Citation

McNeely HL, Thomason KK, Tong S. J. Pediatr. Nurs. 2018; ePub(ePub): ePub.

Affiliation

University of Colorado Anschutz Medical Campus, Pediatrics, School of Medicine, Biostatistics and Informatics, Colorado School of Public Health, 13001 E 17Th Place, AMC Building 500, Mail Stop C243, Aurora, CO 80045, United States. Electronic address: Suhong.Tong@ucdenver.edu.

Copyright

(Copyright © 2018, Elsevier Publishing)

DOI

10.1016/j.pedn.2018.02.010

PMID

29499905

Abstract

PURPOSE: Compare two pediatric fall risk assessment tools (I'M SAFE and Humpty Dumpty) used at the same organization to determine if one is better able to predict which patients fall. DESIGN AND METHODS: Retrospective data was obtained from patients admitted in 2014. Each patient who experienced a fall during hospitalization was matched with two non-fallers based on age and diagnosis. Logistic regression was performed to identify which tool more accurately determines fall risk and reliability testing was completed for the I'M SAFE tool.

RESULTS: Over 22,000 patient files were extracted for this study. One hundred seventy-seven falls were identified, seventy-one of them were intrinsic. Of those patients who fell, the majority were assessed to be at high risk for falls. There were too few falls during the study period using the Humpty Dumpty tool to assess and make formal conclusions. The results for the I'M SAFE tool were opposite of what was expected and showed an increased risk for falls for patients who scored low risk using this tool.

CONCLUSIONS: At completion of this study the data reflected that the I'M SAFE tool was not adequately predicting patients at greatest risk for intrinsic falls for this particular population. PRACTICE IMPLICATIONS: Further research on these tools is needed in other populations or across multiple sites. Additional work to adapt the tools may be necessary to better predict fall risk without over identifying high risk patients.

Copyright © 2018 Elsevier Inc. All rights reserved.

Language: en