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      Healthcare costs for the elderly in Japan: Analysis of medical care and long-term care claim records

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          Abstract

          Background

          The population is aging rapidly in many developed countries. Such countries need to respond to the growing demand and expanding costs of healthcare (HC) for the elderly. Therefore, it is important to investigate the factors correlating such HC costs. In Japan, HC is composed of two sections, namely medical care (MC) and long-term care (LTC). While many studies have examined MC and LTC costs on their own, few studies have conducted comprehensive investigations of HC costs. The aim of this study is to examine the risk factors that influence HC costs for the elderly who enroll in the LTC insurance system in Japan.

          Methods

          The inclusion criteria in the present study are as follows: being 65 years of age, or older; certified eligibility for, and use of services offered by the LTC insurance system at home or in an institutional setting in December 2009; and being covered by the National Health Insurance (NHI) system. MC and LTC insurance data were obtained from claim records for the elderly in July and December of 2007, 2008, and 2009 (i.e., a total of six survey points). Panel data, per subject, were constructed using MC and LTC claim records. The sample included 810 subjects and 4029 observations.

          Results

          We estimated a regression equation with a censored dependent variable using a Tobit model. Significant associations between MC or LTC costs and interaction terms (household composition × seasonal effects) were investigated. MC costs significantly decreased and LTC costs significantly increased among subjects living alone during winter. Income level was also a positive determinant of MC costs, while eligibility level was a positive determinant of LTC costs.

          Conclusions

          We recommend that the health policy for the elderly focus more on seasonal effects, household composition, and income level, as well as on eligibility level.

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          Most cited references17

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          Estimation of Relationships for Limited Dependent Variables

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            Informal care and health care use of older adults.

            Informal care by adult children is a common form of long-term care for older adults and can reduce medical expenditures if it substitutes for formal care. We address how informal care by all children affects formal care, which is critically important given demographic trends and the many policies proposed to promote informal care. We examine the 1998 Health and Retirement Survey (HRS) and 1995 Asset and Health Dynamics Among the Oldest-Old Panel Survey (AHEAD) using two-part utilization models. Instrumental variables (IV) estimation controls for the simultaneity of informal and formal care. Informal care reduces home health care use and delays nursing home entry.
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              Understanding the context of healthcare utilization: assessing environmental and provider-related variables in the behavioral model of utilization.

              The behavioral model of utilization, developed by Andersen, Aday, and others, is one of the most frequently used frameworks for analyzing the factors that are associated with patient utilization of healthcare services. However, the use of the model for examining the context within which utilization occurs-the role of the environment and provider-related factors-has been largely neglected. To conduct a systematic review and analysis to determine if studies of medical care utilization that have used the behavioral model during the last 20 years have included environmental and provider-related variables and the methods used to analyze these variables. We discuss barriers to the use of these contextual variables and potential solutions. The Social Science Citation Index and Science Citation Index. We included all articles from 1975-1995 that cited any of three key articles on the behavioral model, that included all articles that were empirical analyses and studies of formal medical care utilization, and articles that specifically stated their use of the behavioral model (n = 139). Design was a systematic literature review. We used a structured review process to code articles on whether they included contextual variables: (1) environmental variables (characteristics of the healthcare delivery system, external environment, and community-level enabling factors); and (2) provider-related variables (patient factors that may be influenced by providers and provider characteristics that interact with patient characteristics to influence utilization). We also examined the methods used in studies that included contextual variables. Forty-five percent of the studies included environmental variables and 51 percent included provider-related variables. Few studies examined specific measures of the healthcare system or provider characteristics or used methods other than simple regression analysis with hierarchical entry of variables. Only 14 percent of studies analyzed the context of healthcare by including both environmental and provider-related variables as well as using relevant methods. By assessing whether and how contextual variables are used, we are able to highlight the contributions made by studies using these approaches, to identify variables and methods that have been relatively underused, and to suggest solutions to barriers in using contextual variables.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: Writing – original draftRole: Writing – review & editing
                Role: Formal analysisRole: Investigation
                Role: ConceptualizationRole: Supervision
                Role: ConceptualizationRole: Supervision
                Role: Supervision
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                14 May 2018
                2018
                : 13
                : 5
                : e0190392
                Affiliations
                [1 ] Iwate Medical University, School of Nursing, Iwate, Japan
                [2 ] Department of Health and Welfare Services, National Institute of Public Health, Wako, Saitama, Japan
                [3 ] Nursing and Health Sciences, Oita University, Oita, Oita, Japan
                [4 ] Department of Medical Informatics and Management, University Hospital, University of Occupational and Environmental Health, Kitakyushu, Fukuoka, Japan
                Public Library of Science, UNITED KINGDOM
                Author notes

                Competing Interests: NA received funding from Pfizer Health Research Foundation. The Pfizer Health Research Foundation is a separate organization from Pfizer Pharmaceutical. This does not alter adherence to PLOS ONE policies on sharing data and materials.

                Article
                PONE-D-16-15465
                10.1371/journal.pone.0190392
                5951584
                29758026
                c7de9f42-ebb9-4533-a905-3c8ec3c94018
                © 2018 Akiyama et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 18 April 2016
                : 14 December 2017
                Page count
                Figures: 0, Tables: 8, Pages: 15
                Funding
                Funded by: Pfizer Health Research Foundation
                Award ID: 09-09-40
                Award Recipient :
                This work was supported by the Pfizer Health Research Foundation, grant number is 09-09-40 ( https://www.health-research.or.jp/index.html) to NA. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Geriatrics
                People and Places
                Population Groupings
                Age Groups
                Elderly
                Engineering and Technology
                Management Engineering
                Risk Management
                Insurance
                Social Sciences
                Economics
                Health Economics
                Health Insurance
                Medicine and Health Sciences
                Health Care
                Health Economics
                Health Insurance
                People and Places
                Geographical Locations
                Asia
                Japan
                Medicine and Health Sciences
                Health Care
                Long-Term Care
                Earth Sciences
                Seasons
                Medicine and Health Sciences
                Health Care
                Patients
                Outpatients
                Custom metadata
                To protect participant privacy, public data sharing has been restricted by the Ethics Committee of the University of Tokyo and the government administration of City A. Qualified researchers may request data access by emailing the research center at kenkyu@ 123456j.iwate-med.ac.jp .

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                Uncategorized

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