Article

Valid comparison of patient outcomes of physical therapy care
requires risk adjustment for patient characteristics using statistical models.
Because patients are clustered within clinics, results of risk adjustment models
are likely to be biased by random, unobserved between-clinic differences. Such
bias could lead to inaccurate prediction and interpretation of outcomes.
The purpose of this study was to determine if including between-clinic variation
as a random effect would improve the performance of a risk adjustment model for
patient outcomes following physical therapy for low back dysfunction. DESIGN:
This was a secondary analysis of data from a longitudinal cohort of 147,623
patients with lumbar dysfunction receiving physical therapy in 1,470 clinics in
48 states of the United States. METHODS: Three linear mixed models predicting
patients' functional status (FS) at discharge, controlling for FS at intake, age,
sex, number of comorbidities, surgical history, and health care payer, were
developed. Models were: (1) a fixed-effect model, (2) a random-intercept model
that allowed clinics to have different intercepts, and (3) a random-slope model
that allowed different intercepts and slopes for each clinic. Goodness of fit,
residual error, and coefficient estimates were compared across the models.
RESULTS: The random-effect model fit the data better and explained an additional
11% to 12% of the between-patient differences compared with the fixed-effect
model. Effects of payer, acuity, and number of comorbidities were confounded by
random clinic effects. LIMITATIONS: Models may not have included some variables
associated with FS at discharge. The clinics studied may not be representative of
all US physical therapy clinics. CONCLUSIONS:
Risk adjustment models for
functional outcome of patients with lumbar dysfunction that control for
between-clinic variation performed better than a model that does not.
CI - (c) 2015 American Physical Therapy Association.

Langue : ANGLAIS