Long-Term Nursing Home Entry: A Prognostic Model for Older Adults with a Family or Unpaid Caregiver

Abstract

Objectives: To comprehensively examine factors associated with long-term nursing home (NH) entry from 6 domains of older adult and family caregiver risk from nationally representative surveys and develop a prognostic model and a simple scoring system for use in risk stratification.

Design: Retrospective observational study.

Setting: National Long-Term Care Surveys 1999 and 2004 and National Health and Aging Trends Study 2011 and linked caregiver surveys.

Participants: Community-living older adults receiving help with self-care disability and their primary family or unpaid caregiver (N=2,676).

Measurements: Prediction of long-term NH entry (>100 days or ending in death) by 24 months follow up, ascertained from Minimum Data Set assessments and dates of death from Medicare enrollment files. Risk factors were measured from survey responses.

Results: In total, 16.1% of older adults entered a NH. Our final model and risk scoring system includes 7 independent risk factors: older adult age (1 point/5 years), living alone (5 points), dementia (3 points), 3 or more of 6 self-care activities (2 points), caregiver age (45-64: 1 point, 65-74: 2 points, ≥75: 4 points), caregiver help with money management (2 points), and caregiver report of moderate (2 points) or high (4 points) strain. Using this model, participants were assigned to risk quintiles. Long-term NH entry was 7.0% in the lowest quintile (0-6 points), 20.4% in the middle 3 quintiles (7-14 points), and 30.9% in the highest quintile (15-22 points). The model was well calibrated and demonstrated moderate discrimination (c-statistic=0.670 in the original data, c-statistic=0.647 in bootstrapped samples, c-statistic=0.652 using the point-scoring system).

Conclusion: We developed a prognostic model and simple scoring system that may be used to stratify risk of long-term NH entry of community-living older adults. Our model may be useful for population health and policy applications.

Keywords: disability; nursing home entry; risk prediction.