Development and External Validation of Models to Predict Need for Nursing Home Level of Care in Community-Dwelling Older Adults With Dementia

Author:

Deardorff W. James12,Jeon Sun Y.12,Barnes Deborah E.34,Boscardin W. John123,Langa Kenneth M.5678,Covinsky Kenneth E.19,Mitchell Susan L.1011,Lee Sei J.12,Smith Alexander K.12

Affiliation:

1. Division of Geriatrics, Department of Medicine, University of California, San Francisco

2. Geriatrics, Palliative and Extended Care Service Line, San Francisco Veterans Affairs Health Care System, San Francisco, California

3. Department of Epidemiology and Biostatistics, University of California, San Francisco

4. Department of Psychiatry and Behavioral Sciences, University of California, San Francisco

5. Department of Internal Medicine, School of Medicine, University of Michigan, Ann Arbor

6. Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor

7. Veterans Affairs Ann Arbor Center for Clinical Management Research, Ann Arbor, Michigan

8. Institute for Social Research, University of Michigan, Ann Arbor

9. Associate Editor, JAMA Internal Medicine

10. Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, Massachusetts

11. Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts

Abstract

ImportanceMost older adults living with dementia ultimately need nursing home level of care (NHLOC).ObjectiveTo develop models to predict need for NHLOC among older adults with probable dementia using self-report and proxy reports to aid patients and family with planning and care management.Design, Setting, and ParticipantsThis prognostic study included data from 1998 to 2016 from the Health and Retirement Study (development cohort) and from 2011 to 2019 from the National Health and Aging Trends Study (validation cohort). Participants were community-dwelling adults 65 years and older with probable dementia. Data analysis was conducted between January 2022 and October 2023.ExposuresCandidate predictors included demographics, behavioral/health factors, functional measures, and chronic conditions.Main Outcomes and MeasuresThe primary outcome was need for NHLOC defined as (1) 3 or more activities of daily living (ADL) dependencies, (2) 2 or more ADL dependencies and presence of wandering/need for supervision, or (3) needing help with eating. A Weibull survival model incorporating interval censoring and competing risk of death was used. Imputation-stable variable selection was used to develop 2 models: one using proxy responses and another using self-responses. Model performance was assessed by discrimination (integrated area under the receiver operating characteristic curve [iAUC]) and calibration (calibration plots).ResultsOf 3327 participants with probable dementia in the Health and Retirement Study, the mean (SD) age was 82.4 (7.4) years and 2301 (survey-weighted 70%) were female. At the end of follow-up, 2107 participants (63.3%) were classified as needing NHLOC. Predictors for both final models included age, baseline ADL and instrumental ADL dependencies, and driving status. The proxy model added body mass index and falls history. The self-respondent model added female sex, incontinence, and date recall. Optimism-corrected iAUC after bootstrap internal validation was 0.72 (95% CI, 0.70-0.75) in the proxy model and 0.64 (95% CI, 0.62-0.66) in the self-respondent model. On external validation in the National Health and Aging Trends Study (n = 1712), iAUC in the proxy and self-respondent models was 0.66 (95% CI, 0.61-0.70) and 0.64 (95% CI, 0.62-0.67), respectively. There was excellent calibration across the range of predicted risk.Conclusions and RelevanceThis prognostic study showed that relatively simple models using self-report or proxy responses can predict need for NHLOC in community-dwelling older adults with probable dementia with moderate discrimination and excellent calibration. These estimates may help guide discussions with patients and families in future care planning.

Publisher

American Medical Association (AMA)

Subject

Internal Medicine

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3