Geospatial Inequities and Community-Based Behavioral Interventions for Type 2 Diabetes Control in Health Region 10, Thailand

Abstract

District health system strengthening increasingly requires spatially informed decision making to address inequities in service accessibility, workforce distribution, and resource allocation. However, geoinformatics has often been applied as a technical mapping tool, with limited integration into governance structures and managerial competency development. This study proposes a Geoinformatics-Based Competency Framework to institutionalize GIS-supported spatial analytics within district-level health system management. A mixed-methods research design was employed in eight districts of Krabi Province, Southern Thailand. Quantitative data were collected from primary care managers using a quasi-experimental pre–post design, while qualitative data were obtained through participatory workshops and in-depth discussions. Spatial datasets, including population distribution, health facility locations, and health workforce deployment, were integrated into a GIS environment to support spatial overlay analysis and network-based accessibility assessment. Participatory learning activities were implemented to enhance geospatial literacy and spatial decision-making capability among district managers. The results demonstrate statistically significant improvements in district health management performance, particularly in planning, directing, and leading functions (p < 0.05). GIS-based spatial analysis revealed localized service accessibility gaps and resource mismatches that were not identifiable through conventional management information systems. Qualitative findings indicate that participatory engagement with spatial outputs strengthened managerial capacity to interpret spatial evidence, justify prioritization decisions, and support equity-oriented governance. This study advances applied geoinformatics by embedding spatial analytics within managerial competency development and routine governance processes. The proposed framework provides a transferable model for integrating geoinformatics into decentralized health systems, positioning GIS as a decision-support infrastructure that enhances spatially informed governance rather than a standalone technical application.