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Updated: Jun 2, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Classification tree model identifies home-based service needs of Japanese long-term care insurance consumers
Takashi Naruse1, Satoko Nagata, Atsuko Taguchi
1Department of Community Health Nursing, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan. takanaruse-tky@umin.ac.jp
Objectives:
To clarify care receivers' needs and unmet needs for home help or home nursing services during daytime and/or nighttime hours, and to identify the characteristic of elders who are most likely to need home care services.
Design And Sample:
We used a chi-squared automatic interaction detection technique to analyze data from 92 care management researchers, who interviewed 280 caregivers.
Measures:
Demographic information, assessments of the statuses and service needs of elders.
Results:
We found that care receivers had more unmet needs at night than during the day. Daytime home help was needed by elders who (1) lived alone or (2) lived with just one person and whose primary caregiver was not their wife. Nighttime home help was needed by those who required assistance eating, and whose primary caregiver was male. Daytime home nursing was needed by elders who (1) received medical treatment instead of day care or (2) did not receive medical treatment, but had difficulty eating. Nighttime home nursing was needed by those who had unstable illnesses and whose medical treatments continued during the night.
Conclusions:
Our findings may help public health nurses assess community needs in order to effectively and efficiently manage health care resources.
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