Quality evaluation of the usefulness of an emergency department fall risk assessment tool

被引:0
作者
Ortenzio, Mark P. [1 ,5 ]
Brittain, Garrett V. [1 ]
Frommeyer, Timothy C. [1 ]
Muwanga, David P. [1 ]
Stol, Adrienne [2 ]
Parikh, Priti P. [3 ]
O'Malley, Patricia A. [4 ]
机构
[1] Wright State Univ, Boonshoft Sch Med, Dayton, OH USA
[2] Wright State Univ, Boonshoft Sch Med, Dept Pediat, Dayton, OH USA
[3] Wright State Univ, Boonshoft Sch Med, Dept Surg, Dayton, OH USA
[4] Miami Valley Hosp, Premier Hlth, Ctr Nursing Excellence, Dayton, OH USA
[5] Wright State Univ, Boonshoft Sch Med, 3640 Colonel Glenn Hwy, Dayton, OH 45435 USA
关键词
Falls; Fall risk; Fall risk assessment; Emergency department;
D O I
10.1016/j.ajem.2023.10.033
中图分类号
R4 [临床医学];
学科分类号
1002 ; 100602 ;
摘要
Introduction: Falls that occur within a hospital setting are difficult to predict, however, are preventable adverse events with the potential to negatively impact patient care. Falls have the potential to cause serious or fatal inju-ries and may increase patient morbidity. Many hospitals utilize fall "predictor tools" to categorize a patient's fall risk, however, these tools are primarily studied within in-patient units. The emergency department (ED) pre-sents a unique environment with a distinct patient population and demographic. The Memorial Emergency De-partment Fall Risk Assessment Tool (MEDFRAT) has shown to be effective with predicting a patient's fall risk in the ED. This IRB-approved study aims to assess the predictive validity of the MEDFRAT by evaluating the sensi-tivity and specificity for predicting a patient's fall risk in an emergency department at a level 1 trauma center.Methods: A retrospective cohort analysis was conducted using an electronic medical record (EMR) for patients who met study inclusion criteria at a level 1 trauma center ED. Extracted data includes MEDFRAT components, demographic information, and data from the Moving Safely Risk Assessment (MSRA) Tool, our institution's cur-rent fall assessment tool. A receiver operating characteristic (ROC) curve was constructed to determine the best cutoff for identifying any fall risk. Sensitivity, specificity, accuracy, positive likelihood ratio (LR+) and negative LR (LR-), with 95% CIs were then calculated for the cutoff value determined from the ROC curve. To compare overall tool performance, the areas under the ROC curves (AUC) were determined and compared with a z-test.Results: The MEDFRAT had a significantly higher sensitivity compared to the MSRA (83.1% vs. 66.1%, p = 0.002), while the MSRA had a significantly higher specificity (84.5% vs. 69.0%, p = 0.012). For identifying any level of fall risk, ROC curve analysis showed that the cutoff providing the best trade-off between sensitivity and specificity for the MEDFRAT was a score of >= 1. Additionally, area under the curve was determined for the MEDFRAT and MSRA (0.817 vs. 0.737).Conclusion: This study confirms the validity of the MEDFRAT as an acceptable tool to predict in-hospital falls in a level 1 trauma center ED. Accurate identification of patients at a high risk of falling is critical for decreasing healthcare costs and improving health outcomes and patient safety.(c) 2023 Elsevier Inc. All rights reserved.
引用
收藏
页码:93 / 98
页数:6
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