Estimation and Evaluation of Future Demand and Supply of Healthcare Services Based on a Patient Access Area Model

Shunsuke Doi, Hiroo Ide, Koichi Takeuchi, Shinsuke Fujita and Katsuhiko Takabayashi
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Shunsuke Doi: Department of Healthcare and Information Management, University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
Hiroo Ide: Department of Welfare and Medical Intelligence, Chiba University Hospital, 1-8-1 Inohana, Chuo-ku, Chiba 260-8677, Japan
Koichi Takeuchi: Department of Welfare and Medical Intelligence, Chiba University Hospital, 1-8-1 Inohana, Chuo-ku, Chiba 260-8677, Japan
Shinsuke Fujita: Department of Welfare and Medical Intelligence, Chiba University Hospital, 1-8-1 Inohana, Chuo-ku, Chiba 260-8677, Japan
Katsuhiko Takabayashi: Department of Internal Medicine, Sanwa Hospital, Medical Incorporated Association Kanae-kai, 7-379 Higurashi, Matsudo, Chiba 270-2253, Japan

IJERPH, 2017, vol. 14, issue 11, 1-15

Abstract: Accessibility to healthcare service providers, the quantity, and the quality of them are important for national health. In this study, we focused on geographic accessibility to estimate and evaluate future demand and supply of healthcare services. We constructed a simulation model called the patient access area model (PAAM), which simulates patients’ access time to healthcare service institutions using a geographic information system (GIS). Using this model, to evaluate the balance of future healthcare services demand and supply in small areas, we estimated the number of inpatients every five years in each area and compared it with the number of hospital beds within a one-hour drive from each area. In an experiment with the Tokyo metropolitan area as a target area, when we assumed hospital bed availability to be 80%, it was predicted that over 78,000 inpatients would not receive inpatient care in 2030. However, this number would decrease if we lowered the rate of inpatient care by 10% and the average length of the hospital stay. Using this model, recommendations can be made regarding what action should be undertaken and by when to prevent a dramatic increase in healthcare demand. This method can help plan the geographical resource allocation in healthcare services for healthcare policy.

Keywords: geographic information systems; health services demand; health services geographic accessibility; estimation (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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