1. Data dissemination meeting February 28, 2007 ICAP New York

3. Summary of ICAP-supported activities through December, 2007 Care and treatment (cumulative) –236 of 258 sites reporting –Nearly 404,833 patients have been enrolled enrolled in care since 2004, 189,339 of whom initiated ART. TB screening in HIV patients (last quarter) –171 of 214 sites reporting –Of 24,484 newly enrolled patients, 65% were screened for TB at enrollment (compared with 61%, 54%, and 48% in the previous 3 quarters, respectively). PMTCT (last quarter) – 249 of 260 sites reporting –43,590 women attending ANC (first visit) were screened for HIV, 4,264 screened positive, and 2,761 received prophylaxis –5,007 PMTCT client partners were tested.

4. Today’s data dissemination meeting Routinely collected CD4-related indicator data –Data elements reported –Descriptive analysis –Example of in-depth CD4-related data quality assessment (TZ) Discussion Next data dissemination meeting –Topic: Characteristics of ICAP-supported care and treatment facilities and programs (PFACTS)

5. CD4 counts in patients In a patient: A measure of the degree of immunodeficiency Helps determine whether a patient –needs OI prophylaxis –should start ART –is responding to ART Patients should generally have CD4 counts at time of –enrollment into care and every 6 months thereafter –ART initiation and every 6 months thereafter

6. CD4 counts in programs Completeness of CD4 testing –Are patients being tested at the expected frequency and intervals? Median CD4 count at enrollment –Degree of immunodeficiency at enrollment into care Median CD4 count at ART initiation –Degree of immunodeficiency in the patient population at ART initiation Change in CD4 count over time –Degree to which patients who remain on ART are responding to therapy

7. Median CD4 count vs. time on ART

9. Cohorts of patients initiating ART CD4-related data elements captured on cohorts of patients who have been on ART for 6 and 12 months Aggregate by facility, no age/sex breakdown Only patients > 6 years of age, no CD4% data collected for children CD4 data on pre-ART patients not reported

10. Why CD4 cohort data? Need to follow groups of patients over time to assess CD4 response Patient-level databases do not exist at all sites Data sources include: Lab slips and/or lab information abstracted from patient registers, patient visit history forms, or patient-level databases.

11. Cohort enrollment and follow-up Patients initiated ART during Feb, Mar, Apr 2007 Reporting quarter Ex: Oct- Dec 2007 6 month cohort Patients initiated ART during Aug, Sep, Oct 2006 12 month cohort (6 month data reported in April-June 2007)

12. CD4-related data elements reported by ICAP care and treatment programs For each cohort of patients initiating ART: –Baseline No. in cohort No. with CD4 count Median CD4 count –6 months/ 12 months No. in cohort No. with CD4 count Median CD4 count No. on ART for 6/6 and 12/12months

13. Outcome measures CD4 completeness –Proportion of patients with baseline and follow-up CD4 counts Average median CD4 count at baseline, 6 and 12 months Change in average median CD4 count with time on ART

14. Analysis methods Stratified analysis by country Trends analysis Means weighted to account for difference in cohort size

15. Cohort data received to date 189,339 patients have initiated ART in 257 sites Baseline cohort data on 64,303 patients initiating ART –6-month cohort data on 61,158 patients 937 cohorts from 210 sites –12- month cohort data on 51,687 patients 707 cohorts from 190 sites Difficult to assess completeness of cohort reporting, but –has generally improved with time –varies substantially by country

16. Overall proportion of patients with CD4 count at baseline, 6, and 12 months after ART initiation, July 2004-December 2007 % patients with CD4 count n=64,303 Source: ICAP URS, January 2008 n=61,158n=51,687 Baseline 6-month 12-month6-month

17. Proportion of patients with CD4 count at baseline, 6, and 12 months after ART initiation, July 2004-December 2007 % patients with CD4 count

18. Distribution of baseline CD4 counts for 6 month cohorts as of December 2007

19. Distribution of 6 months follow up CD4 counts for 6 month cohorts as of December 2007

20. Distribution of 12 months follow up CD4 counts for 12 month cohorts as of December 2007

21. Average median CD4 count at baseline and 6 and 12 months after ART initiation, July 2004-December 2007

22. Change in Median CD4 count (cells/µL) at 6 and12 months of ART, July 2004-December 2007 Change in median CD4 count

23. Trends in completeness of CD4 evaluation and median baseline CD4 Cumulatively, completeness of CD4 evaluation at baseline is suboptimal and at 6 and 12 month follow up is very low  Are we getting better at it over time? Cumulatively, average median baseline CD4 was 133  Has this changed over time?

24. Completeness of CD4 evaluation at baseline for 6 month cohorts over time, July 2005-October 2007 Percent of patients with baseline CD4

25. Mozambique Percent of patients with baseline CD4

26. Rwanda Percent of patients with baseline CD4

27. Completeness of CD4 evaluation at 6 months follow up for 6 months cohorts over time, July 2005-October 2007 Percent of patients with 6 month CD4

28. Completeness of CD4 evaluation at 12 months follow up for 12 months cohorts over time, July 2005-October 2007 Percent of patients with 12 month CD4 P<0.05

29. Median CD4 counts at baseline for 6 month cohorts overtime, July 2005-October 2007 CD4 count

30. Ethiopia CD4 count

31. Completeness of CD4 evaluation at baseline for 6 month cohorts over time in Tanzania, July 2005- October 2007 Percent of patients with baseline CD4

32. Example: Why is CD4 completeness low in ICAP Tanzania sites ? Tanzania reported a low proportion (~50%) of patients in ART cohorts with documented baseline and follow-up cd4 counts Unclear whether problem is: –Documentation –Logistics (e.g., reagent shortages or lack of equipment) –Tests not being ordered Data quality assurance (DQA) exercises done at 3 sites in Tanzania, November 2007 to determine source of problem

33. Tanzania (methods) Randomly sampled 20% of all files at care and treatment clinic (CTC) Counted and cross-checked total number of CD4 results in –Lab register –Patient medical file –Visit history cards –Care and treatment database

34. Receptionist/ Nurse (ctc) Patient visits Clinic Physician Laboratory Data Entry Clerk Lab technician Patient flow Flow of patient data Database lab results Lab request form Lab request form/ specimen labels Patient file Flow of patients and patient information to, from and within the care and treatment clinic (CTC) Patient file START END

35. Lab Register Patient file Visit history Card Database 171/181 94% Proportion of CD4 tests documented by data source – Nyakahanga, Tanzania 147/181 81% 90/181 49% 181/181 100% 130 patients146 patients132 patients85 patients

36. CD4 machine available on- site Reagents Shortage Reagents available Number of electronic cd4 data entry and number of new enrollees by quarter – Nyakahanga

37. Conclusions Problems stem from inefficient and inconsistent data flow, personnel shortages, and M&E activity given low priority Lab Database/ Register Patient File Patient Visit Card Database Laboratories should adapt standard registers and/or databases -These should serve as the primary source of transcription to other sources

38. Rwanda National ART program evaluation Nationally representative sample of 3,194 adult ART patients Median baseline CD4=142 –All ICAP: 133 –ICAP-RW: 187 Percent with CD4 at baseline: >90% –All ICAP: 80% –ICAP RW: 93% % with CD4 at 6 months: 49% –All ICAP: 45% –ICAP RW: 61% % with CD4 at 12 months: 35% –All ICAP: 46% –ICAP RW: 48%

39. Take home messages from routine data Many patients in ICAP-supported programs have been on ART for 6 and 12 months –91,000 person-years of ART experience as of Sep 2007 Completeness of cohort reporting needs further assessment (and likely further improvement) Patients appear to be initiating ART earlier in many settings (role of entry points and increasing coverage?) CD4 completeness of follow-up CD4 count data is a serious problem –Not an isolated problem (e.g., Rwanda) –Reasons are likely related to both documentation problems and service delivery gaps –Ignoring completeness problem, responses seem to be good –Potential for bias Sub analysis Variation in CD4-related outcomes between countries and sites

40. Discussion