ICAP Quarterly Data Dissemination Meeting

September 25, 2009

Data Dissemination MeetingWelcome

Ideas for future Data Dissemination MeetingsPlease email Suzue Saito: ss1117@columbia.edu

2nd quarter data (April-June 2009) available on URS872 of 904 facilities reporting (96%)

Excluding Swaziland sitesCare and treatment: 47,950 newly enrolled patients and 25,353 newly

initiating ART (cumulative 327,092)PFaCTS Round 4 nearly completed

PMTCT: 118,259 women tested and received resultsTB screening: 13,746 new HIV patients screened fpr TB

Counseling and testing: 239,592 clients, plus 10,141 TB patientsMore details in forthcoming eUpdate, URS, data dissemination page

We want your data slides (icap-data-slides@socialtext.net)

Data Dissemination MeetingMatthew Lamb, Maria Lahuerta & Denis Nash

ICAP-MER NY Sept 25th, 2009

Patient-level data

Monitoring

EvaluationResearch

An orientation to monitoring, evaluation,

and research using routinely-collected care and treatment patient-

level data

1) Intro to care and treatment patient-level data available at ICAP sites

2) Routine program evaluation and dissemination• Country reports, site reports and SOC reports

3) Operations ResearchTheoretical framework: Identifying Optimal Models of HIV care

• Examples4) Strengths and Limitations

Outline

1) Intro to care and treatment patient-level data available at ICAP sites

2) Routine program evaluation and dissemination• Country reports, site reports and SOC reports

3) Operations ResearchTheoretical framework: Identifying Optimal Models of HIV care

• Examples4) Strengths and Limitations

Outline

Routinely-collected care & treatment data

Program/site-level characteristics

Patient-level data

Aggregate indicators

Routine M&E Operations Research

Common-structure patient-level database for sites with electronic patient-level data

Simplifies the development of automated quarterly feedback reports

Enable comparison across sites and countries

ICAP patient-level data warehouse

ICAP common patient-level data warehouse

Common patient-level data

warehouse

MZ

KY

TZ

RW

SA

CDI MTCT+

Current

Coming soon

Closed

Not sharing

Not available

ET

SW

LT

NI

Patient-level data flow, security, and confidentiality

Site-level electronic data entry intocounty-specific database

Regional/Country Aggregation of site databases

Password protectionRoutine backup

Transfer to ICAP-NY

Conversion to common data warehouse format

Site reports

Country reports

SOC reports

Anonymization & Merge Tool

Password protectionencryption

Routine backupStorage of archival dataRestricted access

Analysis file for research

ICAP patient-level data warehouse elements

Enrollment Table• Basic

demographic information • Age• Sex• enrollment

date• Prior ARV use• Point of entry• Transfer

Visit Table: Visit date, WHO stage, height, weight, Hb, ALT, nextscheduled visit date

CD4 Table: CD4 test date, CD4 count, CD4 percent

ART Table: ART regimen, regimen start & end date,reason(s) for switching ART regimen

Medication Table: TB screening date and result, TB medicationreason (treatment or prophylaxis) and dates, CTX & fluconazole

Status Table: Patient disposition status (dead, transferred, withdrew, LTF, stopped ART, etc) and status date

Pregnancy Table: Visit date, weeks gestation at visit, due date, actual pregnancy end date

Baseline: 1 rowPer patient Follow-up data: 1 row per measure per patient

*measures at key points of interest (e.g., enrollment, ART initiation) calculated based on visit dates

ICAP patient-level database through June 2009

COUNTRYSites w/

electronic DB (% over

total)

Sites submitting

data to ICAP-MER NY

Cum # patients enrolled in Care

(% pediatric)

Cum # patients on ART

(% pediatric)

Kenya 6 (5%) 6 22,826 (11.4%) 12,815 (12.0%)

Ethiopia 44 (94%) 0 - -

Mozambique 27 (51%) 27 135,873 (6.6%) 45,160 (6.5%)

Rwanda 32 (64%) 32 33,228 (10.2%) 18,142 (10.5%)

South Africa 3 (7%) 3 5,726 (0.9%) 3,780 (0.3%)

Tanzania 20 (21%) 16 22,094 (7.2%) 10,751 (7.3%)

Cote d’Ivoire 13 (38%) 0 - -

Swaziland 9 (50%) 0 - -

MTCT-Plus* NA 14 10,161 (6%) 5,203 (8%)

TOTAL 154 (33%) 98 229,908 (9.8%) 95,851 (7.9%)

Enrollment into Care (N = 229,908)

Age and Sex distribution through June 2009, 98 sites

1) Intro to care and treatment patient-level data available at ICAP sites

2) Routine program evaluation and dissemination• Country reports, site reports and SOC reports

3) Operations ResearchTheoretical framework: Identifying Optimal Models of HIV care

• Examples4) Strengths and Limitations

Outline

• Overall picture of country programs• Provides between-site comparisons• Separate for adults and pediatric patients

Country reports

Country reports Adult patientsMozambique

Country reportsFigure 4.2 - Median (25th – 75th percentile) CD4 count at ART initiation:

adult patients initiating ART in the last year

Adult patientsMozambique

Country reports Adult patientsMozambique

The overall percentage is represented by a horizontal line

Figure 4.7 Proportion of patients receiving tuberculosis treatment at ART initiation among adult patients initiating ART in the last year

• Provide in-depth, site-specific feedback for program improvement to ICAP staff, as well as site and district staff

• Describe patient characteristics at enrollment and at ART initiation and patient outcomes

Site reports

Totaln (%)

Adultsn (%)

Childrenn (%)

Total 3075 (100) 2770 (100) 305 (100)Median (IQR) CD4 count at ART initiationa (≥5 years old) 154 (80-210) 151 (78-203) 361 (198-540) <50 cells/µL 252 (8.8) 245 (8.8) 7 (6.7) 50-99 281 (9.8) 272 (9.8) 9 (8.6) 100-199 676 (23.5) 668 (24.1) 8 (7.6) 200-349 375 (13) 356 (12.9) 19 (18.1) 350+ 115 (4) 67 (2.4) 48 (45.7) Missing 1175 (40.9) 1161 (41.9) 14 (13.3)WHO clinical stage at ART initiationa WHO Stage I 473 (15.4) 447 (16.1) 26 (8.5) WHO Stage II 322 (10.5) 251 (9.1) 71 (23.3) WHO Stage III 747 (24.3) 676 (24.4) 71 (23.3) WHO Stage IV 215 (7) 197 (7.1) 18 (5.9) Missing 1318 (42.9) 1199 (43.3) 119 (39)Clinical eligibility for ARTb at enrollment Eligible Ineligible

1465 (47.6) 1329 (48) 136 (44.6)746 (24.3) 659 (23.8) 87 (28.5)

Unknown 864 (28.1) 782 (28.2) 82 (26.9)Clinical eligibility for ARTb at ART initiation Eligible 1569 (51) 1403 (50.6) 166 (54.4) Ineligible 554 (18) 467 (16.9) 87 (28.5) Unknown 952 (31) 900 (32.5) 52 (17)

Table 3.2 Measures of immunodeficiency status at ART initiation: active patients currently on ART

Jose Macamo General Hospital

Mozambique

a: window period three months prior and one month postb: according to WHO guidelines

Site reports

Figure 3.4 Weight-for-age z-score at ART initiation: active children1 < 15 yrs currently on ART (CDC standard)

Weight-for-age missing: 22Weight-for-age out of range (z-score <-10 or >10): 10

Moderately or severely malnourished (z-score < -2): 87 (31.9%)Severely malnourished (z-score < -3): 44 (16.1%)

Jose Macamo General Hospital

MozambiqueSite reports

Figure 4.3 Two-year Kaplan-Meier curves of known death, loss to follow-up, and loss to program among ART patients since ART initiation

Jose Macamo General Hospital

Mozambique

Time (years) since ART initiation

At riskSurvivedNot LTF

Retained

Site reports

• Use patient-level data to calculate SOCs• Useful to identify site-level areas in need of

improvement• All patients as opposed to a sample of patients• Easily assess trends

ICAP Standards of Care (SOC) reports

ICAP Standards of Care (SOC) reports

Activity during the specified quartersCurrent quarter

Jan-Mar 2009

Previous quarter

Oct-Dec 2008

Two quarters ago

Jul-Sep 2008n (%) n (%) n (%)

Patients newly initiating ART 71 57 60On treatment within 1 month of known eligibility 16 (22.5) 13 (22.8) 19 (31.7)CD4 test within one month of ART initiation 37 (52.1) 36 (63.2) 38 (63.3)

WHO stage at ART initiation 3 (4.2) 11 (19.3) 11 (18.3)Weight at ART initiation 70 (98.6) 54 (94.7) 59 (98.3)At least one recorded height measurement 0 (0) 0 (0) 0 (0)Screened for TB at ART initiation 0 (0) 0 (0) 0 (0)Children <15 years newly initiating ART 3 (4.2) 3 (5.3) 2 (3.3)

Where to find the reports

1) Intro to care and treatment patient-level data available at ICAP sites

2) Routine program evaluation and dissemination• Country reports, site reports and SOC reports

3) Operations ResearchTheoretical framework: Identifying Optimal Models of HIV care

• Examples4) Strengths and Limitations

Outline

What is Operations Research?

“Operations research is being defined broadly and includes the use of analytical techniques to achieve better health outcomes, define optimal

processes of service delivery, and develop more cost-effective systems. It encompasses a wide range of studies, including observational and

outcomes studies, epidemiological modeling, and cost-effectiveness studies.”

From the Doris Duke Charitable Foundation, ORACTA program

Identifying Optimal Models of HIV Care

Contextual

Program/site-level

Patient-level

•Background HIV+ prevalence•Urban/peri-urban/rural

•National guidelines•Social norms, stigma, etc

•Facility type & size•Services offered

•Staffing characteristics•Monitoring frequency

•CD4/WHO stage•Baseline comorbidity

•Demographics•Point of entry

DHS data,Census data, etc

PFaCTS

Patient-level data

Identifying Optimal Models of HIV Care

Goals: 1. Assess the variation in key HIV care and

treatment outcomes within & across sites and countries• CD4/WHO stage at enrollment & ART initiation• Non-retention, loss to follow-up, and death• Treatment failure and regimen switching

2. Identify factors at multiple levels associated with patient & program outcomes, with a particular focus on program-level factors

Factors associated with Late ART initiationExample 1

No ad-vanced HIV

disease48%WHO Stage

IV36%

CD4 < 100

cells/µL64%

Definition of advanced HIV disease at ART initiation (late ART initiation)

•CD4 count <100 cells/µL or

•WHO Stage IV

A B C D E F G H I J K L M N O P Q R S T0%

10%

20%

30%

40%

50%

60%

70%Overall

proportion52%

Fig 1. Distribution of HIV disease status at ART initiation for the 24,273 eligible patients

Fig 2. Variability of the proportion late ART initiators by site

Example 2 Retention of ART patients

Two year LTF and known deaths among ART patients

Overall LTF 29%

A B C D E f G H I J K L M N O P Q R S0%

10%

20%

30%

40%

50% 47%

42%39% 39%

35% 35%

28%26% 26% 26% 25% 24% 24% 23%

19% 19% 18%

13%12%

0%

7%10%

6% 4%

12%

8%

2%5%

2%

10%7%

2% 3%

8%5%

7%4%

10%

% LTF at 24 months % Reported deaths at 24 months

Sites

Perc

enta

ge

Overall death

5%

1) Intro to care and treatment patient-level data available at ICAP sites

2) Routine program evaluation and dissemination• Country reports, site reports and SOC reports

3) Operations ResearchTheoretical framework: Identifying Optimal Models of HIV care

• Examples4) Strengths and Limitations

Outline

Uses of common patient-level data warehouse

M&E

Quality of CareResearch

Data Quality

Strengths

• Service delivery data from scale-up programs• Multiple countries and contexts• Adults and pediatrics• Longitudinal

– Retrospective to program start• Data from pre-ART phase of care• Variety of exposures and outcomes• Ability to examine impact of interventions,

changes in guidelines, etc.• Large sample size

Limitations

• Missing data (completeness)– Incomplete data entry– Incomplete documentation– Incomplete care

• Inaccurate data– Single data entry

• High rates of loss to follow-up– A mixed bag of unascertained deaths, transfers, and

drop outs– Precludes meaningful examination of survival as an

outcome

Figure 4.3 Two-year Kaplan-Meier curves of known death, loss to follow-up, and loss to program among ART patients since ART initiation

Jose Macamo General Hospital

Mozambique

Time (years) since ART initiation

At riskSurvivedNot LTF

Retained

Gatundu District HospitalKenya (intensive defaulter tracing)

Conclusions

• Over 154 of 510 (30%) ICAP-supported care and treatment sites have patient-level databases– 84 sites in 5 countries (17%) are submitting data to ICAP-NY on

a quarterly basis. Warehouse includes:• 229,908 of 754,086 pre-ART patients represented: 30%• 95,851 of 367,179 ART patients: 26%

– Data quality and completeness will be an ongoing challenge• Timely routine feedback/dissemination process in place

– Program evaluation– Program improvement

• SOC report

– Will help shed light on and address data quality issues• Platform for multi-country operations research in place

(Optimal Models protocols)

Future directions

• Feedback and dissemination, utilization, analysis• Need to understand more about reasons for

missing data for key variables, and how to impact it– Improving with time for some variables (e.g. CD4 at

ART initiation) and not others (e.g. height)• Improve ability to examine survival as an

outcome

Acknowledgements• Ashraf Fawzy, Caroline Korves• Senior M&E Advisors and teams

– Muhsin Sheriff– Veronicah Mugisha, Emmanuel Manzi– Maria Fernanda-Alvim, Matt Rosenthal, Carla Xavier– Molly Strachan, Harriet Nuwagaba-Biribonwoha– Kanchan Reed

• Ruby Fayorsey, Stephen Arpadi and Rosalind Carter (peds reports)

• ICAP NY M&E team (MER Liaisons)• ICAP Clinical Unit• ICAP Clinical Advisers