Development of a predictive model using the Kihon Checklist for older adults at risk of needing long-term care based on cohort data of 19 months.

AIM

This study developed a risk scoring tool and examined its applicability using data from the Kihon Checklist cohort dataset for 19 months to predict the transition from no certification for long-term care to long-term care level 3 or above.

METHODS

Data were collected from 26 357 functionally independent, community-dwelling older adults in a Japanese city who answered the Checklist in 2014 and were followed for 19 months. Individuals certified for long-term care during the follow-up period were classified into three levels depending on their certification status: low, moderate, and high long-term care levels. Relationships between the Kihon Checklist domains and high long-term care levels were examined using the logistic regression model. A score chart predicting incidents of high long-term care levels was created to facilitate its applicability.

RESULTS

As of 2016, 971 participants were certified for long-term care (3.7%), of which 168 (0.6%), 357 (1.4%), and 446 (1.7%) were certified as high, moderate, and low long-term care levels, respectively. Variables associated with the certification of high long-term care level included difficulties in activities of daily living, a decline in locomotor and cognitive function in the Kihon Checklist domains, and age. The score chart was created based on these variables and demonstrated excellent discriminatory ability, with an area under curve of 0.817 (95% confidence interval: 0.785-0.849).

CONCLUSIONS

The Kihon Checklist can predict the future development of a high degree of dependency. The score chart we developed can be easily implemented to identify older adults at high risk with reasonable accuracy. Geriatr Gerontol Int 2022; 22: 797-802.