Citation

Potter P, Allen K, Costantinou E, Klinkenberg WD, Malen J, Norris T, O'Connor E, Roney W, Tymkew HH, Wolf L. Jt. Comm. J. Qual. Patient Saf. 2017; 43(8): 414-421.

Copyright

(Copyright © 2017, Joint Commission on Accreditation of Healthcare Organizations)

DOI

10.1016/j.jcjq.2017.05.003

PMID

28738987

Abstract

BACKGROUND: Sensor technology that dynamically identifies hospitalized patients' fall risk and detects and alerts nurses of high-risk patients' early exits out of bed has potential for reducing fall rates and preventing patient harm. During Phase 1 (August 2014-January 2015) of a previously reported performance improvement project, an innovative depth sensor was evaluated on two inpatient medical units to study fall characteristics. In Phase 2 (April 2015-January 2016), a combined depth and bed sensor system designed to assign patient fall probability, detect patient bed exits, and subsequently prevent falls was evaluated.

METHODS: Fall detection depth sensors remained in place on two medicine units; bed sensors used to detect patient bed exits were added on only one of the medicine units. Fall rates and fall with injury rates were evaluated on both units.

RESULTS: During Phase 2, the designated evaluation unit had 14 falls, for a fall rate of 2.22 per 1,000 patient-days-a 54.1% reduction compared with the Phase 1 fall rate. The difference in rates from Phase 1 to Phase 2 was statistically significant (z = 2.20; p = 0.0297). The comparison medicine unit had 30 falls-a fall rate of 4.69 per 1,000 patient-days, representing a 57.9% increase as compared with Phase 1.

CONCLUSION: A fall detection sensor system affords a level of surveillance that standard fall alert systems do not have. Fall prevention remains a complex issue, but sensor technology is a viable fall prevention option.

Copyright © 2017 The Joint Commission. Published by Elsevier Inc. All rights reserved.

Language: en