Patient-Representing Population's Perceptions of GPT-Generated Versus Standard Emergency Department Discharge Instructions: Randomized Blind Survey Assessment.

BACKGROUND: Discharge instructions are a key form of documentation and patient communication in the time of transition from the emergency department (ED) to home. Discharge instructions are time-consuming and often underprioritized, especially in the ED, leading to discharge delays and possibly impersonal patient instructions. Generative artificial intelligence and large language models (LLMs) offer promising methods of creating high-quality and personalized discharge instructions; however, there exists a gap in understanding patient perspectives of LLM-generated discharge instructions. OBJECTIVE: We aimed to assess the use of LLMs such as ChatGPT in synthesizing accurate and patient-accessible discharge instructions in the ED. METHODS: We synthesized 5 unique, fictional ED encounters to emulate real ED encounters that included a diverse set of clinician history, physical notes, and nursing notes. These were passed to GPT-4 in Azure OpenAI Service (Microsoft) to generate LLM-generated discharge instructions. Standard discharge instructions were also generated for each of the 5 unique ED encounters. All GPT-generated and standard discharge instructions were then formatted into standardized after-visit summary documents. These after-visit summaries containing either GPT-generated or standard discharge instructions were randomly and blindly administered to Amazon MTurk respondents representing patient populations through Amazon MTurk Survey Distribution. Discharge instructions were assessed based on metrics of interpretability of significance, understandability, and satisfaction. RESULTS: Our findings revealed that survey respondents' perspectives regarding GPT-generated and standard discharge instructions were significantly (P=.01) more favorable toward GPT-generated return precautions, and all other sections were considered noninferior to standard discharge instructions. Of the 156 survey respondents, GPT-generated discharge instructions were assigned favorable ratings, "agree" and "strongly agree," more frequently along the metric of interpretability of significance in discharge instruction subsections regarding diagnosis, procedures, treatment, post-ED medications or any changes to medications, and return precautions. Survey respondents found GPT-generated instructions to be more understandable when rating procedures, treatment, post-ED medications or medication changes, post-ED follow-up, and return precautions. Satisfaction with GPT-generated discharge instruction subsections was the most favorable in procedures, treatment, post-ED medications or medication changes, and return precautions. Wilcoxon rank-sum test of Likert responses revealed significant differences (P=.01) in the interpretability of significant return precautions in GPT-generated discharge instructions compared to standard discharge instructions but not for other evaluation metrics and discharge instruction subsections. CONCLUSIONS: This study demonstrates the potential for LLMs such as ChatGPT to act as a method of augmenting current documentation workflows in the ED to reduce the documentation burden of physicians. The ability of LLMs to provide tailored instructions for patients by improving readability and making instructions more applicable to patients could improve upon the methods of communication that currently exist.

Interrogating and Uprooting Systemic Racism in the Emergency Department.

This Viewpoint discusses how recognizing systemic racism in emergency departments will allow for the mitigation of racial and ethnic disparities and promote equitable treatment for all patients.

Accelerated Chest Pain Treatment With Artificial Intelligence-Informed, Risk-Driven Triage.

This quality improvement study evaluates the use of artificial intelligence to accelerate triage of patients presenting to the emergency department with chest pain.

Impact of the geriatric emergency medicine specialist intervention on final emergency department disposition.

BACKGROUND: The Geriatric Emergency Medicine Specialist (GEMS) pilot program is an innovative approach that utilizes geriatric-trained advanced practice providers to facilitate geriatric assessments and care planning for older adults in the emergency department (ED). The objective of this study was to explore the effect of GEMS on the use of observation status and final ED disposition. METHODS: This was a retrospective study under a target trial emulation framework. Geriatric patients (65+ years old) who presented to two ED sites within a large regional healthcare system between December 2020 and December 2022 were included. The primary outcome was final ED disposition (discharge, hospital inpatient admission, or hospital observation admission). Secondary outcomes included ED observation and ED length of stay. Non-GEMS patients were propensity score matched 5:1 to GEMS patients. Doubly robust regression was used to estimate the odds ratios and 95% confidence intervals of inpatient admission, discharge, hospital observation admission, ED observation admission, and estimate the mean ED length of stay. RESULTS: A total of 427 of 43,064 total patients (1.0%) received a GEMS intervention during the study period. Our analysis included 2,302 geriatric ED patients (410 GEMS, 1,892 non-GEMS) after propensity score matching. Hospital admission rates were 34.1% for GEMS compared to 56.4% for conventional treatment. GEMS patients had decreased odds of inpatient admission (OR: 0.41, 95 CI: 0.34-0.51, p < 0.001), increased odds of discharge (OR: 1.19 95 CI: 1.00-1.42, p = 0.047), hospital observation admission (OR: 2.97, 95 CI: 2.35-3.75, p < 0.001), ED observation admission (OR: 4.84 95 CI: 3.67-6.38, p < 0.001), and had a longer average ED length of stay (170 min, 95 CI: 84.6-256, p < 0.001) compared to non-GEMS patients. CONCLUSIONS: Patients seen by GEMS during their ED visit were associated with higher rates of hospital discharge and lower rates of hospital admissions.

Automated HEART score determination via ChatGPT: Honing a framework for iterative prompt development.

Objectives: This study presents a design framework to enhance the accuracy by which large language models (LLMs), like ChatGPT can extract insights from clinical notes. We highlight this framework via prompt refinement for the automated determination of HEART (History, ECG, Age, Risk factors, Troponin risk algorithm) scores in chest pain evaluation. Methods: We developed a pipeline for LLM prompt testing, employing stochastic repeat testing and quantifying response errors relative to physician assessment. We evaluated the pipeline for automated HEART score determination across a limited set of 24 synthetic clinical notes representing four simulated patients. To assess whether iterative prompt design could improve the LLMs' ability to extract complex clinical concepts and apply rule-based logic to translate them to HEART subscores, we monitored diagnostic performance during prompt iteration. Results: Validation included three iterative rounds of prompt improvement for three HEART subscores with 25 repeat trials totaling 1200 queries each for GPT-3.5 and GPT-4. For both LLM models, from initial to final prompt design, there was a decrease in the rate of responses with erroneous, non-numerical subscore answers. Accuracy of numerical responses for HEART subscores (discrete 0-2 point scale) improved for GPT-4 from the initial to final prompt iteration, decreasing from a mean error of 0.16-0.10 (95% confidence interval: 0.07-0.14) points. Conclusion: We established a framework for iterative prompt design in the clinical space. Although the results indicate potential for integrating LLMs in structured clinical note analysis, translation to real, large-scale clinical data with appropriate data privacy safeguards is needed.

Inequities among patient placement in emergency department hallway treatment spaces.

BACKGROUND: Limited capacity in the emergency department (ED) secondary to boarding and crowding has resulted in patients receiving care in hallways to provide access to timely evaluation and treatment. However, there are concerns raised by physicians and patients regarding a decrease in patient centered care and quality resulting from hallway care. We sought to explore social risk factors associated with hallway placement and operational outcomes. STUDY DESIGN/METHODS: Observational study between July 2017 and February 2020. Primary outcome was the adjusted odds ratio (aOR) of patient placement in a hallway treatment space adjusting for patient demographics and ED operational factors. Secondary outcomes included left without being seen (LWBS), discharge against medical advice (AMA), elopement, 72-h ED revisit, 10-day ED revisit and escalation of care during boarding. RESULTS: Among 361,377 ED visits, 100,079 (27.7%) visits were assigned to hallway beds. Patient insurance coverage (Medicaid (aOR 1.04, 95% CI 1.01,1.06) and Self-pay/Other (1.08, (1.03, 1.13))) with comparison to private insurance, and patient sex (Male (1.08, (1.06, 1.10))) with comparison to female sex are associated with higher odds of hallway placement but patient age, race, and language were not. These associations are adjusted for ED census, triage assigned severity, ED staffing, boarding level, and time effect, with social factors mutually adjusted. Additionally adjusting for patients' social factors, patients placed in hallways had higher odds of elopement (1.23 (1.07,1.41)), 72-h ED revisit (1.33 (1.08, 1.64)) and 10-day ED revisit (1.23 (1.11, 1.36)) comparing with patients placed in regular ED rooms. We did not find statistically significant associations between hallway placement and LWBS, discharge AMA, or escalation of care. CONCLUSION: While hallway usage is ad hoc, we find consistent differences in care delivery with those insured by Medicaid and self-pay or male sex being placed in hallway beds. Further work should examine how new front-end processes such as provider in triage or split flow may be associated with inequities in patient access to emergency and hospital care.

Correlations among common emergency medicine physician performance measures: Mixed messages or balancing forces?

The increasing complexity of ED physician performance measures has resulted in significant challenges, including duplicative and conflicting measures that fail to account for different ED settings. We performed a cross sectional analysis of correlations between measures to characterize their relationships and determine if differences exist between academic versus non-academic ED settings. Pearson correlations were calculated for 12 measures among 220 ED physicians at 11 EDs. Higher admission rate was strongly correlated with higher CT utilization rate (R = 0.7, p < 0.01) and longer room to discharge time (R = 0.7, p < 0.01). Higher patients per hour was strongly correlated with shorter room to doctor time (R = -0.7, p < 0.01). Stronger measure correlations were found in the academic setting compared to the non-academic setting. Strong correlations between ED measures imply opportunities to reduce competing performance demands on clinicians. Differences in correlations at academic versus non-academic settings suggest that it may be inappropriate to apply the same performance standards across settings.

Sociodemographic Disparities in Queue Jumping for Emergency Department Care.

Importance: Emergency department (ED) triage models are intended to queue patients for treatment. In the absence of higher acuity, patients of the same acuity should room in order of arrival. Objective: To characterize disparities in ED care access as unexplained queue jumps (UQJ), or instances in which acuity and first come, first served principles are violated. Design, Setting, and Participants: Retrospective, cross-sectional study between July 2017 and February 2020. Participants were all ED patient arrivals at 2 EDs within a large Northeast health system. Data were analyzed from July to September 2022. Exposure: UQJ was defined as a patient being placed in a treatment space ahead of a patient of higher acuity or of a same acuity patient who arrived earlier. Main Outcomes and Measures: Primary outcomes were odds of a UQJ and association with ED outcomes of hallway placement, leaving before treatment complete, escalation to higher level of care while awaiting inpatient bed placement, and 72-hour ED revisitation. Secondary analysis examined UQJs among high acuity ED arrivals. Regression models (zero-inflated Poisson and logistic regression) adjusted for patient demographics and ED operational variables at time of triage. Results: Of 314 763 included study visits, 170 391 (54.1%) were female, the mean (SD) age was 50.46 (20.5) years, 132 813 (42.2%) patients were non-Hispanic White, 106 401 (33.8%) were non-Hispanic Black, and 66 465 (21.1%) were Hispanic or Latino. Overall, 90 698 (28.8%) patients experienced a queue jump, and 78 127 (24.8%) and 44 551 (14.2%) patients were passed over by a patient of the same acuity or lower acuity, respectively. A total of 52 959 (16.8%) and 23 897 (7.6%) patients received care ahead of a patient of the same acuity or higher acuity, respectively. Patient demographics including Medicaid insurance (incident rate ratio [IRR], 1.11; 95% CI, 1.07-1.14), Black non-Hispanic race (IRR, 1.05; 95% CI, 1.03-1.07), Hispanic or Latino ethnicity (IRR, 1.05; 95% CI, 1.02-1.08), and Spanish as primary language (IRR, 1.06; 95% CI, 1.02-1.10) were independent social factors associated with being passed over. The odds of a patient receiving care ahead of others were lower for ED visits by Medicare insured (odds ratio [OR], 0.92; 95% CI, 0.88-0.96), Medicaid insured (OR, 0.81; 95% CI, 0.77-0.85), Black non-Hispanic (OR, 0.94; 95% CI, 0.91-0.97), and Hispanic or Latino ethnicity (OR, 0.87; 95% CI, 0.83-0.91). Patients who were passed over by someone of the same triage severity level had higher odds of hallway bed placement (OR, 1.01; 95% CI, 1.00-1.02) and leaving before disposition (OR, 1.02; 95% CI, 1.01-1.04). Conclusions and Relevance: In this cross-sectional study of ED patients in triage, there were consistent disparities among marginalized populations being more likely to experience a UQJ, hallway placement, and leaving without receiving treatment despite being assigned the same triage acuity as others. EDs should seek to standardize triage processes to mitigate conscious and unconscious biases that may be associated with timely access to emergency care.

Real-World Observational Evaluation of Common Interventions to Reduce Emergency Department Prescribing of Opioid Medications.

BACKGROUND: Prior work on opioid prescribing has examined dosing defaults, interruptive alerts, or "harder" stops such as electronic prescribing of controlled substances (EPCS), which has become increasingly required by state policy. Given that real-world opioid stewardship policies are concurrent and overlapping, the authors examined the effect of such policies on emergency department (ED) opioid prescriptions. METHODS: The researchers performed observational analysis of all ED visits discharged between December 17, 2016, and December 31, 2019, across seven EDs of a hospital system. Four interventions were examined in chronological order, with each successive intervention added on top of all previous interventions: 12-pill prescription default, EPCS, electronic health record (EHR) pop-up alert, and 8-pill prescription default. The primary outcome was opioid prescribing, which was described as number of opioid prescriptions per 100 discharged ED visits and modeled as a binary outcome for each visit. Secondary outcomes included prescription morphine milligram equivalents (MME) and non-opioid analgesia prescriptions. RESULTS: A total of 775,692 ED visits were included in the study. Compared to the preintervention period, cumulative reductions in opioid prescribing were seen with incremental interventions, including after adding a 12-pill default (odds ratio [OR] 0.88, 95% confidence interval [CI] 0.82-0.94), after adding EPCS (OR 0.7, 95% CI 0.63-0.77), after adding pop-up alerts (OR 0.67, 95% CI 0.63-0.71), and after adding an 8-pill default (OR 0.61, 95% CI 0.58-0.65). CONCLUSION: EHR-implemented solutions such as EPCS, pop-up alerts, and pill defaults had varying but significant effects on reducing ED opioid prescribing. Policy makers and quality improvement leaders might achieve sustainable improvements in opioid stewardship while balancing clinician alert fatigue through policy efforts promoting implementation of EPCS and default dispense quantities.

Exploratory Descriptive Analysis of Smart Speaker Utilization in the Emergency Department During the COVID-19 Pandemic.

BACKGROUND: In March 2020, the U.S. Department of Health and Human Services Office for Civil Rights stated that they would use discretion when enforcing the Health Insurance Portability and Accountability Act regarding remote communication technologies that promoted telehealth delivery during the COVID-19 pandemic. This was in an effort to protect patients, clinicians, and staff. More recently, smart speakers-voice-activated, hands-free devices-are being proposed as productivity tools within hospitals. OBJECTIVE: We aimed to characterize the novel use of smart speakers in the emergency department (ED). METHODS: A retrospective observational study of Amazon Echo Show® utilization from May 2020 to October 2020 in a large academic Northeast health system ED. Voice commands and queries were classified as either patient care-related or non-patient care-related, and then further subcategorized to explore the content of given commands. RESULTS: Of 1232 commands analyzed, 200 (16.23%) were determined to be patient care-related. Of these commands, 155 (77.5%) were clinical in nature (i.e., "drop in on triage") and 23 (11.5%) were environment-enhancing commands (i.e., "play calming sounds"). Among non-patient care-related commands, 644 (62.4%) were for entertainment. Among all commands, 804 (65.3%) were during night-shift hours, which was statistically significant (p < 0.001). CONCLUSIONS: Smart speakers showed notable engagement, primarily being used for patient communication and entertainment. Future studies should examine content of patient care conversations using these devices, effects on frontline staff wellbeing, productivity, patient satisfaction, and even explore opportunities for "smart" hospital rooms.

Emergency department visits in Connecticut for survivors of sexual assault before and during the COVID-19 pandemic.

STUDY OBJECTIVE: We evaluate the impact of the COVID-19 pandemic on care for survivors of sexual assault in three urban Emergency Departments (ED) in the United States. METHODS: A retrospective chart review was conducted on patients who presented after sexual assault to three EDs during 6-month intervals before and during the COVID-19 pandemic. We excluded individuals <18 years old. We performed a structured chart review to ascertain demographics, ED treatments, and adherence to guidelines for care of sexual assault survivors. RESULTS: Of 105 patients who received care after a sexual assault, 57 presented during the COVID-19 pandemic. The majority were female, White/Caucasian, and presented within 120 h of sexual assault. There was an increase in ED presentations for sexual assault during the pandemic. While there was no difference in medical care, there were fewer sexual assault advocates called during the pandemic. In addition, there was an increase in non-White survivors in the first 3 months of the pandemic that did not remain at 6 months. CONCLUSION: The care of survivors in the ED was disrupted by the COVID-19 pandemic. While medical care remained similar, fewer calls to sexual assault advocates, a key component of ED and long-term care of survivors, demonstrate a disruption in their care.

Choice Architecture to Assist Clinicians with Appropriate COVID-19 Test Ordering.

BACKGROUND: Despite improving supplies, SARS-CoV-2 nucleic acid amplification tests remain limited during surges and more so given concerns around COVID-19/influenza co-occurrence. Matching clinical guidelines to available supplies ensures resources remain available to meet clinical needs. We report a change in clinician practice after an electronic health record (EHR) order redesign to impact emergency department (ED) testing patterns. METHODS: We included all ED visits between December 1, 2021 and January 18, 2022 across a hospital system to assess the impact of EHR order changes on provider behavior 3 weeks before and after the change. The EHR order redesign included embedded symptom-based order guidance. Primary outcomes were the proportion of COVID-19 + flu/respiratory syncytial virus (RSV) testing performed on symptomatic, admitted, and discharged patients, and the proportion of COVID-19 + flu testing on symptomatic, discharged patients. RESULTS: A total of 52 215 ED visits were included. For symptomatic, discharged patients, COVID-19 + flu/RSV testing decreased from 11.4 to 5.8 tests per 100 symptomatic visits, and the rate of COVID-19 + flu testing increased from 7.4 to 19.1 before and after the intervention, respectively. The rate of COVID-19 + flu/RSV testing increased from 5.7 to 13.1 tests per 100 symptomatic visits for symptomatic patients admitted to the hospital. All changes were significant (P < 0.0001). CONCLUSIONS: A simple EHR order redesign was associated with increased adherence to institutional guidelines for SARS-CoV-2 and influenza testing amidst supply chain limitations necessitating optimal allocation of scarce testing resources. With continually shifting resource availability, clinician education is not sufficient. Rather, system-based interventions embedded within exiting workflows can better align resources and serve testing needs of the community.

Rapid serum tubes reduce transport hemolysis and false positive rates for high-sensitivity troponin T.

INTRODUCTION: Hemolysis in the emergency department (ED) can significantly delay results and appropriate action. We evaluated the main sources of hemolysis during sample collection, and to evaluate the use of rapid serum tubes (RST) as a transport hemolysis-mitigating measure for high-sensitivity troponin T (hs-cTnT) testing. METHODS: We examined the effect of tube type, tube fill, types of sample draw and collection methods on hemolysis and hs-cTnT in samples (n = 158) from ED patients. We also compared hs-cTnT values in paired RST and plasma separate tube (PST) samples that were hemolysis-free. RESULTS: The primary source of hemolysis in samples collected in the ED was underfilling tubes. In both tube types, PST and RST, filled tubes showed a median reduction in hemolysis of 69.1 % (p < 0.0001). Blood collected in RST also experienced less hemolysis compared to PST. In hemolysis-free samples, false positive results in PST were noted in patients with hs-cTnT values < 50 ng/l. CONCLUSION: We suggest that proper tube filling during sample collection and use of RST tubes can significantly reduce the effects of hemolysis. In addition, laboratories should be aware that PST tubes have a non-trivial rate of false positives when hs-cTnT < 50 ng/l.

Prehospital emergency department care activations during the initial COVID-19 pandemic surge.

OBJECTIVE: To describe trends in prehospital presentations of critical medical and trauma conditions during the COVID-19 pandemic using prehospital and emergency department (ED) care activations. METHODS: Observational analysis of ED care activations in a tertiary, urban ED between March 10, 2020 and September 1, 2020 was compared to the same time periods in 2018 and 2019. ED care activations for critical medical conditions were classified based on clinical indication: undifferentiated medical, trauma, or stroke. MAIN OUTCOME: The primary outcomes were the number of patients presenting from the prehospital setting with specified ED activation criteria, total ED volume, ambulance arrival volume, and volume of COVID-19 hospital admissions. Locally weighted scatterplot smoothing curves were used to visually display our results. RESULTS: There were 1,461 undifferentiated medical activations, 905 stroke activations, and 1,478 trauma activations recorded, representing absolute decreases of 11.3, 28.1, and 20.3 percent, respectively, relative to the same period in 2019, coinciding with the declaration of a public health emergency in Connecticut. For all three types of presentation, post-peak spikes in activations were observed in early May, approximately two weeks after our health system in Connecticut reached its peak number of COVID-19 hospitalizations-eg, undifferentiated medical activations: increase in 280 percent, n = 140 from 2019, p < 0.0001-and declined thereafter, reaching a nadir in early June 2020. CONCLUSIONS: After the announcement of public health measures to mitigate COVID-19, ED care activations declined in a large Northeast academic ED, followed by post-peak surges in activations as COVID- 19 cases decreased.

Implementation of an Electronic Health Record Integrated Clinical Pathway Improves Adherence to COVID-19 Hospital Care Guidelines.

BACKGROUND: During the COVID-19 pandemic, frequently changing guidelines presented challenges to emergency department (ED) clinicians. The authors implemented an electronic health record (EHR)-integrated clinical pathway that could be accessed by clinicians within existing workflows when caring for patients under investigation (PUI) for COVID-19. The objective was to examine the association between clinical pathway utilization and adherence to institutional best practice treatment recommendations for COVID-19. METHODS: The authors conducted an observational analysis of all ED patients seen in a health system inclusive of seven EDs between March 18, 2020, and April 20, 2021. They implemented the pathway as an interactive flow chart that allowed clinicians to place orders while viewing the most up-to-date institutional guidance. Primary outcomes were proportion of admitted PUIs receiving dexamethasone and aspirin in the ED, and secondary outcome was time to delivering treatment. RESULTS: A total of 13 269 patients were admitted PUIs. The pathway was used by 40.6% of ED clinicians. When clinicians used the pathway, patients were more likely to be prescribed aspirin (OR, 7.15; 95% CI, 6.2-8.26) and dexamethasone (10.4; 8.85-12.2). For secondary outcomes, clinicians using the pathway had statistically significant ( P < 0.0001) improvement in timeliness of ordering medications and admission to the hospital. Aspirin, dexamethasone, and admission order time were improved by 103.89, 94.34, and 121.94 minutes, respectively. CONCLUSIONS: The use of an EHR-integrated clinical pathway improved clinician adherence to changing COVID-19 treatment guidelines and timeliness to associated medication administration. As pathways continue to be implemented, their effects on improving patient outcomes and decreasing disparities in patient care should be further examined.

Universal SARS-CoV-2 Testing of Emergency Department Admissions Increases Emergency Department Length of Stay.

STUDY OBJECTIVE: Our institution experienced a change in SARS-CoV-2 testing policy as well as substantial changes in local COVID-19 prevalence, allowing for a unique examination of the relationship between SARS-CoV-2 testing and emergency department (ED) length of stay. METHODS: This was an observational interrupted time series of all patients admitted to an academic health system between March 15, 2020, and September 30, 2020. Given testing limitations from March 15 to April 24, all patients receiving SARS-CoV-2 tests were symptomatic. On April 24, testing was expanded to all ED admissions. The primary and secondary outcomes were ED length of stay and number needed to test to obtain a positive, respectively. RESULTS: A total of 70,856 patients were cared for in the EDs during the 7-month period. The testing change increased admission length of stay by 1.89 hours (95% confidence interval 1.39 to 2.38). The number needed to test was 2.5 patients and was highest yield on April 1, 2020, when the state positivity rate was 39.7%; however, the number needed to test exceeded 170 patients by Sept 1, 2020, at which point the state positivity rate was 0.5%. CONCLUSION: Although universal SARS-CoV-2 testing of ED admissions may meaningfully support mitigation and containment efforts, the clinical cost of testing all admissions amid low community positivity is notable. In our system, universal ED SARS-CoV-2 testing was associated with a 24% increase in admission length of stay alongside the detection of only 1 positive case every other day. Given the known harms and risks of ED boarding and crowding, solutions must be developed to support regular operational flow while balancing infection prevention needs.

Real-world assessment of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) nasopharyngeal swab testing in a region with a high burden of coronavirus disease 2019 (COVID-19).

Concerns persist regarding possible false-negative results that may compromise COVID-19 containment. Although obtaining a true false-negative rate is infeasible, using real-life observations, the data suggest a possible false-negative rate of ˜2.3%. Use of a sensitive, amplified RNA platform should reassure healthcare systems.

Simulating approaches to emergency department pandemic physician staffing during COVID-19.

OBJECTIVE: During pandemics, emergency departments (EDs) are challenged by the need to replace quarantined ED staff and avoid staffing EDs with nonemergency medicine (EM) trained physicians. We sought to design and examine three feasible ED staffing models intended to safely schedule EM physicians to staff three EDs within a health system during a prolonged infectious disease outbreak. METHODS: We conducted simulation analyses examining the strengths and limitations of three ED clinician staffing models: two-team and three-team fixed cohort, and three-team unfixed cohort. Each model was assessed with and without immunity, and by varying infection rates. We assumed a 12-week pandemic disaster requiring a 2-week quarantine. MAIN OUTCOME: The outcome, time to staffing shortage, was defined as depletion of available physicians in both 8- and 12-hour shift duration scenarios. RESULTS: All staffing models initially showed linear physician attrition with higher infection rates resulting in faster staffing shortages. The three-team fixed cohort model without immunity was not viable beyond 11 weeks. The three-team unfixed cohort model without immunity avoided staffing shortage for the duration of the pandemic up to an infection rate of 50 percent. The two-team model without immunity also avoided staffing shortage up to 30 percent infection rate. When accounting for immunity, all models behaved similarly initially but returned to adequate staffing during week 5 of the pandemic. CONCLUSIONS: Simulation analyses reveal fundamental tradeoffs that are critical to designing feasible pandemic disaster staffing models. Emergency physicians should test similar models based on local assumptions and capacity to ensure adequate staffing preparedness for prolonged pandemics.