Falls prediction using the nursing home minimum dataset.

ABSTRACT:

Objective

The purpose of the study was to develop and validate a model to predict the risk of experiencing a fall for nursing home residents utilizing data that are electronically available at the more than 15 000 facilities in the United States.

Materials and methods

The fall prediction model was built and tested using 2 extracts of data (2011 through 2013 and 2016 through 2018) from the Long-term Care Minimum Dataset (MDS) combined with drug data from 5 skilled nursing facilities. The model was created using a hybrid Classification and Regression Tree (CART)-logistic approach.

Results

The combined dataset consisted of 3985 residents with mean age of 77 years and 64% female. The model's area under the ROC curve was 0.668 (95% confidence interval: 0.643-0.693) on the

SUBMITTER: Boyce RD 

PROVIDER: S-EPMC9382393 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature