|
Hokkaido University Collection of Scholarly and Academic Papers >
Graduate School of Health Sciences / Faculty of Health Sciences >
Peer-reviewed Journal Articles, etc >
Relationship between accessibility and resources to treat acute ischemic stroke. Hokkaido, Japan : Analysis of inequality and coverage using geographic information systems
This item is licensed under:Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
| Title: | Relationship between accessibility and resources to treat acute ischemic stroke. Hokkaido, Japan : Analysis of inequality and coverage using geographic information systems |
| Authors: | Ishikawa, Tomoki Browse this author | | Mizuguchi, Hiro Browse this author | | Murayama, Hiroshi Browse this author | | Fujiwara, Kensuke Browse this author | | Tanikawa, Takumi Browse this author →KAKEN DB | | Kobayashi, Eiichi Browse this author | | Ogasawara, Katsuhiko Browse this author →KAKEN DB |
| Keywords: | Health services accessibility | | Spatial analysis | | Geographic information system (GIS) | | Response time (RT) | | Emergency medical services (EMS) |
| Issue Date: | Dec-2019 |
| Publisher: | Elsevier |
| Journal Title: | Health policy and technology |
| Volume: | 8 |
| Issue: | 4 |
| Start Page: | 337 |
| End Page: | 342 |
| Publisher DOI: | 10.1016/j.hlpt.2019.10.001 |
| Abstract: | Objectives: This study aimed to clarify the relationship between the institution and resident with respect to accessibility to acute ischemic stroke (AIS) treatment in Hokkaido and to propose new methodology monitoring for accessibility to healthcare resources. Methods: This study involves the use of geographic information system (GIS) network analysis. We established hospital/clinic with one of the following conditions as resources for AIS treatment: (1) medical facility practicing AIS treatment, (2) having computed tomography (CT) equipment, (3) having angiography equipment, and (4) having AIS specialists (neurosurgeons). We evaluated the coverage of population resources using transport time between ambulance departure and arrival at the healthcare facility. Furthermore, we compared the population coverage rate using available resources and calculated a Gini coefficient to analyze its relation with inequality. Empirical analysis was performed, and public database for data collection was utilized. We calculated the rate of population coverage with a transport time within 10 min as an indicator of accessibility to medical resources by GIS. Results: The Gini coefficients of practicable facilities, CT, angiography, and neurosurgeons are 0.35, 0.16, 0.18, and 0.30, respectively. The inequality of accessibility differs depending on the resources, and Gini coefficients indicate that hospital/clinic and neurosurgeons were considered to have higher allocation inequalities than CT and angiography. Conclusions: Combining Gini coefficient and GIS network analysis in accessibility can be useful in quantifying and monitoring variation by region. We propose this combination as a new method for helping the government to make evidence-based healthcare planning. (C) 2019 Fellowship of Postgraduate Medicine. Published by Elsevier Ltd. All rights reserved. |
| Rights: | © 2019. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ | | https://creativecommons.org/licenses/by-nc-nd/4.0/ |
| Type: | article (author version) |
| URI: | http://hdl.handle.net/2115/79547 |
| Appears in Collections: | 保健科学院・保健科学研究院 (Graduate School of Health Sciences / Faculty of Health Sciences) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
|
Submitter: 小笠原 克彦
|
