Determinants of Demand for Community Differentiated Service Delivery among People Living with HIV in Kakamega County

Abstract

Community differentiated service delivery model (CDSD) is community level health system strengthening intervention that addresses barriers to accessing health services. Increased number of stable people living with human immunodeficiency virus (PLHIV) has prompted more emphasis to promoting CDSD model utilization as a significant policy to improve health outcomes and meet the international commitment to make health services accessible. However, key health systems policy makers have put more emphasis on improving physical access rather than its patterns of utilization. This study seeks to understand demand for CDSD model and its determinants among PLHIV in order to device appropriate strategies that will encourage better utilization. The objectives were to assess CDSD model of choice, and factors that determine its demand among PLHIV. A quantitative design was conducted in Kakamega County, Kenya. Systematic random sampling was used to select 402 participants from facilities with high number of stable patients. A pretested interview schedule, and structured questionnaire was used to collect data using an open data kit app. Non parametric test was used to determine determinants for demand for CDSD model. A total of 402 (depicting a response rate of 100%) participants took part in the study. The tests revealed 66 % (264) of participants prefers the family model, 25 % (100) community anti-retroviral treatment groups, 8% (30) community drug distribution points, and 2% (8) community pharmacies. Determinants of demand were awareness 76% (307), acceptability 44% (176), service availability 78% (314), and service cost 78% (315). The findings indicate that the model of choice is the family model. Determinants for demand that affect utilization of the model include awareness, service availability and cost of the services. Policy makers in the ministry of health need to use these key determinants of demand to estimate its impact on health service delivery and health outcomes.