In France and elsewhere, decision-makers, healthcare professionals and health planners need to better understand and specify the provision of medical care. To this end, a hospital-based research project on a gravitational health planning modelling process was initiated in 2002. Since then, geomatics has emerged as a major scientific field for facing new challenges in medical informatics and health planning, thanks to the use of attractive interfaces, new methods and user-friendly IT technologies. Our initial 2002 model has recently been enhanced, optimized and automated as part of a spatial decision support system (PoleSat_2018). These decisive improvements and optimizations were mainly based on Delaunay triangulation, the replacement of human expertise with a heuristic dominance rule that provides a complete automated algorithm, and an online graphical user interface. Rapid, easy planning scenarios (by grouping and/or closing hospitals) give a quasi-instantaneous, strategic visualization of hospital catchment areas for decision-makers who are not experts in geomatics via ready-to-use maps and spreadsheets. This new implementation achieves our main objective, since the proposed deterministic method provides a completely automated, stable algorithm. A custom version of this tool is now being used by the French Ministry of Health for real planning issues. Consequently, PoleSat could be easily generalized as a prospective, strategic decision support tool for various health planning issues.
PoleSat, modélisation de la planification sanitaire pour l'aide à la décision. Application à la réorganisation de l'offre de cathétérisme vasculaire au niveau géographique des « groupements hospitaliers de territoire ».
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