Abstract
Health policies are significant in relation to health equity and accessibility. Achieving equity in health care must understand the geographic distribution of health care and the impact of policy decisions on access Planners can use Geographic Information Systems (GIS) as an aid powerful to visualize and scrutinize these differences. The current study addresses some of the challenges of integrating multiple data sources, definitions of access and equity and the dynamic nature of health care processes. Furthermore, sophisticated analytical methods are needed to truly map all complex health care systems. Therefore this paper, describe a cross-sectional mental health treatment (C-SMHT) that uses a fuzzy inference system to assess justice and access to health care. Using ambiguous GIS data to address uncertainty and environmental variability, this approach provides a comprehensive picture of how policy change has shaped health disparities to improve. C-SMHT has many applications for policy makers as well as public health practitioners. This paper will provide a snapshot of mental health provider availability and utilization. Simulation studies to examine how the effectiveness of the C-SMHT approach can help to better identify underserved areas, better allocate resources, and deliver treatment were found to be good. A number of initiatives will be developed as part of this project to assess their impact on the availability of mental health services in defined areas or countries. In addition to providing recommendations to policy makers based on research findings, the simulation will also provide insights into how policies affect equity and access.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call