[Predictors of Admission to Nursing Home in Care-Dependent People - A Longitudinal Secondary Data Analysis].

OBJECTIVE

To determine predictors of admission to nursing home by means of secondary data analysis of German statutory health insurance claims data and care needs assessments.

MATERIALS AND METHODS

A retrospective longitudinal analysis was conducted covering the period 2006-2016 and using routine data. Health insurance data and care needs assessment data for people who became care dependent in 2006 and who lived in their own homes were merged. Cox regression analyses were conducted to identify predictors of admission to a nursing home.

RESULTS

The study population comprised 48,892 persons. Dementia, cancer of the brain, cognitive impairment, antipsychotics prescriptions, hospitalized fractures, hospital stays over ten days, and higher age had the highest hazard ratios among the predictors.

CONCLUSIONS

Knowledge about the predictors serves to sensitize health care professionals in the care of people in need of care. It facilitates identification of care needs in community-dwelling persons at an increased risk of admission to a nursing home.