Evaluating the flow of adults in public HIV care systems in Mozambique: Identifying obstacles to care XVII International AIDS Conference August 5, 2008 MA Micek, AJ Baptista, J Ferro, A Melo, K Gimbel-Sherr, S Gimbel-Sherr, E Matediana, W Johnson, P Montoya, J Pfeiffer, S Gloyd Mozambique Ministry of Health Health Alliance International University of Washington

ART expansion in Mozambique National HIV prevalence 2007 (15-49yrs) = 16% National HIV prevalence 2007 (15-49yrs) = 16% Free ART in public clinics since June 2004 (through Ministry of Health) Free ART in public clinics since June 2004 (through Ministry of Health) 88,211 patients on ART by Dec ,211 patients on ART by Dec % of those with advanced HIV infection 28.0% of those with advanced HIV infection 91% of goal 91% of goal Source: Mozambique National AIDS Council, Mozambique Progress Report for the UN General Assembly Special Session on HIV and AIDS, January, 2008

Objective Evaluate flow of adults >15yrs of age through 2 HIV care systems in central Mozambique Evaluate flow of adults >15yrs of age through 2 HIV care systems in central Mozambique Define key steps to identify and treat HIV- positive people Define key steps to identify and treat HIV- positive people Measure drop-offs at each step Measure drop-offs at each step Determine steps where most people are “lost” Determine steps where most people are “lost”  Results used to prioritize strategies to improve flow through the system

Methodology Setting: 2 public HIV care systems in Setting: 2 public HIV care systems in central Mozambique Beira (Sofala) = pop. ~430,000, HIV prev. 29% Beira (Sofala) = pop. ~430,000, HIV prev. 29% Chimoio (Manica) = pop. ~240,000, HIV prev. 25% Chimoio (Manica) = pop. ~240,000, HIV prev. 25% Both with one major public ART clinic Both with one major public ART clinic Sample: people tested for HIV from July 1, 2004 – June 30, 2005 Sample: people tested for HIV from July 1, 2004 – June 30, 2005 Data: routinely collected Data: routinely collected HIV testing (anonymous paper and computerized registers) HIV testing (anonymous paper and computerized registers) ART clinics (computerized database) ART clinics (computerized database)

Steps to identify and treat people with HIV: The HIV treatment cascade

Definitions Step 1: HIV testing Step 1: HIV testing Number tested per HIV testing facility (VCT, youth-VCT, women at pMTCT) Number tested per HIV testing facility (VCT, youth-VCT, women at pMTCT) Step 2: Arrive at ART clinic Step 2: Arrive at ART clinic Number enrolled <30 days after test / number tested positive Number enrolled <30 days after test / number tested positive Step 3: CD4 testing Step 3: CD4 testing Number with CD4 <30 days after enrollment / number enrolled Number with CD4 <30 days after enrollment / number enrolled Step 4: Start ART (if eligible) Step 4: Start ART (if eligible) Number starting ART <90 days after CD4 testing / number ART eligible Number starting ART <90 days after CD4 testing / number ART eligible Step 5: Adhere to ART Step 5: Adhere to ART Number with pharmacy-based adherence >90% 180 days post-ART / number remaining on ART 180 days post-ART Number with pharmacy-based adherence >90% 180 days post-ART / number remaining on ART 180 days post-ART

Results: Step 1 HIV Testing Estimated 23,430 adults tested for HIV Estimated 23,430 adults tested for HIV 5,211 (VCT); 1,539 (pMTCT); 255 (youth- VCT) 5,211 (VCT); 1,539 (pMTCT); 255 (youth- VCT) 7,005 (30%) HIV-positive 7,005 (30%) HIV-positive Seropositivity rates highest in VCT (45%) vs. pMTCT (16%, X 2 p<.001) and youth-VCT (14%, X 2 p<.001) Seropositivity rates highest in VCT (45%) vs. pMTCT (16%, X 2 p<.001) and youth-VCT (14%, X 2 p<.001)

Results: Step 2 Arrive at ART Clinic 3,956 of 7,005 (56%) enrolled at ART clinic <30 days after HIV test 3,956 of 7,005 (56%) enrolled at ART clinic <30 days after HIV test Highest in VCT (67%) vs. pMTCT (26%, X 2 p<.001) and youth-VCT (24%, X 2 p<.001) Highest in VCT (67%) vs. pMTCT (26%, X 2 p<.001) and youth-VCT (24%, X 2 p<.001) Chimoio (62%) > Beira (53%, X 2 p Beira (53%, X 2 p<.001)

Results: Step 3 CD4 testing 3,046 of 3,949 (77%) had CD4 test <30 days after enrolling at ART clinic 3,046 of 3,949 (77%) had CD4 test <30 days after enrolling at ART clinic No differences between testing sites (VCT 77%, pMTCT 75%, youth-VCT 73%) No differences between testing sites (VCT 77%, pMTCT 75%, youth-VCT 73%) Beira (82%) > Chimoio (70%, X 2 p Chimoio (70%, X 2 p<.001) Rate in Chimoio increased over time (X 2 test for trend p<.001) Rate in Chimoio increased over time (X 2 test for trend p<.001)

Results: Step 4 Starting ART 1,506 of 3,046 (49%) eligible for ART 1,506 of 3,046 (49%) eligible for ART 735 (24%) unclassifiable because missing WHO clinical stage information in database 735 (24%) unclassifiable because missing WHO clinical stage information in database 471 (31%) started ART <90 days after CD4 testing 471 (31%) started ART <90 days after CD4 testing Lowest among pMTCT (20%) vs. VCT (32%, X 2 p=.01) and youth-VCT (40%, X 2 p=.10) Lowest among pMTCT (20%) vs. VCT (32%, X 2 p=.01) and youth-VCT (40%, X 2 p=.10) Chimoio (36%) > Beira (28%, X 2 p=.001) Chimoio (36%) > Beira (28%, X 2 p=.001)

Results: Step 5 Adhere to ART 382 of 471 (81%) continued on ART >180 days at ART clinic 382 of 471 (81%) continued on ART >180 days at ART clinic Reasons for loss: death (n=75), transfer (n=13), suspension (n=1) Reasons for loss: death (n=75), transfer (n=13), suspension (n=1) 317 (83%) with adherence >90% at 180 days post-ART 317 (83%) with adherence >90% at 180 days post-ART No significant differences between cities, HIV testing sites No significant differences between cities, HIV testing sites

Results: Overall HIV treatment cascade

Step 2: Drop-off 44% 3,049 lost Step 4: Drop-off 69% 1,035 lost

Results: Major bottlenecks Number of additional people completing all 5 steps if drop-offs individually improved Number of additional people completing all 5 steps if drop-offs individually improved

Limitations Used only routine data Used only routine data Susceptible to poor data quality Susceptible to poor data quality Unable to determine whether people sought care outside evaluated care system Unable to determine whether people sought care outside evaluated care system Only evaluated vertical HIV care system Only evaluated vertical HIV care system Focused only on one aspect of HIV care Focused only on one aspect of HIV care Other analyses needed to evaluate pediatric care, quality of care, HIV prevention, psychosocial care, etc. Other analyses needed to evaluate pediatric care, quality of care, HIV prevention, psychosocial care, etc.

Conclusions (1) Evaluation of flow in HIV care systems is feasible and important in resource-limited settings Evaluation of flow in HIV care systems is feasible and important in resource-limited settings Use of routine data allows periodic assessment Use of routine data allows periodic assessment Can be adapted to local workflow models and data systems Can be adapted to local workflow models and data systems

Conclusions (2) Drop-offs found in all steps required to identify and treat patients with HIV Drop-offs found in all steps required to identify and treat patients with HIV Drop-offs not unique to these HIV care systems Drop-offs not unique to these HIV care systems Reasons for drop-offs likely multi-factorial Reasons for drop-offs likely multi-factorial Health system factors (i.e. vertical service structure, inadequate counseling, health-worker shortages) Health system factors (i.e. vertical service structure, inadequate counseling, health-worker shortages) Patient factors (i.e. stigma, transportation problems, limited understanding of HIV and chronic care) Patient factors (i.e. stigma, transportation problems, limited understanding of HIV and chronic care) Strategies needed to overcome identified bottlenecks Strategies needed to overcome identified bottlenecks

Acknowledgements Mozambique Ministry of Health Mozambique Ministry of Health Health Alliance International Health Alliance International University of Washington & UW Center for AIDS and STD University of Washington & UW Center for AIDS and STD USAID / PEPFAR USAID / PEPFAR Staff at the Beira and Chimoio ART clinics Staff at the Beira and Chimoio ART clinics Data management team (Artur Gremu & Pedro Tenente) Data management team (Artur Gremu & Pedro Tenente) Social work team (Agostinho Cunguara, Tomas Jonasse, Georgina Angelina João) Social work team (Agostinho Cunguara, Tomas Jonasse, Georgina Angelina João) Pharmacy team (Barbara Simão, Domingos Mangira, Rabia Colaço) Pharmacy team (Barbara Simão, Domingos Mangira, Rabia Colaço)