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Kennedy, Maura

Mayo Clinic

Massachusetts General Hospital

Citations 2

Electronic Health Record Tools for the Detection, Management, and Monitoring of Delirium in Emergency Departments: Examples from Five Healthcare Systems
Kennedy, Maura, Skains, Rachel M. , Bhananker, Annika , Peebles, Alex, Schneider, Katherine A., Liu, Shan W. , Skains, Rachel M , Chary, Anita Nandkumar , Southerland, Lauren T. , Friedman, Ari B. , Lee, Sangil , Schneider, Katherine, Bellolio, Fernanda

Delirium | August 8, 2025 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.56392/001c.142177 Get It

Background Delirium is a state of acute brain failure causing confusion, reduced focus, and changes in alertness. It is common in older patients, occurring in 6-38% of older emergency department (ED) patients. Evidence suggests that systematic screening improves detection rates and early detection, management and reporting are critical. However, examples of operationalizing this in clinical non-research care are scarce. Objective To describe and disseminate examples of best practices for delirium screening, management, and monitoring within the ED. Methods A group of emergency physicians interested in geriatric emergency medicine (GEM) and evidence-based medicine gathered monthly to discuss ways of implementing delirium care. Members were asked to submit any electronic health record (EHR)-based interventions for delirium in current use at their institutions. One group member categorized the EHR tools by their use for screening, prevention, management, and monitoring of delirium. As a group, categorizations were reviewed and agreed upon and similarities, differences and themes were identified. Results Current EHR interventions from 5 EDs were included. We found that: 1) Screening for delirium in EDs is challenging due to the nature of the environment and the variety of tools available. 2) Prevention tools included order sets. 3) Management was accomplished with best practice alerts and order sets to help screen, prevent, address underlying causes, and manage agitation. Delirium prevention order sets emphasize optimizing patient mobility, comfort, and communication. Assessment order sets include routine labs and consultations, while management order sets for agitation provide safe medication options considering older adults’ unique physiology. 4) Utilizing dashboards for compliance monitoring offers real-time feedback, and provides an overview of adherence to clinical guidelines, regulatory standards, and patient safety protocols. Conclusion These real-world examples can be used in EDs implementing delirium programs. Further studies on how EHR interventions impact screening, diagnosis, and treatment of delirium in the ED are needed.
Delirium detection in the emergency department: A diagnostic accuracy meta‐analysis of history, physical examination, laboratory tests, and screening instruments
Carpenter, Christopher R. , Lee, Sangil , Kennedy, Maura, Arendts, Glenn , Schnitker, Linda , Eagles, Debra , Fowler, Susan A. , Doering, Michelle , LaMantia, Michael A., Han, Jin H. , Liu, Shan W. , Han, Jin H , Liu, Shan W , Carpenter, Christopher R , Lee, Sangil , Mooijaart, Simon P.

Academic Emergency Medicine | May 17, 2024 | Volume: 31 | Issue: 10 | Pages: 1014-1036

10.1111/acem.14935 Get It

Abstract Introduction Geriatric emergency department (ED) guidelines emphasize timely identification of delirium. This article updates previous diagnostic accuracy systematic reviews of history, physical examination, laboratory testing, and ED screening instruments for the diagnosis of delirium as well as test–treatment thresholds for ED delirium screening. Methods We conducted a systematic review to quantify the diagnostic accuracy of approaches to identify delirium. Studies were included if they described adults aged 60 or older evaluated in the ED setting with an index test for delirium compared with an acceptable criterion standard for delirium. Data were extracted and studies were reviewed for risk of bias. When appropriate, we conducted a meta‐analysis and estimated delirium screening thresholds. Results Full‐text review was performed on 55 studies and 27 were included in the current analysis. No studies were identified exploring the accuracy of findings on history or laboratory analysis. While two studies reported clinicians accurately rule in delirium, clinician gestalt is inadequate to rule out delirium. We report meta‐analysis on three studies that quantified the accuracy of the 4 A's Test (4AT) to rule in (pooled positive likelihood ratio [LR+] 7.5, 95% confidence interval [CI] 2.7–20.7) and rule out (pooled negative likelihood ratio [LR−] 0.18, 95% CI 0.09–0.34) delirium. We also conducted meta‐analysis of two studies that quantified the accuracy of the Abbreviated Mental Test‐4 (AMT‐4) and found that the pooled LR+ (4.3, 95% CI 2.4–7.8) was lower than that observed for the 4AT, but the pooled LR− (0.22, 95% CI 0.05–1) was similar. Based on one study the Confusion Assessment Method for the Intensive Care Unit (CAM‐ICU) is the superior instrument to rule in delirium. The calculated test threshold is 2% and the treatment threshold is 11%. Conclusions The quantitative accuracy of history and physical examination to identify ED delirium is virtually unexplored. The 4AT has the largest quantity of ED‐based research. Other screening instruments may more accurately rule in or rule out delirium. If the goal is to rule in delirium then the CAM‐ICU or brief CAM or modified CAM for the ED are superior instruments, although the accuracy of these screening tools are based on single‐center studies. To rule out delirium, the Delirium Triage Screen is superior based on one single‐center study.