Regional disparities in the use of long-term care insurance services by municipality and related factors

  • Okada Risa
    Department of Healthcare Economics and Quality Management, Kyoto University
  • Goto Etsu
    Department of Healthcare Economics and Quality Management, Kyoto University
  • Shin Jun-ho
    Department of Healthcare Economics and Quality Management, Kyoto University
  • Sasaki Noriko
    Department of Healthcare Economics and Quality Management, Kyoto University
  • Imanaka Yuichi
    Department of Healthcare Economics and Quality Management, Kyoto University

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Other Title
  • 市区町村別にみた介護保険サービス利用の地域差と関連因子の検討
  • シクチョウソン ベツ ニ ミタ カイゴ ホケン サービス リヨウ ノ チイキサ ト カンレン インシ ノ ケントウ

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Abstract

<p>Multiple perspectives need to be evaluated to address regional disparities in the use of long-term care insurance services. In this study, we identified regional disparities in long-term care insurance services usage on a municipal basis and then examined factors related to these disparities. First, we described the utilization rates of in-home, community-based, and facility-based services of long-term care insurers at a national level and by three sub-national levels: large cities, regional cities, and depopulated areas. Next, regression analyses were conducted to examine the association between the utilization rate of each service and five exposure factors, adjusting for confounding variables. There were large variations in the utilization rates of each service, especially for in-home services, which were distributed from 0% to 20.4% among the municipalities. In addition, in-home services tended to be used more frequently in large cities, while community-based and facility-based services tended to be used more frequently in depopulated areas. Furthermore, all exposure factors, which included the rate of elderly single-person households, the employment rate of women, the employment rate of the elderly, the number of in-home care managers, and the capacity of facility-based services, showed an association with each service’s utilization rate, even after adjusting for confounders.</p>

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