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Researchers at University of Tsukuba have clarified the characteristics and prognoses of elderly people (≥65 years old) who have recently started using long-term care insurance services in Japan. The users have been grouped according to disease patterns. The findings are expected to contribute to the development of intervention methods tailored to each group and improve the quality and efficiency of healthcare services.

Tsukuba, Japan—As the population continues to age, improving the quality and efficiency of healthcare services for older adults has become increasingly important. However, the older adult population is diverse, often suffering from multiple diseases and various combinations of diseases. Developing appropriate intervention methods for this diverse demographic is challenging. Using unsupervised machine learning techniques, the researchers classified individuals aged 65 years or older who had started using long-term care into clinical types based on 22 diseases. The individuals were newly enrolled in long-term care insurance services in Tsukuba City in Ibaraki Prefecture and Sammu City in Chiba Prefecture. The researchers examined the association between the classification (called the "clinical subtype") and prognosis by clinical subtype.

Six clinical subtypes were identified in Tsukuba City: i. Musculoskeletal and sensory diseases, ii. Cardiac diseases, iii. Neurological diseases, iv. Respiratory diseases and cancers, v. Insulin-dependent diabetes, and vi. Others. The same classification was reproduced after analyzing the data from Sammu City.

In terms of prognosis, cardiac disease, respiratory disease/cancer, and insulin-dependent diabetes were found to incur a higher mortality risk than musculoskeletal and sensory diseases. Furthermore, cardiac disease, respiratory disease/cancer, and others were associated with a worsening care-need level.

The findings of this study are relevant not only to individuals requiring care but also to their families and staff(s) involved in their care. The research and development of optimal interventions for each clinical subtype identified in this study could also influence healthcare policy.

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This work was supported by a grant-in-aid from the Health Care Science Institute Research Grant in 2023, and the Ministry of Health, Labour and Welfare Policy Research Grants, Japan (Grant Number: 23AA2003).

Original Paper

Title of original paper:

Clinical subtypes of older adults starting long-term care in Japan and their association with prognoses: A data-driven cluster analysis

Journal:

Scientific Reports

DOI:

10.1038/s41598-024-65699-6

Correspondence

Professor TAMIYA Nanako
Research and Development Center for Health Services / Institute of Medicine, University of Tsukuba

Related Link

Research and Development Center for Health Services

Institute of Medicine