
Psychiatr Serv 60:1245-1250, September 2009
doi: 10.1176/appi.ps.60.9.1245
© 2009 American Psychiatric Association
Predicting Falls Among Psychiatric Inpatients: A Case-Control Study at a State Psychiatric Facility
Irene Estrin, R.N.,
Raymond Goetz, Ph.D.,
David J. Hellerstein, M.D.,
Amy Bennett-Staub, R.N., M.P.A. and
Gretchen Seirmarco, D.M.H., A.P.R.N.
The authors are affiliated with the Department of Psychiatry, New York State Psychiatric Institute, 1051 Riverside Dr., New York, NY 10032 (e-mail: estrini{at}pi.cpmc.columbia.edu).
OBJECTIVE: The purpose of the study was to add to the research on risk of falling in an understudied population of psychiatric inpatients in an acute setting. METHODS: Five years of fall data in an inpatient psychiatric facility, where falls were frequent but benign, were examined for patient and treatment characteristics that might be associated with falls. This was a retrospective analysis, which matched 1:1 the medical records of fallers and nonfallers on primary psychiatric diagnoses. The total sample consisted of 148 patients. Statistical analysis was conducted on patient demographic characteristics, summed medical history items reported, summed physical complaints on the day of the fall, the number and types of medications taken within a 24-hour period of the fall, and the patient's vital signs. Multivariate logistic regression was used to identify the most salient associations with faller status. RESULTS: Univariate analyses revealed that fallers were prescribed significantly more medications and complained of more physical symptoms on the day of their fall. Fallers were more likely to have a current acute medical condition and to be currently prescribed clonazepam or antihypertensive medication. Multivariate logistic regression analysis revealed that current physical complaints and current clonazepam treatment had significant associations with faller status. CONCLUSIONS: Risk factors identified in this study should be assessed in replication studies. Psychiatric clinicians can use such risk factors to create evidence-based fall prevention programs.
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