Geography of spatial utilization of the health services: a Newtonian modelling of hospital catchment areas.. Géographie de l'utilisation spatiale des services de santé: une modélisation newtonienne des zones de recrutement des hôpitaux.

Archive ouverte : Communication dans un congrès

Quesnel-Barbet, Anne

Edité par HAL CCSD

Présentation orale au format .pdf effectuée lors de la conférence , non publié par l'éditeur université de Durham. International audience. Modelling hospital attraction is a major interest for healthcare planners, The impacts of any project can therefore be analyzed prospectively. Our aim is to build an efficient tool for observation, simulation and prediction of hospital catchment areas by medical field for health policy makers. The study covers the French Nord - Pas-de-Calais region (four million inhabitants) for the evaluation of onco-haematology and Trauma orthopedics care activities with the French Medical Program of Information System (PMSI). Our geographical and mathematical model is based on the hypothesis: there is a link between recourse to health care and distance in km or in time. The "principle of least effort" is expected to hold for peripheral hospitals (non-university hospitals). We have improved Reilly's formula by using usual weight (number of beds) and also refining parameters (calculated population from one of the both algorithms: Relative Neighborhood Graph and K-means calculations). So we propose a modelling Process of the spatial health services utilization in four parts. The first phase is a descriptive geographic study from the observed situation of the catchment area, which is completed by a descriptive study of a few haematology departments. The second phase concerns the implementation of our geographical and mathematical model. In the third phase we compare the observed situations with those predicted by our model. The last part is devoted to the spatial prediction of the attraction using a simulation model for reorganization with opening closing and aggregation of health services. After comparison and simulation steps out model appears to be robust, reliable and predictive and along with a better knowledge of the spatial utilization by specialty. It can be a new tool for development and management in health care districts and could be integrated inside a geomatics platform or/and GIS.

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