TY - JOUR
T1 - Identifying models of HIV care and treatment service delivery in Tanzania, Uganda, and Zambia using cluster analysis and Delphi survey
AU - Tsui, Sharon
AU - Denison, Julie A.
AU - Kennedy, Caitlin E.
AU - Chang, Larry W.
AU - Koole, Olivier
AU - Torpey, Kwasi
AU - Van Praag, Eric
AU - Farley, Jason
AU - Ford, Nathan
AU - Stuart, Leine
AU - Wabwire-Mangen, Fred
N1 - Funding Information:
This research has been funded in part and facilitated by the infrastructure and resources provided by the President’s Emergency Plan for AIDS Relief (PEPFAR) through the Centers for Disease Control and Prevention (CDC) and the Health Resources & Services Administration (HRSA) under the terms of the contract number 2006-N-08428 with FHI 360, the National Institute of Health National Research Service Award (NRSA) under the terms of the fellowship number F31MH095665, the U.S. Department of Education Fulbright-Hays Doctoral Dissertation Research Abroad Award under the fellowship number P022A150076, and the Johns Hopkins University Center for AIDS Research (JHU CFAR), an NIH funded program (P30AI094189), which is supported by the following NIH Co-Funding and Participating Institutes and Centers: NIAID, NCI, NICHD, NHLBI, NIDA, NIMH, NIA, FIC, NIGMS, NIDDK, and OAR. Specifically, CDC/HRSA funded the study design and quantitative data collection, and the NRSA and Fulbright-Hays award supported the qualitative data collection, analysis, interpretation, and writing of the manuscript. JHU CFAR also supported technical advice from a biostatistician on how to perform a cluster analysis. The content is solely the responsibility of the authors and does not necessarily represent the official views of CDC, HRSA, NIH, or any other federal agency or office.
Publisher Copyright:
© 2017 The Author(s).
PY - 2017/12/6
Y1 - 2017/12/6
N2 - Background: Organization of HIV care and treatment services, including clinic staffing and services, may shape clinical and financial outcomes, yet there has been little attempt to describe different models of HIV care in sub-Saharan Africa (SSA). Information about the relative benefits and drawbacks of different models could inform the scale-up of antiretroviral therapy (ART) and associated services in resource-limited settings (RLS), especially in light of expanded client populations with country adoption of WHO's test and treat recommendation. Methods: We characterized task-shifting/task-sharing practices in 19 diverse ART clinics in Tanzania, Uganda, and Zambia and used cluster analysis to identify unique models of service provision. We ran descriptive statistics to explore how the clusters varied by environmental factors and programmatic characteristics. Finally, we employed the Delphi Method to make systematic use of expert opinions to ensure that the cluster variables were meaningful in the context of actual task-shifting of ART services in SSA. Results: The cluster analysis identified three task-shifting/task-sharing models. The main differences across models were the availability of medical doctors, the scope of clinical responsibility assigned to nurses, and the use of lay health care workers. Patterns of healthcare staffing in HIV service delivery were associated with different environmental factors (e.g., health facility levels, urban vs. rural settings) and programme characteristics (e.g., community ART distribution or integrated tuberculosis treatment on-site). Conclusions: Understanding the relative advantages and disadvantages of different models of care can help national programmes adapt to increased client load, select optimal adherence strategies within decentralized models of care, and identify differentiated models of care for clients to meet the growing needs of long-term ART patients who require more complicated treatment management.
AB - Background: Organization of HIV care and treatment services, including clinic staffing and services, may shape clinical and financial outcomes, yet there has been little attempt to describe different models of HIV care in sub-Saharan Africa (SSA). Information about the relative benefits and drawbacks of different models could inform the scale-up of antiretroviral therapy (ART) and associated services in resource-limited settings (RLS), especially in light of expanded client populations with country adoption of WHO's test and treat recommendation. Methods: We characterized task-shifting/task-sharing practices in 19 diverse ART clinics in Tanzania, Uganda, and Zambia and used cluster analysis to identify unique models of service provision. We ran descriptive statistics to explore how the clusters varied by environmental factors and programmatic characteristics. Finally, we employed the Delphi Method to make systematic use of expert opinions to ensure that the cluster variables were meaningful in the context of actual task-shifting of ART services in SSA. Results: The cluster analysis identified three task-shifting/task-sharing models. The main differences across models were the availability of medical doctors, the scope of clinical responsibility assigned to nurses, and the use of lay health care workers. Patterns of healthcare staffing in HIV service delivery were associated with different environmental factors (e.g., health facility levels, urban vs. rural settings) and programme characteristics (e.g., community ART distribution or integrated tuberculosis treatment on-site). Conclusions: Understanding the relative advantages and disadvantages of different models of care can help national programmes adapt to increased client load, select optimal adherence strategies within decentralized models of care, and identify differentiated models of care for clients to meet the growing needs of long-term ART patients who require more complicated treatment management.
KW - Africa
KW - Antiretroviral therapy
KW - Cluster analysis
KW - Delphi method
KW - Human resources for health
KW - Task sharing
KW - Task shifting
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U2 - 10.1186/s12913-017-2772-4
DO - 10.1186/s12913-017-2772-4
M3 - Article
C2 - 29207973
AN - SCOPUS:85037621759
SN - 1472-6963
VL - 17
JO - BMC health services research
JF - BMC health services research
IS - 1
M1 - 811
ER -