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ICAP Quarterly Data Dissemination Meeting

ICAP Quarterly Data Dissemination Meeting. September 25, 2009. Data Dissemination Meeting. Welcome Ideas for future Data Dissemination Meetings Please email Suzue Saito: ss1117@columbia.edu 2 nd quarter data (April-June 2009) available on URS 872 of 904 facilities reporting (96%)

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ICAP Quarterly Data Dissemination Meeting

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  1. ICAP Quarterly Data Dissemination Meeting September 25, 2009

  2. Data Dissemination Meeting • Welcome • Ideas for future Data Dissemination Meetings • Please email Suzue Saito: ss1117@columbia.edu • 2nd quarter data (April-June 2009) available on URS • 872 of 904 facilities reporting (96%) • Excluding Swaziland sites • Care 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 results • TB screening: 13,746 new HIV patients screened fpr TB • Counseling and testing: 239,592 clients, plus 10,141 TB patients • More details in forthcoming eUpdate, URS, data dissemination page • We want your data slides (icap-data-slides@socialtext.net)

  3. An orientation to monitoring, evaluation, and research using routinely-collected care and treatment patient-level data Data Dissemination MeetingMatthew Lamb, Maria Lahuerta & Denis NashICAP-MER NY Sept 25th, 2009

  4. Outline • Intro to care and treatment patient-level data available at ICAP sites • Routine program evaluation and dissemination • Country reports, site reports and SOC reports • Operations Research • Theoretical framework: Identifying Optimal Models of HIV care • Examples 4) Strengths and Limitations

  5. Outline • Intro to care and treatment patient-level data available at ICAP sites • Routine program evaluation and dissemination • Country reports, site reports and SOC reports • Operations Research • Theoretical framework: Identifying Optimal Models of HIV care • Examples 4) Strengths and Limitations

  6. Routinely-collected care & treatment data Program/site-level characteristics Aggregate indicators Patient-level data Operations Research Routine M&E

  7. ICAPpatient-level data warehouse • 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

  8. ET • SW • LT • NI ICAP common patient-level data warehouse Current Coming soon Closed Not sharing Not available

  9. Patient-level data flow, security, and confidentiality Password protection Routine backup Site-level electronic data entry into county-specific database • Regional/Country Aggregation of site • databases Anonymization & Merge Tool • Transfer to ICAP-NY Password protection encryption • Conversion to common data warehouse • format Routine backup Storage of archival data Restricted access • Country • reports Analysis file for research • SOC reports • Site • reports

  10. 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, next scheduled 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 medication reason (treatment or prophylaxis) and dates, CTX & fluconazole Pregnancy Table: Visit date, weeks gestation at visit, due date, actual pregnancy end date Status Table: Patient disposition status (dead, transferred, withdrew, LTF, stopped ART, etc) and status date Follow-up data: 1 row per measure per patient Baseline: 1 row Per patient *measures at key points of interest (e.g., enrollment, ART initiation) calculated based on visit dates

  11. ICAPpatient-level database through June 2009

  12. Age and Sex distribution through June 2009, 98 sites Enrollment into Care (N = 229,908)

  13. Outline • Intro to care and treatment patient-level data available at ICAP sites • Routine program evaluation and dissemination • Country reports, site reports and SOC reports • Operations Research • Theoretical framework: Identifying Optimal Models of HIV care • Examples 4) Strengths and Limitations

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

  15. Country reports Adult patients Mozambique

  16. Country reports Adult patients Mozambique Figure 4.2 - Median (25th – 75th percentile) CD4 count at ART initiation: adult patients initiating ART in the last year

  17. Country reports Adult patients Mozambique Figure 4.7 Proportion of patients receiving tuberculosis treatment at ART initiation among adult patients initiating ART in the last year The overall percentage is represented by a horizontal line

  18. Site reports • 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

  19. Site reports Jose Macamo General Hospital Mozambique Table 3.2 Measures of immunodeficiency status at ART initiation: active patients currently on ART a: window period three months prior and one month post b: according to WHO guidelines

  20. Site reports Jose Macamo General Hospital Mozambique Figure 3.4 Weight-for-age z-score at ART initiation: active children1 < 15 yrs currently on ART (CDC standard) Weight-for-age missing: 22 Weight-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%)

  21. Site reports Jose Macamo General Hospital Mozambique Figure 4.3 Two-year Kaplan-Meier curves of known death, loss to follow-up, and loss to programamong ART patients since ART initiation At risk Survived Not LTF Retained Time (years) since ART initiation

  22. ICAP Standards of Care (SOC) 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

  23. ICAP Standards of Care (SOC) reports

  24. Where to find the reports

  25. Outline • Intro to care and treatment patient-level data available at ICAP sites • Routine program evaluation and dissemination • Country reports, site reports and SOC reports • Operations Research • Theoretical framework: Identifying Optimal Models of HIV care • Examples 4) Strengths and Limitations

  26. 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

  27. IdentifyingOptimal Models of HIV Care Contextual DHS data, Census data, etc Program/site-level PFaCTS Patient-level Patient-level data

  28. Identifying Optimal Models of HIV Care • Goals: • 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 • Identify factors at multiple levels associated with patient & program outcomes, with a particular focus on program-level factors

  29. Example 1 Fig 1. Distribution of HIV disease status at ART initiation for the 24,273 eligible patients • Definition of advanced HIV disease at ART initiation (late ART initiation) • CD4 count <100 cells/µL • or • WHO Stage IV Fig 2. Variability of the proportion late ART initiators by site Overall proportion 52% Factors associated with Late ART initiation

  30. Example 2 Retention of ART patients • Two year LTF and known deaths among ART patients Overall LTF29% Overall death 5%

  31. Outline • Intro to care and treatment patient-level data available at ICAP sites • Routine program evaluation and dissemination • Country reports, site reports and SOC reports • Operations Research • Theoretical framework: Identifying Optimal Models of HIV care • Examples 4) Strengths and Limitations

  32. Uses of common patient-level data warehouse Data Quality

  33. 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

  34. 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

  35. Jose Macamo General Hospital Mozambique Figure 4.3 Two-year Kaplan-Meier curves of known death, loss to follow-up, and loss to programamong ART patients since ART initiation At risk Survived Not LTF Retained Time (years) since ART initiation

  36. Gatundu District Hospital Kenya (intensive defaulter tracing)

  37. 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)

  38. 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

  39. Acknowledgements • Ashraf Fawzy, Caroline Korves • Senior M&E Advisors and teams • Muhsin Sheriff • VeronicahMugisha, 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

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