Methodology for Real-Time Evaluation of Geographic Health Care Resource Allocation: Iwate Prefectural Hospitals

Xinhe Li; Kazunori Kawamura

doi:doi:10.11648/j.sjbm.20210902.11

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Methodology for Real-Time Evaluation of Geographic Health Care Resource Allocation: Iwate Prefectural Hospitals

Xinhe Li, Kazunori Kawamura

Published in Science Journal of Business and Management (Volume 9, Issue 2)

Received: 20 April 2021 Accepted: Published: 24 May 2021

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Abstract

The effective utilization and assessment of medical resources have become a common concern for scholars in various countries due to the impact of the COVID-19 pandemic. This study deals with a method to monitor medical resource allocation in real-time and verify the effectiveness of the proposed method with actual data. In this work, we selected Iwate Prefecture in northeastern Japan based on the geographical characteristics and social environment. By collecting data from the Japanese Ministry of Land, Infrastructure, Transport, and Tourism and Welfare (MLIT), we clustered population centers in Iwate Prefecture, and found the clustering centers in densely populated areas from the k-means algorithm. Subsequently, to compare the distribution of county-level medical resources across different secondary care areas, we selected the indicators of Iwate Prefectural Hospitals from the Hospital Intelligence Agency. We classified 19 prefectural hospitals in Iwate Prefecture into four different clusters using the spectral clustering algorithm. The clustering results revealed that all hospitals close to the " clustering centers in densely populated areas" were Iwate prefectural disaster stronghold hospitals. Moreover, we found that these hospitals performed well in operational indicators. Only the Ninohe prefectural hospital in the Ninohe medical area was found not located in a population center. However, it still performs well in terms of business indicators since the Ninohe medical area has a high proportion of public hospitals and the Ninohe prefectural hospital plays an important role. Hence, the government should fully consider geographical characteristics when considering hospital restructuring. We used a real data set to demonstrate the validity of the proposed technique, providing a theoretical basis for the government's healthcare policy.

Published in	Science Journal of Business and Management (Volume 9, Issue 2)
DOI	10.11648/j.sjbm.20210902.11
Page(s)	55-61
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Medical Resources, Real-time Evaluation Method, K-means Algorithm, Spectral Clustering Algorithm, Iwate Prefectural Hospitals

References

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APA Style

Xinhe Li, Kazunori Kawamura. (2021). Methodology for Real-Time Evaluation of Geographic Health Care Resource Allocation: Iwate Prefectural Hospitals. Science Journal of Business and Management, 9(2), 55-61. https://doi.org/10.11648/j.sjbm.20210902.11

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ACS Style

Xinhe Li; Kazunori Kawamura. Methodology for Real-Time Evaluation of Geographic Health Care Resource Allocation: Iwate Prefectural Hospitals. Sci. J. Bus. Manag. 2021, 9(2), 55-61. doi: 10.11648/j.sjbm.20210902.11

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AMA Style

Xinhe Li, Kazunori Kawamura. Methodology for Real-Time Evaluation of Geographic Health Care Resource Allocation: Iwate Prefectural Hospitals. Sci J Bus Manag. 2021;9(2):55-61. doi: 10.11648/j.sjbm.20210902.11

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@article{10.11648/j.sjbm.20210902.11,
  author = {Xinhe Li and Kazunori Kawamura},
  title = {Methodology for Real-Time Evaluation of Geographic Health Care Resource Allocation: Iwate Prefectural Hospitals},
  journal = {Science Journal of Business and Management},
  volume = {9},
  number = {2},
  pages = {55-61},
  doi = {10.11648/j.sjbm.20210902.11},
  url = {https://doi.org/10.11648/j.sjbm.20210902.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjbm.20210902.11},
  abstract = {The effective utilization and assessment of medical resources have become a common concern for scholars in various countries due to the impact of the COVID-19 pandemic. This study deals with a method to monitor medical resource allocation in real-time and verify the effectiveness of the proposed method with actual data. In this work, we selected Iwate Prefecture in northeastern Japan based on the geographical characteristics and social environment. By collecting data from the Japanese Ministry of Land, Infrastructure, Transport, and Tourism and Welfare (MLIT), we clustered population centers in Iwate Prefecture, and found the clustering centers in densely populated areas from the k-means algorithm. Subsequently, to compare the distribution of county-level medical resources across different secondary care areas, we selected the indicators of Iwate Prefectural Hospitals from the Hospital Intelligence Agency. We classified 19 prefectural hospitals in Iwate Prefecture into four different clusters using the spectral clustering algorithm. The clustering results revealed that all hospitals close to the " clustering centers in densely populated areas" were Iwate prefectural disaster stronghold hospitals. Moreover, we found that these hospitals performed well in operational indicators. Only the Ninohe prefectural hospital in the Ninohe medical area was found not located in a population center. However, it still performs well in terms of business indicators since the Ninohe medical area has a high proportion of public hospitals and the Ninohe prefectural hospital plays an important role. Hence, the government should fully consider geographical characteristics when considering hospital restructuring. We used a real data set to demonstrate the validity of the proposed technique, providing a theoretical basis for the government's healthcare policy.},
 year = {2021}
}

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TY  - JOUR
T1  - Methodology for Real-Time Evaluation of Geographic Health Care Resource Allocation: Iwate Prefectural Hospitals
AU  - Xinhe Li
AU  - Kazunori Kawamura
Y1  - 2021/05/24
PY  - 2021
N1  - https://doi.org/10.11648/j.sjbm.20210902.11
DO  - 10.11648/j.sjbm.20210902.11
T2  - Science Journal of Business and Management
JF  - Science Journal of Business and Management
JO  - Science Journal of Business and Management
SP  - 55
EP  - 61
PB  - Science Publishing Group
SN  - 2331-0634
UR  - https://doi.org/10.11648/j.sjbm.20210902.11
AB  - The effective utilization and assessment of medical resources have become a common concern for scholars in various countries due to the impact of the COVID-19 pandemic. This study deals with a method to monitor medical resource allocation in real-time and verify the effectiveness of the proposed method with actual data. In this work, we selected Iwate Prefecture in northeastern Japan based on the geographical characteristics and social environment. By collecting data from the Japanese Ministry of Land, Infrastructure, Transport, and Tourism and Welfare (MLIT), we clustered population centers in Iwate Prefecture, and found the clustering centers in densely populated areas from the k-means algorithm. Subsequently, to compare the distribution of county-level medical resources across different secondary care areas, we selected the indicators of Iwate Prefectural Hospitals from the Hospital Intelligence Agency. We classified 19 prefectural hospitals in Iwate Prefecture into four different clusters using the spectral clustering algorithm. The clustering results revealed that all hospitals close to the " clustering centers in densely populated areas" were Iwate prefectural disaster stronghold hospitals. Moreover, we found that these hospitals performed well in operational indicators. Only the Ninohe prefectural hospital in the Ninohe medical area was found not located in a population center. However, it still performs well in terms of business indicators since the Ninohe medical area has a high proportion of public hospitals and the Ninohe prefectural hospital plays an important role. Hence, the government should fully consider geographical characteristics when considering hospital restructuring. We used a real data set to demonstrate the validity of the proposed technique, providing a theoretical basis for the government's healthcare policy.
VL  - 9
IS  - 2
ER  -

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Author Information

Xinhe Li

Graduate School of Information Sciences, Tohoku University, Sendai, Japan
Kazunori Kawamura

Graduate School of Information Sciences, Tohoku University, Sendai, Japan

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APA Style

Xinhe Li, Kazunori Kawamura. (2021). Methodology for Real-Time Evaluation of Geographic Health Care Resource Allocation: Iwate Prefectural Hospitals. Science Journal of Business and Management, 9(2), 55-61. https://doi.org/10.11648/j.sjbm.20210902.11

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ACS Style

Xinhe Li; Kazunori Kawamura. Methodology for Real-Time Evaluation of Geographic Health Care Resource Allocation: Iwate Prefectural Hospitals. Sci. J. Bus. Manag. 2021, 9(2), 55-61. doi: 10.11648/j.sjbm.20210902.11

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AMA Style

Xinhe Li, Kazunori Kawamura. Methodology for Real-Time Evaluation of Geographic Health Care Resource Allocation: Iwate Prefectural Hospitals. Sci J Bus Manag. 2021;9(2):55-61. doi: 10.11648/j.sjbm.20210902.11

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@article{10.11648/j.sjbm.20210902.11,
  author = {Xinhe Li and Kazunori Kawamura},
  title = {Methodology for Real-Time Evaluation of Geographic Health Care Resource Allocation: Iwate Prefectural Hospitals},
  journal = {Science Journal of Business and Management},
  volume = {9},
  number = {2},
  pages = {55-61},
  doi = {10.11648/j.sjbm.20210902.11},
  url = {https://doi.org/10.11648/j.sjbm.20210902.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjbm.20210902.11},
  abstract = {The effective utilization and assessment of medical resources have become a common concern for scholars in various countries due to the impact of the COVID-19 pandemic. This study deals with a method to monitor medical resource allocation in real-time and verify the effectiveness of the proposed method with actual data. In this work, we selected Iwate Prefecture in northeastern Japan based on the geographical characteristics and social environment. By collecting data from the Japanese Ministry of Land, Infrastructure, Transport, and Tourism and Welfare (MLIT), we clustered population centers in Iwate Prefecture, and found the clustering centers in densely populated areas from the k-means algorithm. Subsequently, to compare the distribution of county-level medical resources across different secondary care areas, we selected the indicators of Iwate Prefectural Hospitals from the Hospital Intelligence Agency. We classified 19 prefectural hospitals in Iwate Prefecture into four different clusters using the spectral clustering algorithm. The clustering results revealed that all hospitals close to the " clustering centers in densely populated areas" were Iwate prefectural disaster stronghold hospitals. Moreover, we found that these hospitals performed well in operational indicators. Only the Ninohe prefectural hospital in the Ninohe medical area was found not located in a population center. However, it still performs well in terms of business indicators since the Ninohe medical area has a high proportion of public hospitals and the Ninohe prefectural hospital plays an important role. Hence, the government should fully consider geographical characteristics when considering hospital restructuring. We used a real data set to demonstrate the validity of the proposed technique, providing a theoretical basis for the government's healthcare policy.},
 year = {2021}
}

Copy | Download

TY  - JOUR
T1  - Methodology for Real-Time Evaluation of Geographic Health Care Resource Allocation: Iwate Prefectural Hospitals
AU  - Xinhe Li
AU  - Kazunori Kawamura
Y1  - 2021/05/24
PY  - 2021
N1  - https://doi.org/10.11648/j.sjbm.20210902.11
DO  - 10.11648/j.sjbm.20210902.11
T2  - Science Journal of Business and Management
JF  - Science Journal of Business and Management
JO  - Science Journal of Business and Management
SP  - 55
EP  - 61
PB  - Science Publishing Group
SN  - 2331-0634
UR  - https://doi.org/10.11648/j.sjbm.20210902.11
AB  - The effective utilization and assessment of medical resources have become a common concern for scholars in various countries due to the impact of the COVID-19 pandemic. This study deals with a method to monitor medical resource allocation in real-time and verify the effectiveness of the proposed method with actual data. In this work, we selected Iwate Prefecture in northeastern Japan based on the geographical characteristics and social environment. By collecting data from the Japanese Ministry of Land, Infrastructure, Transport, and Tourism and Welfare (MLIT), we clustered population centers in Iwate Prefecture, and found the clustering centers in densely populated areas from the k-means algorithm. Subsequently, to compare the distribution of county-level medical resources across different secondary care areas, we selected the indicators of Iwate Prefectural Hospitals from the Hospital Intelligence Agency. We classified 19 prefectural hospitals in Iwate Prefecture into four different clusters using the spectral clustering algorithm. The clustering results revealed that all hospitals close to the " clustering centers in densely populated areas" were Iwate prefectural disaster stronghold hospitals. Moreover, we found that these hospitals performed well in operational indicators. Only the Ninohe prefectural hospital in the Ninohe medical area was found not located in a population center. However, it still performs well in terms of business indicators since the Ninohe medical area has a high proportion of public hospitals and the Ninohe prefectural hospital plays an important role. Hence, the government should fully consider geographical characteristics when considering hospital restructuring. We used a real data set to demonstrate the validity of the proposed technique, providing a theoretical basis for the government's healthcare policy.
VL  - 9
IS  - 2
ER  -

Copy | Download