title: Combinations of long-term care insurance services and associated factors in Japan: a classification tree model.
abstract: BACKGROUND
  To develop a quality community-based care management system, it is important to identify the actual use of long-term care insurance (LTCI) services and the most frequent combinations of services. It is also important to determine the factors associated with the use of such combinations.
  
  
  METHODS
  This study was conducted in 10 care management agencies in the urban area around Tokyo, Japan. The assessment and services data of 983 clients using the Minimum Data Set for Home Care were collected from the agencies. We categorized combination patterns of services from descriptive data analysis of service use and conducted chi-squared automatic interaction detection (CHAID) analysis to identify the primary variables determining the combinations of the services used.
  
  
  RESULTS
  We identified nine patterns of service use: day care only (16.5%); day care and assistive devices (14.4%); day care, home helper, and assistive devices (13.2%); home helper and assistive devices (11.8%); assistive devices only (10.9%); home helper only (8.7%); day care and home helper (7.7%); home helper, visiting nurse, and assistive devices (5.4%); and others (11.3%). The CHAID dendrogram illustrated the relative importance of significant independent variables in determining combination use; the most important variables in predicting combination use were certified care need level, living arrangements, cognitive function, and need for medical procedures. The characteristics of care managers and agencies were not associated with the combinations.
  
  
  CONCLUSIONS
  This study clarified patterns of community-based service use in the LTCI system in Japan. The combinations of services were more related to the physical and psychosocial status of older adults than to the characteristics of agencies and care managers. Although we found no association between service use and the characteristics of agencies and care managers, further examination of possible bias in the use of services should be included in future studies. Researchers and policymakers can use these combinations identified in this study to categorize the use of community-based care service and measure the outcomes of care interventions.
authors.affiliation: School of Health Sciences & Nursing, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan. igarashi-a@umin.ac.jp.
authors.forename: Ayumi
authors.initials: A
authors.lastname: Igarashi
authors.forename: Tomoaki
authors.initials: T
authors.lastname: Ishibashi
authors.forename: Tomohiro
authors.initials: T
authors.lastname: Shinozaki
authors.forename: Noriko
authors.initials: N
authors.lastname: Yamamoto-Mitani
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D016009:Chi-Square Distribution; D019058:Community Networks; D016208:Databases, Factual; D005260:Female; D006296:Health Services / Q000706:statistics & numerical data*; D006801:Humans; D007353:Insurance, Long-Term Care / Q000706:statistics & numerical data*; D008134:Long-Term Care / Q000145:classification / Q000706:statistics & numerical data*; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D011795:Surveys and Questionnaires; D014041:Tokyo; D014505:Urban Population; D055815:Young Adult