Validation of the Hendrich II Fall Risk Model: The imperative to reduce modifiable risk factors.
Fall risk factors
Hendrich II Fall Risk Model
Injurious fall risk reduction
Inpatient falls
Journal
Applied nursing research : ANR
ISSN: 1532-8201
Titre abrégé: Appl Nurs Res
Pays: United States
ID NLM: 8901557
Informations de publication
Date de publication:
06 2020
06 2020
Historique:
received:
02
09
2019
revised:
06
02
2020
accepted:
15
02
2020
entrez:
27
5
2020
pubmed:
27
5
2020
medline:
16
6
2021
Statut:
ppublish
Résumé
To validate the psychometrics of the Hendrich II Fall Risk Model (HIIFRM) and identify the prevalence of intrinsic fall risk factors in a diverse, multisite population. Injurious inpatient falls are common events, and hospitals have implemented programs to achieve "zero" inpatient falls. Retrospective analysis of patient data from electronic health records at nine hospitals that are part of Ascension. Participants were adult inpatients (N = 214,358) consecutively admitted to the study hospitals from January 2016 through December 2018. Fall risk was assessed using the HIIFRM on admission and one time or more per nursing shift. Overall fall rate was 0.29%. At the standard threshold of HIIFRM score ≥ 5, 492 falls and 76,800 non-falls were identified (fall rate 0.36%; HIIFRM specificity 64.07%, sensitivity 78.72%). Area under the receiver operating characteristic curve was 0.765 (standard error 0.008; 95% confidence interval 0.748, 0.781; p < 0.001), indicating moderate accuracy of the HIIFRM to predict falls. At a lower cut-off score of ≥4, an additional 74 falls could have been identified, with an improvement in sensitivity (90.56%) and reduction in specificity (44.43%). Analysis of this very large inpatient sample confirmed the strong psychometric characteristics of the HIIFRM. The study also identified a large number of inpatients with multiple fall risk factors (n = 77,292), which are typically not actively managed during hospitalization, leaving patients at risk in the hospital and after discharge. This finding represents an opportunity to reduce injurious falls through the active management of modifiable risk factors.
Sections du résumé
AIM
To validate the psychometrics of the Hendrich II Fall Risk Model (HIIFRM) and identify the prevalence of intrinsic fall risk factors in a diverse, multisite population.
BACKGROUND
Injurious inpatient falls are common events, and hospitals have implemented programs to achieve "zero" inpatient falls.
METHODS
Retrospective analysis of patient data from electronic health records at nine hospitals that are part of Ascension. Participants were adult inpatients (N = 214,358) consecutively admitted to the study hospitals from January 2016 through December 2018. Fall risk was assessed using the HIIFRM on admission and one time or more per nursing shift.
RESULTS
Overall fall rate was 0.29%. At the standard threshold of HIIFRM score ≥ 5, 492 falls and 76,800 non-falls were identified (fall rate 0.36%; HIIFRM specificity 64.07%, sensitivity 78.72%). Area under the receiver operating characteristic curve was 0.765 (standard error 0.008; 95% confidence interval 0.748, 0.781; p < 0.001), indicating moderate accuracy of the HIIFRM to predict falls. At a lower cut-off score of ≥4, an additional 74 falls could have been identified, with an improvement in sensitivity (90.56%) and reduction in specificity (44.43%).
CONCLUSION
Analysis of this very large inpatient sample confirmed the strong psychometric characteristics of the HIIFRM. The study also identified a large number of inpatients with multiple fall risk factors (n = 77,292), which are typically not actively managed during hospitalization, leaving patients at risk in the hospital and after discharge. This finding represents an opportunity to reduce injurious falls through the active management of modifiable risk factors.
Identifiants
pubmed: 32451003
pii: S0897-1897(19)30621-4
doi: 10.1016/j.apnr.2020.151243
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
151243Informations de copyright
Copyright © 2020 Elsevier Inc. All rights reserved.