利用机器学习方法预测医疗保险受益人的认知功能障碍

IF 3.5 3区 医学 Q2 GERIATRICS & GERONTOLOGY
Zongliang Yue, Sara Jaradat, Jingjing Qian
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引用次数: 0

摘要

目标开发机器学习(ML)模型,以预测美国医疗保险受益人的认知障碍。方法这项回顾性研究使用了 2016-2019 年医疗保险当前受益人调查成本和使用情况以及调查公共使用档案。研究纳入了至少有连续两年数据的 65 岁及以上医疗保险受益人(4965 人)。根据自我报告的数据,认知障碍分为三个阶段:重度、中度和无。基线年的人口统计学、社会经济因素、自我报告的功能限制、健康状况和合并症、同时服用药物的数量、社会参与程度、行为变量和对医疗质量的满意度等特征,都在预测下一年认知功能的 ML 算法中进行了评估。我们使用 Python 3.11 版本开发、测试并比较了六大类 ML 模型(准确率、AUC 和 F1 分数)。特征的重要性通过基尼系数的总降幅进行评估。结果≥65 岁的受益人中约有 11.1%患有中度或重度认知功能障碍。基线认知功能是预测下一年认知功能障碍的最重要因素,其次是基线 IADL、社会活动水平、ADL、一般健康状况、收入、年龄、教育程度、居住地区和体重指数。结论老年人的基线认知功能和 IADL 是预测认知功能障碍的前两个重要因素。临床医生应定期筛查和监测老年人的认知和日常功能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prediction of cognitive impairment among Medicare beneficiaries using a machine learning approach

Objective

Developing machine learning (ML) models to predict cognitive impairment among Medicare beneficiaries in the United States.

Methods

This retrospective study used the 2016–2019 Medicare Current Beneficiary Survey Cost and Use and Survey Public Use Files. Medicare beneficiaries aged 65 and older (n=4,965) with at least two consecutive years’ data were included. Cognitive impairment was categorized into three stages: severe, moderate, and none based on self-reported data. Baseline year’s demographic, socioeconomic factors, self-reported functional limitations, health status and comorbidities, number of concurrent medications, level of social engagement, behavioral variables, and satisfaction of medical care’s quality were features assessed in ML algorithms to predict next years’ cognitive function. ML models in six major categories were developed, tested, and compared (accuracy, AUC, and F1 score) using Python version 3.11. The importance of features was evaluated using the total reduction of the Gini. A subgroup analysis was conducted among beneficiaries who were 80 years and older.

Results

Approximately 11.1% of beneficiaries aged ≥ 65 had moderate or severe cognitive function impairment. Baseline cognitive function was the most significant predictor for next year’s cognitive function impairment, followed by baseline IADL, level of social activities, ADL, general health status, income, age, education, region of residence, and body mass index. Beneficiaries 80 years and older had satisfaction of medical care’s quality among the top 10 most significant predictors.

Conclusions

Older adults’ baseline cognitive function and IADL were top two predictors of cognitive function impairment. Clinicians should regularly screen and monitor older adults’ cognitive and daily function.

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来源期刊
CiteScore
7.30
自引率
5.00%
发文量
198
审稿时长
16 days
期刊介绍: Archives of Gerontology and Geriatrics provides a medium for the publication of papers from the fields of experimental gerontology and clinical and social geriatrics. The principal aim of the journal is to facilitate the exchange of information between specialists in these three fields of gerontological research. Experimental papers dealing with the basic mechanisms of aging at molecular, cellular, tissue or organ levels will be published. Clinical papers will be accepted if they provide sufficiently new information or are of fundamental importance for the knowledge of human aging. Purely descriptive clinical papers will be accepted only if the results permit further interpretation. Papers dealing with anti-aging pharmacological preparations in humans are welcome. Papers on the social aspects of geriatrics will be accepted if they are of general interest regarding the epidemiology of aging and the efficiency and working methods of the social organizations for the health care of the elderly.
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