Estimating healthy life years without activity limitations using medical claims data in Japan.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος:	Estimating healthy life years without activity limitations using medical claims data in Japan.
Συγγραφείς:	Nishi M; Department of Cardiovascular Medicine, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan., Nagamitsu R; Department of Health and Welfare, Kyoto Prefectural Government, Kyoto, Japan.; Department of Epidemiology for Community Health and Medicine, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan., Morita S; Department of Health and Welfare, Kyoto Prefectural Government, Kyoto, Japan.; Department of Pulmonary Medicine, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan., Matoba S; Department of Cardiovascular Medicine, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Πηγή:	International journal of epidemiology [Int J Epidemiol] 2026 Jun 24; Vol. 55 (4).
Τύπος έκδοσης:	Journal Article
Γλώσσα:	English
Στοιχεία περιοδικού:	Publisher: Oxford University Press Country of Publication: England NLM ID: 7802871 Publication Model: Print Cited Medium: Internet ISSN: 1464-3685 (Electronic) Linking ISSN: 03005771 NLM ISO Abbreviation: Int J Epidemiol Subsets: MEDLINE
Imprint Name(s):	Original Publication: [London] Oxford University Press.
Ιατρικοί όροι (MeSH):	Life Expectancy* , Activities of Daily Living*, Japan/epidemiology ; Humans ; Male ; Female ; Aged ; Aged, 80 and over ; Machine Learning ; Middle Aged ; Insurance Claim Review ; Adult ; Young Adult ; Life Tables ; Adolescent ; Infant
Περίληψη:	Background: Healthy life years are estimated from national population surveys that assess limitations in daily activities. However, the infrequent timing and limited sample sizes hinder the timely and detailed assessment of regional health conditions. We aimed to develop a novel method to estimate municipal-level healthy life years without activity limitations by using medical claims data. Methods: We analysed medical claims data in Kyoto Prefecture, Japan. Outpatient data from May to July in 2016 and 2019 (n = 1 489 920) were used for development and data from the same period in 2022 (n = 739 236) were used for evaluation. A total of 5743 diagnostic codes were aggregated into 40 disease categories. A machine-learning model was employed to produce the probability of activity limitation, which was calibrated by using data from the Comprehensive Survey of Living Conditions and applied to derive age-specific prevalence rates. Healthy life years at the municipal level as of June 2022 were then estimated by incorporating a life table. Results: We observed variation in healthy life years among municipalities: 72.1 years across all regions for males, ranging from 67.3 to 75.2 years, and 75.8 years for females, ranging from 71.3 to 77.6 years. Regional disparities were also noted in the prevalence of diseases associated with activity limitations. Conclusion: This study provides the first robust, scalable method to estimate healthy life years without activity limitations at the municipal level by using real-world administrative data. Timely monitoring of regional healthy life years will support targeted health-promotion policies and contribute to reducing health disparities. (© The Author(s) 2026. Published by Oxford University Press on behalf of the International Epidemiological Association.)
Grant Information:	JP25ek0210219h0001 Foundation for Total Health Promotion, the Japan Agency for Medical Research and Development
Contributed Indexing:	Keywords: National Health Insurance; health disparities; healthy life expectancy; healthy life years; machine learning; medical claims data
Entry Date(s):	Date Created: 20260730 Date Completed: 20260730 Latest Revision: 20260801
Update Code:	20260801
PubMed Central ID:	PMC13421775
DOI:	10.1093/ije/dyag126
PMID:	42530585
Βάση Δεδομένων:	MEDLINE

Περιγραφή
ISSN:	1464-3685
DOI:	10.1093/ije/dyag126