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<p>Geographic variation is a fundamental dimension of health and healthcare delivery; however, the routine integration of geographic information systems (GIS) into clinical and health services research remains inconsistent and often unsystematic. Despite substantial methodological advances in spatial epidemiology, the application of GIS in practice is frequently fragmented, with limited guidance on how to align specific research questions with appropriate spatial analytical methods. This study presents a practical, question-driven framework designed to support health services researchers, clinicians, and public health researchers in the selection, application, and interpretation of GIS-based methods within routine research workflows. Drawing on established principles from spatial epidemiology and recent methodological developments (2010–2024), this framework systematically links common research objectives to appropriate spatial data representations, analytical methods, and interpretation strategies. A key contribution of this work is the explicit operationalization of spatial analysis as a decision-support process, moving beyond tool-based or descriptive approaches. The framework integrates GIS with conventional statistical analysis, incorporates guidance on methodological considerations such as spatial scale, autocorrelation, accessibility modelling, and spatio-temporal dynamics, and provides a structured workflow and decision matrix to support reproducible and policy-relevant analysis. The framework demonstrates applicability across core domains of health services research, including healthcare accessibility, service distribution, spatial inequalities, environmental exposure assessment, and explanatory modelling. By embedding spatial analysis within standard analytical workflows, it lowers conceptual and methodological barriers to adoption and enhances the interpretability and practical relevance of spatial evidence. This approach supports more consistent and informed use of GIS in health research, strengthening evidence-based decision-making for healthcare planning, service delivery, and health policy, particularly in settings characterized by spatial inequities in access and outcomes.</p>

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From clinical questions to spatial analysis: a practical GIS framework for clinicians and public health researchers

  • 期刊论文

  • 发表日期：

    2026年7月13日

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  • Arshad Ahmed,
  • U. Venkatesh

摘要

Geographic variation is a fundamental dimension of health and healthcare delivery; however, the routine integration of geographic information systems (GIS) into clinical and health services research remains inconsistent and often unsystematic. Despite substantial methodological advances in spatial epidemiology, the application of GIS in practice is frequently fragmented, with limited guidance on how to align specific research questions with appropriate spatial analytical methods. This study presents a practical, question-driven framework designed to support health services researchers, clinicians, and public health researchers in the selection, application, and interpretation of GIS-based methods within routine research workflows. Drawing on established principles from spatial epidemiology and recent methodological developments (2010–2024), this framework systematically links common research objectives to appropriate spatial data representations, analytical methods, and interpretation strategies. A key contribution of this work is the explicit operationalization of spatial analysis as a decision-support process, moving beyond tool-based or descriptive approaches. The framework integrates GIS with conventional statistical analysis, incorporates guidance on methodological considerations such as spatial scale, autocorrelation, accessibility modelling, and spatio-temporal dynamics, and provides a structured workflow and decision matrix to support reproducible and policy-relevant analysis. The framework demonstrates applicability across core domains of health services research, including healthcare accessibility, service distribution, spatial inequalities, environmental exposure assessment, and explanatory modelling. By embedding spatial analysis within standard analytical workflows, it lowers conceptual and methodological barriers to adoption and enhances the interpretability and practical relevance of spatial evidence. This approach supports more consistent and informed use of GIS in health research, strengthening evidence-based decision-making for healthcare planning, service delivery, and health policy, particularly in settings characterized by spatial inequities in access and outcomes.