Clinical operations of academic versus non-academic emergency departments: a descriptive comparison of two large emergency department operations surveys

BACKGROUND: Academic and non-academic emergency departments (EDs) are regularly compared in clinical operations benchmarking despite suggestion that the two groups may differ in their clinical operations characteristics. and outcomes. We sought to describe and compare clinical operations characteristics of academic versus non-academic EDs. METHODS: We performed a descriptive, comparative analysis of academic and non-academic adult and general EDs with 40,000+ annual encounters, using the Academy of Academic Administrators of Emergency Medicine (AAAEM)/Association of Academic Chairs of Emergency Medicine (AACEM) and Emergency Department Benchmarking Alliance (EDBA) survey results. We defined academic EDs as primary teaching sites for emergency medicine (EM) residencies and non-academic EDs as sites with minimal resident involvement. We constructed the academic and non-academic cohorts from the AAAEM/AACEM and EDBA surveys, respectively, and analyzed metrics common to both surveys. RESULTS: Eighty and 454 EDs met inclusion criteria for academic and non-academic EDs, respectively. Academic EDs had more median annual patient encounters (73,001 vs 54,393), lower median proportion of pediatric patients (6.3% vs 14.5%), higher median proportion of EMS patients (27% vs 19%), and were more commonly designated as Level I or II Trauma Centers (94% vs 24%). Median patient arrival-to-provider times did not differ (26 vs 25 min). Median length-of-stay was longer (277 vs 190 min) for academic EDs, and left-before-treatment-complete was higher (5.7% vs 2.9%). MRI utilization was higher for academic EDs (2.2% patients with at least one MRI vs 1.0 MRIs performed per 100 patients). Patients-per-hour of provider coverage was lower for academic EDs with and without consideration for advanced practice providers and residents. CONCLUSIONS: Demographic and operational performance measures differ between academic and non-academic EDs, suggesting that the two groups may be inappropriate operational performance comparators. Causes for the differences remain unclear but the differences appear not to be attributed solely to the academic mission

Creation of Surge Capacity by Early Discharge of Hospitalized Patients at Low Risk for Untoward Events

Objectives: US hospitals are expected to function without external aid for up to 96 hours during a disaster; however, concern exists that there is insufficient capacity in hospitals to absorb large numbers of acute casualties. The aim of the study was to determine the potential for creation of inpatient bed surge capacity from the early discharge (reverse triage) of hospital inpatients at low risk of untoward events for up to 96 hours. Methods: In a health system with 3 capacity-constrained hospitals that are representative of US facilities (academic, teaching affiliate, community), a variety (N = 50) of inpatient units were prospectively canvassed in rotation using a blocked randomized design for 19 weeks ending in February 2006. Intensive care units (ICUs), nurseries, and pediatric units were excluded. Assuming a disaster occurred on the day of enrollment, patients who did not require any (previously defined) critical intervention for 4 days were deemed suitable for early discharge. Results: Of 3491 patients, 44% did not require any critical intervention and were suitable for early discharge. Accounting for additional routine patient discharges, full use of staffed and unstaffed licensed beds, gross surge capacity was estimated at 77%, 95%, and 103% for the 3 hospitals. Factoring likely continuance of nonvictim emergency admissions, net surge capacity available for disaster victims was estimated at 66%, 71%, and 81%, respectively. Reverse triage made up the majority (50%, 55%, 59%) of surge beds. Most realized capacity was available within 24 to 48 hours. Conclusions: Hospital surge capacity for standard inpatient beds may be greater than previously believed. Reverse triage, if appropriately harnessed, can be a major contributor to surge capacity

Operational factors associated with emergency department patient satisfaction: Analysis of the Academy of Administrators of Emergency Medicine/Association of Academic Chairs of Emergency Medicine national survey

BACKGROUND: Patient satisfaction is a focus for emergency department (ED) and hospital administrators. ED patient satisfaction studies have tended to be single site and focused on patient and clinician factors. Inclusion of satisfaction scores in a large, national operations database provided an opportunity to conduct an investigation that included diverse operational factors. METHODS: We performed a retrospective analysis of the 2019 Academy of Administrators in Academic Emergency Medicine/Association of Academic Chairs of Emergency Medicine (AAAEM/AACEM) benchmarking survey to identify associations between operational factors and patient satisfaction. We identified 59 database variables as potential predictors of Press Ganey likelihood-to-recommend and physician overall scores. Using random forest modeling, we identified the top eight predictors in the models and described their associations. RESULTS: Forty-three (57.3%) academic departments responding to the AAAEM/AACEM survey reported patient satisfaction scores for 78 EDs. Likelihood to recommend ranged from 30.0 to 93.0 (median = 74.8) and was associated with ED length of stay, boarding, use of hallway spaces, hospital annual admissions, faculty base clinical hours, proportion of patients leaving before treatment complete (LBTC), and provider in triage hours per day. Physician overall score ranged from 53.3 to 93.4 (median = 81.9) and was associated with faculty base clinical hours, x-ray utilization, annual ED arrivals, LBTC, use of hallway spaces, arrivals per attending hour, and CT utilization. CONCLUSIONS: ED patient satisfaction was associated with intrinsic and extrinsic factors, some being potentially manageable within the ED but others being relatively fixed or outside the control of ED operations. For likelihood to recommend, patient flow was dominant, with erosion of satisfaction observed with increased boarding and longer LOS. Factors associated with physician overall score were more varied. The use of hallway spaces and base clinical hours greater than 1,500 per year were associated with both lower likelihood-to-recommend and lower physician overall scores

Contributions of Academic Emergency Medicine Programs to U.S. Health Care: Summary of the AAAEM-AACEM Benchmarking Data

OBJECTIVES: The societal contribution of emergency care in the United States has been described. The role and impact of academic emergency departments (EDs) has been less clear. Our report summarizes the results of a benchmarking effort specifically focused on academic emergency medicine (EM) practices. METHODS: From October through December 2016, the Academy of Academic Administrators of Emergency Medicine (AAAEM) and the Association of Academic Chairs of Emergency Medicine (AACEM) jointly administered a benchmarking survey to allopathic, academic departments and divisions of emergency medicine. Participation was voluntary and nonanonymous. The survey queried various aspects of the three components of the tripartite academic mission: clinical care, education and research, and faculty effort and compensation. Responses reflected a calendar year from July 1, 2015, to June 30, 2016. RESULTS: Of 107 eligible U.S. allopathic, academic departments and divisions of emergency medicine, 79 (74%) responded to the survey overall, although individual questions were not always answered by all responding programs. The 79 responding programs reported 6,876,189 patient visits at 97 primary and affiliated academic clinical sites. A number of clinical operations metrics related to the care of these patients at these sites are reported in this study. All responding programs had active educational programs for EM residents, with a median of 37 residents per program. Nearly half of the overall respondents reported responsibility for teaching medical students in mandatory EM clerkships. Fifty-two programs reported research and publication activity, with a total of $129,494,676 of grant funding and 3,059 publications. Median faculty effort distribution was clinical effort, 66.9$277,045. CONCLUSIONS: Academic EM programs are characterized by significant productivity in clinical operations, education, and research. The survey results reported in this investigation provide appropriate benchmarking for academic EM programs because they allow for comparison of academic programs to each other, rather than nonacademic programs that do not necessarily share the additional missions of research and education and may have dissimilar working environments

Use of Systems Engineering to Design a Hospital Command Center

© 2018 The Joint Commission Background: In hospitals and health systems across the country, patient flow bottlenecks delay care delivery—emergency department boarding and operating room exit holds are familiar examples. In other industries, such as oil, gas, and air traffic control, command centers proactively manage flow through complex systems. Methods: A systems engineering approach was used to analyze and maximize existing capacity in one health system, which led to the creation of the Judy Reitz Capacity Command Center. This article describes the key elements of this novel health system command center, which include strategic colocation of teams, automated visual displays of real-time data providing a global view, predictive analytics, standard work and rules-based protocols, and a clear chain of command and guiding tenets. Preliminary data are also shared. Results: With proactive capacity management, subcycle times decreased and allowed the health system\u27s flagship hospital to increase occupancy from 85% to 92% while decreasing patient delays. Conclusion: The command center was built with three primary goals—reducing emergency department boarding, eliminating operating room holds, and facilitating transfers in from outside facilities—but the command center infrastructure has the potential to improve hospital operations in many other areas

2017 AAAEM Benchmarking Survey: Comparing Pediatric and Adult Academic Emergency Departments

OBJECTIVES: The Academy of Administrators in Academic Emergency Medicine Benchmark Survey of academic emergency departments (EDs) was conducted in 2017. We compared operational measures between pediatric and adult (defined as fewer than 5% pediatric visits) EDs based on survey data. Emergency departments in dedicated pediatric hospitals were not represented. METHODS: Measures included: (1) patient volumes, length of stay, and acuity; and 2) faculty staffing, productivity, and percent effort in academics. t Tests were used to compare continuous measures and inferences for categorical variables were made using Pearson chi test. RESULTS: The analysis included 17 pediatric and 52 adult EDs. We found a difference in the number of annual visits between adult (median, 66,275; interquartile range [IQR], 56,184-77,702) and pediatric EDs (median, 25,416; IQR, 19,840-29,349) (P \u3c 0.0001). Mean arrivals per faculty clinical hour and total arrivals per treatment space showed no differences. The proportion of visits (1) arriving by emergency medical services and (2) for behavioral health were significantly higher in adult EDs (both P \u3c 0.0001). The mean length of stay in hours for all patients was significantly longer in adult (5.4; IQR, 5.0-6.6) than in pediatric EDs (3.5; IQR, 2.9-4.3; P = 0.017). A similar difference was found for discharged patients (P = 0.004). Emergency severity indices, professional evaluation and management codes, and hospitalization rates all suggest higher acuity in adult EDs (all P \u3c 0.0001). There were no differences in mean work relative value units per patient or in the distribution of full time equivalent effort dedicated to academics. CONCLUSIONS: In this cohort, significant differences in operational measures exist between academic adult and pediatric EDs. No differences were found when considering per unit measures, such as arrivals per faculty clinical hour or per treatment space