
Records patient demographics 1d - 4d
Maintains up-to-date problem lists 13d, 14d
Maintains medication lists 20d, 26d
Maintains allergy lists 10d
Records vital signs 12d, 21d
Incorporates lab test results 24d
71
Generates Patient lists 8d
Patient Education Materials available 16d
Generates clinical summaries 30d
Provides a longitudinal view of a patient’s medical history 29d
Captures historical medical history / information 9d
Manages drug interactions 27d
Manages adverse drug reactions 28d
Implements persistent patient records allowing for rollback
in case of Deletion of Patient/Patient Records
Supports Appointment scheduling set up, update and
management
18d
3. CLINICAL DECISION SUPPORT
Incorporates clinical decision guidelines 22d
Generates alerts to support clinical decision 22d, 23d, 24d, 27d 4. ORDER ENTRY AND PRESCRIBING
Generates prescriptions orders 25d
Generates lab orders 15d 5. HEALTH INFORMATION AND REPORTING
Customizable Reports General section, 1g
Export/import of external reports 5g
Generates MoH required reports 2g
Generates Patient level reports 4g
Generates facility specific reports 3g 6. SECURITY AND CONFIDENTIALITY
Supports user authentication 1a, 2a
Encryption Matrix implemented for User Passwords 1a, 2a
Supports role based access control 1b – 18b
Audit trail / log supported 22b, 7g
72
Supports analysis of audit trails reports 7g
Automatic logoff implemented 19b
Manual and automated database back up 1c, 2c
Data Encryption within the Database General Section EXCHANGE OF ELECTRONIC INFORMATION
Exchanges clinical information and patient summaries 31d
Electronically transmits prescriptions 32d
Electronically transmits and receives laboratory orders
and results
33d
Electronically transmits aggregate information to DHIS2 6g
Supports HL7 messaging
Supports XML generation and messaging
Supports SDMX-HD
$$
73
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WHY SUBSTITUTE CODES
1-Toxicity/side effects; 2-Pregnancy 3-Risk of pregnancy 4-Due to new TB 5-New drug available 6-Drug out of stock 7-Other reasons(specify)
REASONS FOR SWITCH TO 2ND LINE REGIMEN ONLY
8. Clinical treatment failure 9. Immunologic failure 10. Virologic failure
75
Data Item Individual Visitation Details
Visit Details Date (a) 26 /2 /2011 13/3 /2011 / / / / / / / / / / / / / / / / / / / /
Type (b) ! ! ! ! ! ! ! ! ! ! !
Duration Since (in months)
Start ART (c)
Current Regimen (d)
Weight (kg) /Blood Pressure (e) 64kgs/120/80 66kgs/118/80 / / / / / / / / / /
Height (cm) (f) 136 136
BMI (g)
Pregnancy Status (h) 00167/11 00167/11
EDD (i) 7/ 9 /2011 7/ 9 /2011 / / / / / / / / / / / / / / / / / / / /
FP Status FP/No FP (j) NOFP NOFP
Method/Why (k) -
Tuberculosis Status
Status (l) No Signs No signs
TBRx # (m) - -
Potential Side Effects (n) - -
New OIs & Other Problems (o) - -
WHO Stage (p) 2 2
Cotrimoxazole Adherence (q) G
Dispensed (r) 960mgs OD 960mgs OD
INH dispensed (s) - -
Other Medications Dispensed (t) M/Vits M/Vits
ARV drugs
Adherence (u) - -
Why poor/fair (v) - -
Regm/Dose/Days (w) - AZT/3TC/NVP 2 wks
Laboratory Investigations Done
CD4 (# or %) (x) - 280
Hgb (y) - 12.6
RPR (z) - -ve
TB Sputum (aa) - -
Other (ab) - Alt – 22
Referral / Hospitalized (ac) IFC[ ] IFC[ ] [ ] [ ] [ ]
[ ] [ ] [ ] [ ]
At Risk Population [Place codes here] (ad)
PwP Services
Disclosure Partner tested (ae) ND 0 ND 0
Condoms Screened STI - X - X
Date of Next Appointment (af) 12/ 3 /2011 27/ 3 /2011 / / / / / / / / / / / / / / / / / / / /
Clinician Initials (ag) PO PO
76
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77
References 1. Constitution of Kenya, 2010 2. Kenya Vision 2030 3. Standards and Guidelines for EMR Systems in Kenya 4. Review of EMR Systems – Concept Paper