From framework to frontline: Embedding enterprise risk management into emergency department fall prevention

This letter to the editor responds to Bailey and Delchamps' recent article on integrating enterprise risk management (ERM) in fall-related injury prevention. We extend their framework to emergency departments (EDs), emphasizing the strategic advantage of initiating individualized fall risk assessment at the point of triage. Many high-risk indicators-such as anticoagulant use and cognitive impairment-are already accessible in ED settings and can be embedded into machine learning-supported tools like the Rothman index or fall triage score. We also highlight the financial implications of fall-related injuries originating in or near the ED, noting their potential to increase hospital length of stay and trigger non-reimbursable costs. The authors' inclusion of risk matrices and heat maps presents scalable opportunities for safety prioritization in dynamic ED environments. We conclude by recommending prospective validation of ERM-based approaches within level 1 trauma centers and invite collaboration to test the framework's effectiveness in real-world emergency settings.

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Publication Details

Journal
Journal of Healthcare Risk Management
Published
2025-09-17
DOI
https://doi.org/10.1002/jhrm.70012
Primary Topic
Emergency and Acute Care Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

From framework to frontline: Embedding enterprise risk management into emergency department fall prevention

Ömer Faruk Karakoyun, Yalçın Gölcük
Journal of Healthcare Risk Management
Emergency and Acute Care Studies
article

From framework to frontline: Embedding enterprise risk management into emergency department fall prevention

Ömer Faruk Karakoyun, Yalçın Gölcük
article en

Abstract

This letter to the editor responds to Bailey and Delchamps' recent article on integrating enterprise risk management (ERM) in fall-related injury prevention. We extend their framework to emergency departments (EDs), emphasizing the strategic advantage of initiating individualized fall risk assessment at the point of triage. Many high-risk indicators-such as anticoagulant use and cognitive impairment-are already accessible in ED settings and can be embedded into machine learning-supported tools like the Rothman index or fall triage score. We also highlight the financial implications of fall-related injuries originating in or near the ED, noting their potential to increase hospital length of stay and trigger non-reimbursable costs. The authors' inclusion of risk matrices and heat maps presents scalable opportunities for safety prioritization in dynamic ED environments. We conclude by recommending prospective validation of ERM-based approaches within level 1 trauma centers and invite collaboration to test the framework's effectiveness in real-world emergency settings.

Journal of Healthcare Risk ManagementVol. 45(2)
Muğla University (TR)
Openalex Percentile: Top 62%
Emergency and Acute Care Studies
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