Research on the optimization of local healthcare delivery system using geographical information system
Project/Area Number |
16390152
|
Research Category |
Grant-in-Aid for Scientific Research (B)
|
Allocation Type | Single-year Grants |
Section | 一般 |
Research Field |
Medical sociology
|
Research Institution | Kagawa University |
Principal Investigator |
HIRAO Tomohiro Kagawa University, Faculty of Medicine, Associate Professor (20325335)
|
Co-Investigator(Kenkyū-buntansha) |
JITSUNARI Fumihko Kagawa University, Faculty of Medicine, Professor (60127561)
MANNAMI Toshifumi Kagawa University, Faculty of Medicine, Associate Professor (90398032)
SUZUE Takeshi Kagawa University, Faculty of Medicine, Assistant Professor (70398030)
|
Project Period (FY) |
2004 – 2006
|
Project Status |
Completed (Fiscal Year 2006)
|
Budget Amount *help |
¥7,600,000 (Direct Cost: ¥7,600,000)
Fiscal Year 2006: ¥1,900,000 (Direct Cost: ¥1,900,000)
Fiscal Year 2005: ¥2,700,000 (Direct Cost: ¥2,700,000)
Fiscal Year 2004: ¥3,000,000 (Direct Cost: ¥3,000,000)
|
Keywords | healthcare delivery system / access / geographical information system / 地域医療 |
Research Abstract |
A purpose of this study is to clarify the optimal referral patterns in regional healthcare system, considering the characteristics of healthcare facilities, patients and the geographic relations between them. 1. Geographic access to healthcare and choice We surveyed the patterns of consultation and factors affected to the choice of facilities for the residents in the suburb area. With geostatistical analysis, it became clear that the consultation patterns were different between inpatient and outpatient and workers and non-workers, and the distance between worksites and homes affected the choice of facilities. 2. Measurements of geographical distances to healthcare facilities and equity We developed the effective methods with which the geographical access to the facilities and equity were measured. The distance and/or time to the nearest facilities and the number of facilities within certain distance and/or time were appropriate indicators. We estimated the both indicators for major specialties, internal medicine, pediatrics, OBGYN, etc, for each geographical mesh areas. By multiplying the expected number of patients, the average distance and/or time to the nearest facilities and the average number of facilities within certain distance and/or were calculated. They clearly showed the impact of geographical access for small geographical units and were easy to understand by mapping. 3. Development of referral model By using the knowledge of above and clustering the healthcare facilities, we estimated the cluster which caused the optimal geographical access to the healthcare facilities.
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Report
(4 results)
Research Products
(25 results)