Premium
Deriving a Risk‐Adjustment Model for Pressure Ulcer Development Using the Minimum Data Set
Author(s) -
Berlowitz Dan R.,
Brandeis Gary H.,
Morris John N.,
Ash Arlene S.,
Anderson Jennifer J.,
Kader Boris,
Moskowitz Mark A.
Publication year - 2001
Publication title -
journal of the american geriatrics society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.992
H-Index - 232
eISSN - 1532-5415
pISSN - 0002-8614
DOI - 10.1046/j.1532-5415.2001.49175.x
Subject(s) - medicine , minimum data set , logistic regression , body mass index , risk assessment , bivariate analysis , intensive care medicine , nursing homes , statistics , nursing , mathematics , computer security , computer science
OBJECTIVE: To use the Minimum Data Set (MDS) to derive a risk‐adjustment model for pressure ulcer development that may be used in assessing the quality of nursing home care. DESIGN: Perspective observational study using MDS data from 1997. SETTING: A large, for‐profit, nursing home chain. PARTICIPANTS: Our unit of analysis was 39,649 observations made on 14,607 nursing home residents who were without a stage 2 or larger pressure ulcer on an index assessment. MEASUREMENTS: Pressure ulcer status was determined at an outcome assessment approximately 90 days after an index assessment. Potential predictors of pressure ulcer development were examined for bivariate associations, contributing to the development of a multivariate logistic regression model. RESULTS: A stage 2 or larger pressure ulcer developed in 2.3% of the observations. Seventeen resident characteristics were found to be associated with pressure ulcer development. These included dependence in mobility and transferring, diabetes mellitus, peripheral vascular disease, urinary incontinence, lower body mass index, and end‐stage disease. A risk‐adjustment model based on these characteristics was well calibrated and able to discriminate among residents with different levels of risk for ulcer development (model c‐statistic = 0.73). CONCLUSION: A clinically credible risk‐adjustment model with good performance properties can be developed using the MDS. This model may be useful in profiling nursing homes on their rate of pressure ulcer development.