Predictive Model Development and Validation of the Emergency Hester Davis Scale© for Fall Risk Screening

Stella Kientz,1 Amy Hester2 1Regional Accreditation, Regulatory & Licensing, Kaiser Permanente, Pasadena, CA, USA; 2Center for Nursing Excellence, University of Arkansas for Medical Sciences, Little Rock, AR, USACorrespondence: Amy Hester Email hesteramyl@uams.eduIntroduction: Falls are amon...

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Autores principales: Kientz S, Hester A
Formato: article
Lenguaje:EN
Publicado: Dove Medical Press 2020
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Acceso en línea:https://doaj.org/article/defbf2be8e3147b288a689a95a8bc6f5
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Sumario:Stella Kientz,1 Amy Hester2 1Regional Accreditation, Regulatory & Licensing, Kaiser Permanente, Pasadena, CA, USA; 2Center for Nursing Excellence, University of Arkansas for Medical Sciences, Little Rock, AR, USACorrespondence: Amy Hester Email hesteramyl@uams.eduIntroduction: Falls are among the most serious adverse events in healthcare. Patients presenting to the emergency department may be at risk for falls due to various conditions. The ability for clinicians to quickly and accurately determine fall risk is vital to the implementation of appropriate fall prevention efforts.Methods: A secondary data analysis was used to construct the initial emergency Hester Davis Scale (eHDS) fall risk screening model. The model was first retrospectively developed and then prospectively validated concurrently in an urban academic medical center in the south-central United States and in a large, urban emergency department (ED) on the west coast of the United States. The retrospective sample included 152 fallers. The prospective sample included 13 fallers and a random sample of 216 non-fallers. Statistical analyses included descriptive statistics, sensitivity, specificity, and receiver operating characteristic (ROC) curve procedures.Results: Retrospective analysis of data including 152 ED fallers experiencing anticipated physiologic events revealed three salient screening variables including mobility, medications, and behavior. Prospective data included a random sample of 216 non-fallers and 13 fallers from the two participating hospitals from 110,445 combined ED visits. The derived tool correctly identified risk in all 13 anticipated physiologic falls. The use and interpretation of the ROC curve analysis contributed to further evaluation.Discussion: The eHDS can accurately identify adults at risk for falling in the ED and can be the first step in preventing falls and subsequent fall-related costs.Keywords: accidental falls/prevention and control, health risk assessment, emergency room nursing, emergency departments