Tokyo Metropolitan Institute of Gerontology, 35-2 Sakae-cho, Itabashi-Ku, Tokyo, 173-0015, Japan.
BMC Geriatr. 2021 Jan 7;21(1):22. doi: 10.1186/s12877-020-01968-z.
Predicting incidence of long-term care insurance (LTCI) certification in the short term is of increasing importance in Japan. The present study examined whether the Kihon Checklist (KCL) can be used to predict incidence of LTCI certification (care level 1 or higher) in the short term among older Japanese persons.
In 2015, the local government in Tokyo, Japan, distributed the KCL to all individuals older than 65 years who had not been certified as having a disability or who had already been certified as requiring support level 1-2 according to LTCI system. We also collected LTCI certification data within the 3 months after collecting the KCL data. The data of 17,785 respondents were analyzed. First, we selected KCL items strongly associated with incidence of LTCI certification, using stepwise forward-selection multiple logistic regression. Second, we conducted receiver operating characteristic (ROC) analyses for three conditions (1: Selected KCL items, 2: The main 20 KCL items (nos. 1-20), 3: All 25 KCL items). Third, we estimated specificity and sensitivity for each condition.
During a 3-month follow-up, 81 (0.5%) individuals required new LTCI certification. Eight KCL items were selected by multiple logistic regression as predictive of certification. The area under the ROC curve in the three conditions was 0.92-0.93, and specificity and sensitivity for all conditions were greater than 80%.
Three KCL conditions predicted short-term incidence of LTCI certification. This suggests that KCL items may be used to screen for the risk of incident LTCI certification.
在日本,短期预测长期护理保险(LTCI)认证的发生率变得越来越重要。本研究旨在探讨 Kihon Checklist(KCL)是否可用于预测短期内在日本老年人中 LTCI 认证(护理水平 1 或更高)的发生率。
2015 年,日本东京地方政府向所有未被认定为残疾或已根据 LTCI 系统被认定为需要 1-2 级支持的 65 岁以上的人分发了 KCL。我们还在收集 KCL 数据后的 3 个月内收集了 LTCI 认证数据。对 17785 名应答者的数据进行了分析。首先,我们使用逐步向前选择多变量逻辑回归选择与 LTCI 认证发生率密切相关的 KCL 项目。其次,我们对三种情况(1:选择的 KCL 项目,2:主要的 20 个 KCL 项目(编号 1-20),3:所有 25 个 KCL 项目)进行了接收者操作特征(ROC)分析。最后,我们估计了每种情况的特异性和敏感性。
在 3 个月的随访中,81 人(0.5%)需要新的 LTCI 认证。多变量逻辑回归选择了 8 个 KCL 项目作为认证的预测指标。在这三种情况下,ROC 曲线下的面积为 0.92-0.93,所有情况下的特异性和敏感性均大于 80%。
三种 KCL 情况预测了 LTCI 短期认证的发生率。这表明 KCL 项目可能用于筛选 LTCI 认证的风险。