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Decentralization of HIV care and treatment services in Central Province, Kenya: Adult patient characteristics and outcomes. Presenting author: William Reidy , PhD Reidy W, Hawken M, Wang C, Koech E, Elul B, and Abrams EJ
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Decentralization of HIV care and treatment services in Central Province, Kenya: Adult patient characteristics and outcomes Presenting author: William Reidy, PhD Reidy W, Hawken M, Wang C, Koech E, Elul B, and Abrams EJ for the Identifying Optimal Models of HIV Care in Africa: Kenya Consortium
Background: Kenya • Population: 38.6 million • Adult HIV prevalence: 6.2% • Living with HIV: 1.6 million • Estimated annual number of newly infected: 100,000 • Number died of AIDS-related causes in 2011: 49,126
Background: Decentralization of HIV care in Kenya • HIV care/ART in Kenya was provided in a small number of secondary health facilities (HF): • District, sub-district, provincial, or teaching/national referral hospitals • Beginning in 2004, started scaling up HIV clinics at smaller, primary HF: • Health centers and dispensaries • Performance of primary HF during scale-up is not well-established
Objective • To compare the performance of primary and secondary HF in Central Province, Kenya during a period of scale-up: • Patient volume • Patient and facility characteristics • Quality of care • Patient retention
Population and data sources • 37 of 52 government health facilities in Central Province supported by ICAP at Columbia University via PEPFAR funding • 15 secondary and22 primary HF • Included patients enrolled between 2006-10 (N=26,690) • Data sources: • HIV care/ART data from patient-level databases maintained by facility staff • Annual facility survey conducted by ICAP
Key variables and outcomes (1) • Patient volume • Number of patients enrolled in HIV care, by year • Patient characteristics • Gender, age, WHO stage, CD4 count at enrollment and ART initiation • Facility characteristics • Rural/non-rural, nurse ART provision, CD4 machine on-site
Key variables and outcomes (2) • Quality of care • Assessment of ART eligibility (CD4/WHO), prompt ART initiation • Patient retention • Death: Recorded as dead in facility database • Loss to follow-up: Not dead, not transferred out, and not attending clinic for >6 months for patients on ART, or >12 month for pre-ART patients
Analytic Methods • Descriptive statistics • Kaplan-Meier survival curves • Competing risks regression (pre-ART) and Cox proportional hazards regression (ART) • Multivariate regression models included: site type (primary vs. secondary HF), WHO stage, CD4 count, age group, gender, year of patient enrollment in care or ART initiation
Enrollment in HIV care and treatment at primary and secondary HF
Enrollment in HIV care and treatment at primary and secondary HF # Primary HF # Secondary HF
Clinic location, nurse ART provision, and presence of CD4 machine on-site
Quality of care: ART eligibility assessment and prompt initiation
Death following enrollment in HIV care(pre-ART) Adjusted SHR=1.29 95% CI: (0.91-1.84)
LTF following enrollment in HIV care (pre-ART) Adjusted SHR=0.77 95% CI: (0.62-0.97)
Death following ART initiation Adjusted HR=0.94 95% CI: (0.67-1.32)
LTF following ART initiation Adjusted HR=0.67 95% CI: (0.27-1.65)
Adjusted S/HR of non-retention in Primary vs. Secondary HF *Reference category: Secondary HF. Models control for WHO stage, CD4 count, age group, gender, year of patient enrollment in care or ART initiation
Adjusted S/HR of non-retention in Primary vs. Secondary HFSensitivity analysis excluding transfer-in patients *Reference category: Secondary HF. Models control for WHO stage, CD4 count, age group, gender, year of patient enrollment in care or ART initiation
Summary • Patient enrollment at primary HF increased dramatically during the period • Patients enrolling in primary HF were somewhat healthier by WHO stage, CD4 count • Quality of patient care and retention were comparable at primary and secondary HF • Among pre-ART patients, the rate of LTF was lower at primary than at secondary facilities • Primary HF have performed well within the context of decentralization in Central Province, Kenya
Acknowledgements • Kenya Ministry of Health • Government staff at the 37 facilities • ICAP staff in Kenya and in New York • Dr. MuhsinSheriff (Kenya), MansiAgarwal (NY) • US Centers for Disease Control and Prevention • The President’s Emergency Plan for AIDS Relief • This research was supported by PEPFAR through the CDC under the terms of Cooperative Agreement Number 5U62PS223540 and 5U2GPS001537