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Using participatory system dynamics learning to support Ryan White Planning Council priority setting and resource allocations.

Authors :
Weeks MR
Green Montaque HD
Lounsbury DW
Li J
Ferguson A
Warren-Dias D
Source :
Evaluation and program planning [Eval Program Plann] 2022 Aug; Vol. 93, pp. 102104. Date of Electronic Publication: 2022 May 13.
Publication Year :
2022

Abstract

The Ryan White CARE Act provides federal dollars supporting low income people living with HIV/AIDS (PLWH). Regional Ryan White Planning Councils (RWPC) are responsible for setting priorities and deciding CARE Act fund allocations, using local data to identify greatest need. However, RWPC are challenged with interpreting complex epidemiological, service utilization, and community needs data to inform priority setting and resource allocations. We piloted system dynamics (SD) learning, using a validated HIV care continuum SD simulation model calibrated to one northeastern U.S. Ryan White funding area. The pilot applied systems thinking to understand the complex HIV care continuum and to simulate and compare outcomes of various resource allocation decisions. Three scripted workshops provided opportunities to learn the SD modeling process and simulation tool, simulate various resource allocations, and compare population health outcomes. Mixed methods evaluation documented the SD modeling process, member responses to the modeling sessions, and attitudes regarding benefits and limitations of SD modeling for RWPC decision-making. Despite high member turnover and complexity of the SD model, members could understand the simulation model and propose strategies to seek greatest improvements in HIV care retention, viral suppression, and reduced infections. Findings suggests the value of SD modeling to assist RWPC decisions.<br /> (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Details

Language :
English
ISSN :
1873-7870
Volume :
93
Database :
MEDLINE
Journal :
Evaluation and program planning
Publication Type :
Academic Journal
Accession number :
35660383
Full Text :
https://doi.org/10.1016/j.evalprogplan.2022.102104