Emergency Department Operations Research Articles

The hospital costs of high emergency department pediatric readiness.

We estimate annual hospital expenditures to achieve high emergency department (ED) pediatric readiness (HPR), that is, weighted Pediatric Readiness Score (wPRS)≥88 (0-100 scale) across EDs with different pediatric volumes of children, overall and after accounting for current levels of readiness. We calculated the annual hospital costs of HPR based on two components: (1) ED pediatric equipment and supplies and (2) labor costs required for a Pediatric Emergency Care Coordinator (PECC) to perform pediatric readiness tasks. Data sources to generate labor cost estimates included: 2021 national salary information from U.S. Bureau of Labor Statistics, detailed patient and readiness data from 983 EDs in 11 states, the 2021 National Pediatric Readiness Project assessment; a national PECC survey; and a regional PECC survey. Data sources for equipment and supply costs included: purchasing costs from seven healthcare organizations and equipment usage per ED pediatric volume. We excluded costs of day-to-day ED operations (ie, direct clinical care and routine ED supplies). The total annual hospital costs for HPR ranged from $77,712 (95% CI 54,719-100,694) for low volume EDs to $279,134 (95% CI 196,487-362,179) for very high volume EDs; equipment costs accounted for 0.9-5.0% of expenses. The total annual cost-per-patient ranged from $3/child (95% CI 2-4/child) to $222/child (95% CI 156-288/child). After accounting for current readiness levels, the cost to reach HPR ranged from $23,775 among low volume EDs to $145,521 among high volume EDs, with costs per patient of $4/child to $48/child. Annual hospital costs for HPR are modest, particularly when considered per child.

A Granular Approach to Optimal and Fair Patient Placement in Hospital Emergency Departments

Prolonged emergency department (ED) length of stay (LOS) is associated with detrimental effects on patient care quality and outcomes. There is evidence that certain groups of patients experience longer LOS based on their gender or race, especially with regard to the part of LOS that is attributable to waiting to be seen by a clinician. This work tackles the patient prioritization and placement aspects of ED operations with the goal of improving throughput and wait time in a fair, equitable way. We present a novel Mixed Integer Linear Programming (MILP) predictive-prescriptive formulation that incorporates a breakdown of predicted patient ED LOS into actionable pieces. We incorporate considerations for fairness and reformulate the MILP formulation into a compact and computationally tractable formulation that can be solved efficiently in real time. To deal with uncertainty, we propose a sampling-based solution, and provide provable guarantees regarding its convergence, stability and sample complexity. The proposed solution increases the throughput of the ED by [Formula: see text] and decreases the average wait time by [Formula: see text] compared to current hospital practice. In addition, the method is near-optimal in terms of throughput, and produces high-quality solutions in terms of average wait time compared to a clairvoyant oracle. Our proposed approach demonstrates desirable properties when it comes to fairness in patient prioritization, illustrating a path for addressing hidden biases in patient ED wait times and hospital operations as a whole. This work was conducted in collaboration with a large US academic medical center. Data from more than 40,000 patient visits were used to shape and evaluate the predictive-prescriptive models. An important practical contribution is translating a complex algorithm’s output into recommendations that can be operationalized in the context of existing processes in the ED. Specifically, we develop an interpretable metamodel that is trained to mimic the predictive-prescriptive algorithm’s decisions and provides a transparent set of rules for patient placement. The method will be used by the hospital to improve patient flow and quality of care as well as to support more fair and consistent bed allocation decisions.

Improving the emergency services using quality improvement project and Donabedian model in a quaternary teaching hospital in South India

IntroductionThe primary goal of quality improvement is to enhance patient outcomes, particularly in the emergency department (ED). Timely and effective care is crucial in these situations. By comprehending the challenges,...

Impacts of the 2021 heat dome on emergency department visits, hospitalizations, and health system operations in three hospitals in Seattle, Washington.

Extreme heat events (EHEs) are associated with excess healthcare utilization but specific impacts on emergency department (ED) operations and throughput are unknown. In 2021, the Pacific Northwest experienced an unprecedented heat dome that resulted in substantial regional morbidity and mortality. The aim of this study was to examine its impact on ED utilization, unplanned hospitalization, and hospital operations in a large academic healthcare system. Retrospective electronic medical records from three Seattle-area hospitals were used to compare healthcare utilization during the EHE compared to a pre-event reference period within the same month. Interrupted time series analysis was used to evaluate the association between EHE exposure and ED visits and hospitalizations. Metrics of ED crowding for the EHE were compared to the reference period using Student's t-tests and chi-squared tests. Additionally, multivariable Poisson regression was used to identify risk factors for heat-related illness and hospital admission. Interrupted time series analysis showed an increase of 21.7 ED visits per day (95% confidence interval [CI]=14.7, 28.6) and 9.9 unplanned hospitalizations per day (95% CI=8.3, 11.5) during the EHE, as compared to the reference period. ED crowding and process measures also displayed significant increases, becoming the most pronounced by day 3 of the EHE; the EHE was associated with delays in ED length of stay of 1.0h (95% CI=0.4, 1.6) compared to the reference period. Higher incidence rate ratios for heat-related illness were observed for patients who were older (incidence rate ratio [IRR]=1.02; 95% CI=1.01,1.03), female (IRR=1.47; 95% CI=1.06, 2.04), or who had pre-existing diabetes (IRR=3.19; 95% CI=1.47, 6.94). The 2021 heat dome was associated with a significant increase in healthcare utilization including ED visits and unplanned hospitalizations. Substantial impacts on ED and hospital throughput were also noted. These findings contribute to the understanding of the role extreme heat events play on impacting patient outcomes and healthcare system function.

Emergency Department Overcrowding in Canada

What Is the Issue?
 
 Emergency departments (EDs) across Canada are under strain and experiencing overcrowding, a situation that arises when the demand for health services in the ED exceeds the capacity of the health system — which includes the ED, hospital, and community — to provide quality care in a reasonable amount of time.
 ED overcrowding is contributing to a deteriorating standard of care as health care providers and staff become overworked and burned out, is putting health and lives at risk, and is placing additional strain on an already overwhelmed health care system.
 
 What Did We Do?
 
 The CADTH Health Technology Expert Review Panel (HTERP) convened to develop objective, impartial, trusted pan-Canadian guidance to inform decisions about which evidence-informed solutions should be considered to help alleviate ED overcrowding in Canada.
 
 What Is HTERP’s Position on ED Overcrowding?
 
 ED overcrowding is a complex health system issue. EDs operate within hospitals and broader health and social systems, which means that accountability for causes, impacts, and solutions do not lie solely within the ED and its operations.
 Output factors (e.g., misalignment between acute care bed capacity within the hospital and population needs) and input factors (e.g., misalignment between care available in the community and population needs, including care outside of regular business hours) respectively, are the main contributors to ED overcrowding in Canada. Health system capacity is not aligned with, nor has kept pace with, the growing and changing health care needs of the population, which results in overcrowded EDs.
 Health systems will observe better results by implementing strategies that improve patient flow and focus on output and input factors relative to throughput factors.
 
 What Is HTERP’s Guidance to Help Alleviate ED Overcrowding?
 
 Interventions to alleviate overcrowding need to align with the main contributing factors to ED overcrowding in the particular context in which they will be implemented.
 Understanding the context in which ED overcrowding is occurring, with attention to bottlenecks to patient flow, should be the first step to identify evidence-informed solutions.
 Transparency and accountability should be key principles in ED, hospital, and health system operations. HTERP recommends identifying and ensuring clear roles, responsibilities, and reporting relationships embedded within an accountability framework for ED overcrowding across health system partners, including a commitment to act on data.
 Each province and territory should mandate consistent and comprehensive reporting by all hospitals to the Canadian Institute of Health Information’s National Ambulatory Care Reporting System (NACRS) database.
 HTERP’s guidance includes an Evidence Navigation Guide to support identification of evidence-informed interventions to help alleviate ED overcrowding.

Artificial intelligence for emergency medical care

AbstractThere is increasing research into the potential benefits of incorporating artificial intelligence (AI) and machine learning algorithms into emergency medical services. AI is finding new applications across a wide range of sectors, one of which is healthcare, where it is being used to enhance clinical diagnostics. AI solutions have enormous untapped potential to improve healthcare efficiency and quality, thus researchers have focused heavily on emergency medicine (EM). Many individuals without prior experience with any physician often receive their initial medical care in the emergency room. Two areas that could benefit from the implementation of AI are reducing waiting times and enhancing diagnostic capabilities. This study provides further explanation of how AI is used in emergency rooms. Several machine learning‐based algorithms are also addressed. In this research, we summarise recent developments in the use of AI in EM. This research tries to summarise the usefulness of AI in EM by looking at recent developments in emergency department operations and clinical patient management.

The Management of Children and Youth With Pediatric Mental and Behavioral Health Emergencies.

Mental and behavioral health (MBH) emergencies in children and youth continue to increasingly affect not only the emergency department (ED), but the entire spectrum of emergency medical services for children, from prehospital services to the community. Inadequate community and institutional infrastructure to care for children and youth with MBH conditions makes the ED an essential part of the health care safety net for these patients. As a result, an increasing number of children and youth are referred to the ED for evaluation of a broad spectrum of MBH emergencies, from depression and suicidality to disruptive and aggressive behavior. However, challenges in providing optimal care to these patients include lack of personnel, capacity, and infrastructure; challenges with timely access to a mental health professional; the nature of a busy ED environment; and paucity of outpatient post-ED discharge resources. These factors contribute to prolonged ED stays and boarding, which negatively affect patient care and ED operations. Strategies to improve care for MBH emergencies, including systems-level coordination of care, are therefore essential. The goal of this policy statement and its companion technical report is to highlight strategies, resources, and recommendations for improving emergency care delivery for pediatric MBH.

The Management of Children and Youth With Pediatric Mental and Behavioral Health Emergencies

Mental and behavioral health (MBH) emergencies in children and youth continue to increasingly affect not only the emergency department (ED), but the entire spectrum of emergency medical services for children, from prehospital services to the community. Inadequate community and institutional infrastructure to care for children and youth with MBH conditions makes the ED an essential part of the health care safety net for these patients. As a result, an increasing number of children and youth are referred to the ED for evaluation of a broad spectrum of MBH emergencies, from depression and suicidality to disruptive and aggressive behavior. However, challenges in providing optimal care to these patients include lack of personnel, capacity, and infrastructure, challenges with timely access to a mental health professional, the nature of a busy ED environment, and paucity of outpatient post-ED discharge resources. These factors contribute to prolonged ED stays and boarding, which negatively affects patient care and ED operations. Strategies to improve care for MBH emergencies, including systems level coordination of care, is therefore essential. The goal of this policy statement and its companion technical report is to highlight strategies, resources, and recommendations for improving emergency care delivery for pediatric MBH.

Impact of Care Initiation Model on Emergency Department Orders and Operational Metrics: Cohort Study.

Emergency departments (ED) employ many strategies to address crowding and prolonged wait times. They include front-end Care Initiation and clinician-in-triage models that start the diagnostic and therapeutic process while the patient waits for a care space in the ED. The objective of this study was to quantify the impact of a Care Initiation model on resource utilization and operational metrics in the ED. We performed a retrospective analysis of ED visits at our institution during October 2021. Baseline characteristics were compared with Chi-square and quantile regression. We used t-tests to calculate unadjusted difference in outcome measures, including number of laboratory tests ordered and average time patients spent in the waiting room and the ED treatment room, and the time from arrival until ED disposition. We performed propensity score analysis using matching and inverse probability weighting to quantify the direct impact of Care Initiation on outcome measures. There were 2,407 ED patient encounters, 1,191 (49%) of whom arrived during the hours when Care Initiation was active. A total of 811 (68%) of these patients underwent Care Initiation, while the remainder proceeded directly to the main treatment area. Patients were more likely to undergo Care Initiation if they had lower acuity and lower risk of admission, and if the ED was busier as measured by the number of recent arrivals and percentage of occupied ED beds. After adjusting for patient-specific and department-level covariates, Care Initiation did not increase the number of diagnostic laboratory tests ordered. Care Initiation was associated with increased waiting room time by 1.8 hours and longer time from arrival until disposition by 1.3 hours, but with decreased time in the main treatment area by 0.6 hours, which represents a 15% reduction. Care Initiation was associated with a 15% reduction in time spent in the main ED treatment area but longer waiting room time and longer time until ED disposition without significantly increasing the number of laboratory studies ordered. While previous studies produced similar results with Care Initiation models accessing all diagnostic modalities including imaging, our study demonstrates that a more limited Care Initiation model can still result in operational benefits for EDs.

Evaluation of Emergency Service Admissions for Planning the Number of Intensive Care Beds in Hospitals

A significant portion of intensive care unit (ICU) admissions occur through the emergency department (ED). Since there are insufficient ICU beds, critically ill patients may have to be monitored and treated in ED for an extended period. In this study, we aimed to show the importance of the emergency department intensive care unit (EDICU) and that ED applications should be taken into account in determining the number of intensive care unit (ICU) beds in hospitals by analyzing the patients hospitalized in intensive care units from the ED. In this retrospective descriptive study, patients over 18 who applied to the ED of a tertiary hospital between July 1, 2018, and July 1, 2019, and were deemed suitable for ICU admission were included. In descriptive statistics, percentages were used in categorical data, and mean, and standard deviation were used in numerical data. Chi-square test was applied for categorical variables. Since the distribution within the groups was normal in the analysis of continuous variables, one-way analysis of variance (ANOVA) was used when more than two groups were compared. The student's t-test was used when two groups were compared. Of the 2783 patients who applied to the ED and were suitable for admission to the ICU, 1341 (48.2%) were admitted to the second-level ICU, and 1442 (51.8%) were admitted to the third-level ICU. 1140 (40.96%) patients were hospitalized in the EDICU and toxicology ICU within the ED. These units played an important role in facilitating the ED operation and reducing crowding. Patients admitted to the ICU were divided into three groups based on their length of stay. Of the patients, 2312 (%83.1) were hospitalized in the first 6 hours, 337 (%12.1) in 6-12 hours, and 205 (7.36%) in more than 12 hours. It was observed that the mortality rate increased significantly when hospitalization in the ICU was delayed (P=0.014). ED admissions should be considered when determining the number of ICU beds and step levels of hospitals. In addition, the presence of EDICU in tertiary care hospitals relieves the density of the emergency department and indirectly reduces the mortality rate.

Licensed Practical Nurses in Team Triage: A Safe Way to Address Nursing Shortages in the Emergency Department.

Background There is a Registered Nurse (RN) shortage across the United States that is predicted to intensify in the upcoming years. RNs are an integral part of Emergency Departments (EDs) and perform many vital tasks, including IV placement, blood draws, medication administration, acute assessments, and patient hand-offs. Thus, RN staffing is a crucial part of ED operations, and ED initiatives should account for RN workforce shortages. Given the increase in ED visits and crowding, throughput initiatives that can expedite patient care are integral to the functioning of an ED. Team Triage is a throughput initiative that has been shown to improve ED time to provider, length of stay, and left without being seen rates. In our institution, we created a Team Triage model where advanced practice providers (APPs) perform a patient's initial evaluation in triage and place orders for labs, intravenous (IV) catheters, and imaging. Given the RN staffing shortage, we incorporated Licensed Practical Nurses (LPNs) in Team Triage to place IV catheters and draw blood work for laboratory tests. The objective of this investigation was to describe a Team Triage model that incorporated LPNs and to report the patient safety and productivity of this model. Methods This was a single-site retrospective study at a large, academic, tertiary care center with over 100,000 annual visits. Adult patients who self-presented to the ED and went through Team Triage (11 am-11 pm) between Jan 1, 2020, and Jan 31, 2020, were included in this study. LPNs staffed the Team Triage, along with APPs. LPNs placed IV catheters and drew blood specimens for the Team Triage patients. The primary outcomes studied were the proportion of specimens mislabeled by LPNs, the proportion of patients receiving IV catheters, the proportion of patients receiving blood work, blood tubes drawn per hour, and IVs inserted per hour in Team Triage. Results During the study period, 1355 patients went through Team Triage. Of these patients, 1075 (79%) were ordered for blood work, and 1017 (75%) were ordered for an IV catheter. All Team Triage blood work and IV catheter placements were completed by LPNs, who staffed 372 hours of Team Triage. A total of 2558 blood tubes were collected by LPNs. The LPNs cared for 2.9 patients per hour, collected 6.9 blood tubes per hour, inserted 2.7 IV catheters per hour, and collected 2.4 blood tubes per patient. The LPNs had a 0% specimen mislabeling rate. Conclusion Due to the significant RN workforce shortage impacting Emergency Medicine coupled with increased ED crowding, there is a significant need to evaluate the integration of LPNs into Team Triage to place IV catheters and perform blood draws. This study shows that incorporating LPNs in Team Triage is a productive and safe way to address nursing shortages in Emergency Medicine.

Factors that affect pain management in adults diagnosed with acute appendicitis in the emergency department: A retrospective study

BackgroundAnalgesic treatment, including with opioids, can safely be given to patients who are suspected of having appendicitis.The study examined factors which may influence the treatment of pain in appendicitis in the adult emergency department (ED). A secondary objective was to determine if analgesia affected clinical outcomes. MethodsThis single-center retrospective study examined medical records of all adult patients with a discharge diagnosis of appendicitis. Patients were categorized based on the type of analgesia received in the ED. Variables included the day of week and staffing shift of presentation, gender, age, and triage pain scale, as well as time to ED discharge, imaging, operation, and hospital discharge. Univariable and multivariable logistic regression models were performed to determine which factors influenced treatment and affected outcomes. ResultsRecords of 1839 patients were categorized into three groups – 883 (48%) did not receive analgesia, 571 (31%) received only non-opioid medications, and 385 (21%) received at least one opioid.Patients with a higher triage pain level were significantly more likely to receive analgesia (4–6: OR = 1.85; 95% CI = 1.2–2.84, 7–9: OR = 3.36; 95% CI = 2.18–5.17, 10: OR = 10.78; 95% CI = 6.38–18.23) and at least one opioid (4–6: OR = 2.88; 95% CI = 1.13–7.34, 7–9: OR = 4.36; 95% CI = 1.73–11.01, 10: OR = 6.23; 95% CI = 2.42–16.09). Male gender was associated with a significantly lower likelihood of receiving analgesia (OR = 0.74; 95% CI = 0.61–0.9), but a significantly greater likelihood of receiving at least one opioid given that they received any pain medication (OR = 1.87; 95% CI = 1.41–2.48). Patients aged 25–64 years old were significantly more likely to receive at least one opioid if they received any pain medication (25–44: OR = 1.47; 95% CI = 1.08–2.02, 45–64: OR = 1.78; 95% CI = 1.15–2.76). Presentation to the ED on Sundays was associated with lower rates of opioid treatment (OR = 0.63; 95% CI = 0.42–0.94).Regarding clinical outcomes, patients who received analgesia waited longer for imaging (+0.58 h; 95% CI = 0.31–0.85), stayed longer in the ED (+2.2 h; 95% CI = 1.60–2.79), and had a slightly longer hospitalization (+0.62d; 95% CI = 0.34–0.90). ConclusionsAlmost half of patients with appendicitis didn't receive analgesia, with most of those treated receiving only non-opioid analgesia. Older age and Sunday presentations were associated with less opioid treatment. Patients who received analgesia waited longer for imaging, stayed longer in the ED, and had a longer hospitalization.

The Pattern of Injuries in the Emergency Room during the COVID-19 Pandemic.

The coronavirus disease 2019 (COVID-19) pandemic has obviously caused a remarkable change in patients' emergency department (ED) visits; however, data from multicenter studies are lacking. We aimed to present a comprehensive analysis of injury-related ED visits in Republic of Korea before and during the COVID-19 pandemic. Data from 23 tertiary hospitals based on Emergency Department-based Injury In-depth Surveillance were used for this retrospective cross-sectional study. A total of 541,515 ED visits (age ≥ 20 years) between 1 January 2018 and 31 December 2020 were included, and the trend of injuries related to motor vehicular accidents, falls, self-harm and suicide, assault, and poisoning were compared between the pre-COVID-19 time period and during the COVID-19 pandemic. In the first year of the COVID-19 period, a decline in the number of ED visits was observed (41,275, 21%) compared to the previous year. Injuries caused by motor vehicles (36,332 in 2019 vs. 27,144 in 2020), falls and slips (61,286 in 2019 vs. 49,156 in 2020), assaults (10,528 in 2019 vs. 8067 in 2020), and poisonings (7859 in 2019 vs. 7167 in 2020) decreased, whereas self-harm and suicide (8917 in 2019 vs. 8911 in 2020) remained unchanged. The hospitalization (16.6% in 2019 vs. 18.8% in 2020) and ED mortality rate (0.6% in 2019 vs. 0.8% in 2020) also increased. The COVID-19 pandemic led to a decline in the overall number of trauma patients seeking medical care; however, the proportion of patients requiring hospitalization or intensive care unit admission increased, indicating more severe injuries among those who did seek care. Suicide attempt rates remained unchanged, highlighting the need for targeted care and support for vulnerable patients. During the pandemic, EDs had to continue to provide care to patients with medical emergencies unrelated to COVID-19, which requires a delicate and adaptable approach to ED operations. To manage the increased stress and workload caused by the pandemic, increased resources and support for healthcare workers were needed.

Development of a Emergency Department Operations and Throughput Curriculum for Resident Physicians

Development of a Emergency Department Operations and Throughput Curriculum for Resident Physicians

Psychiatric Boarding in Emergency Departments and the COVID-19 First Wave: The New Hampshire Response

The COVID-19 pandemic forced unprecedented challenges for emergency department operations during the spring of 2020. Before the COVID-19 pandemic, psychiatric boarding in emergency departments required a substantial amount of staffing and administrative resources. This case study describes one state's efforts to rapidly decrease psychiatric boarding by 93% in 2 weeks with a multipronged approach, and simultaneously minimal effects observed on outcome measures of psychiatric hospital readmissions and suicide rates. Lessons learned are discussed regarding workflow adaptations and leadership implications.

Characteristics of acute sexual assault care in New England emergency departments.

Interventions such as written protocols and sexual assault nurse examiner programs improve outcomes for patients who have experienced acute sexual assault. How widely and in what ways such interventions have been implemented is largely unknown. We sought to characterize the current state of acute sexual assault care in New England. We conducted a cross-sectional survey of individuals acute with knowledge of emergency department (ED) operations in relation tosexual assault care at New England adult EDs. Our primary outcomesincluded the availability and coverage of dedicated and non-dedicated sexual assault forensic examiners in EDs. Secondary outcomes included frequency of and reasons for patient transfer; treatment before transfer; availability of written sexual assault protocols; characteristics and scope of practice of dedicated and non-dedicated sexual assault forensic examiners (SAFEs), provision of care in SAFEs' absence; availability, coverage, and characteristics of victim advocacy and follow-up resources; and barriers to and facilitators of care. We approached all 186 distinct adult EDs in New England to recruit participants; 92 (49.5%) individuals participated, most commonly physician medical directors (n=34, 44.1%). Two thirds of participants reported they at times have access to a dedicated (n=52, 65%, 95% confidence interval [CI], 54.5%-75.5%) or non-dedicated (n=50, 64.1%; 95% CI, 53.5%-74.7%) SAFE, but fewer reported always having this access (n=9, 17.3%; 95% CI, 7%-27.6%; n=13, 26%; 95% CI, 13.8%-38.2%). We describe in detail findings related to our secondary outcomes. Although SAFEs are recognized as a strategy to provide high-quality acute sexual assault care, their availability and coverage is limited.

Probabilistic Forecasting of Patient Waiting Times in an Emergency Department

Problem definition: We study the estimation of the probability distribution of individual patient waiting times in an emergency department (ED). Whereas it is known that waiting-time estimates can help improve patients’ overall satisfaction and prevent abandonment, existing methods focus on point forecasts, thereby completely ignoring the underlying uncertainty. Communicating only a point forecast to patients can be uninformative and potentially misleading. Methodology/results: We use the machine learning approach of quantile regression forest to produce probabilistic forecasts. Using a large patient-level data set, we extract the following categories of predictor variables: (1) calendar effects, (2) demographics, (3) staff count, (4) ED workload resulting from patient volumes, and (5) the severity of the patient condition. Our feature-rich modeling allows for dynamic updating and refinement of waiting-time estimates as patient- and ED-specific information (e.g., patient condition, ED congestion levels) is revealed during the waiting process. The proposed approach generates more accurate probabilistic and point forecasts when compared with methods proposed in the literature for modeling waiting times and rolling average benchmarks typically used in practice. Managerial implications: By providing personalized probabilistic forecasts, our approach gives low-acuity patients and first responders a more comprehensive picture of the possible waiting trajectory and provides more reliable inputs to inform prescriptive modeling of ED operations. We demonstrate that publishing probabilistic waiting-time estimates can inform patients and ambulance staff in selecting an ED from a network of EDs, which can lead to a more uniform spread of patient load across the network. Aspects relating to communicating forecast uncertainty to patients and implementing this methodology in practice are also discussed. For emergency healthcare service providers, probabilistic waiting-time estimates could assist in ambulance routing, staff allocation, and managing patient flow, which could facilitate efficient operations and cost savings and aid in better patient care and outcomes.Supplemental Material: The online supplement is available at https://doi.org/10.1287/msom.2023.1210 .

Statistical analysis of factors influencing patient length of stay in emergency departments

PurposePatient length of stay (LOS) is an important indicator of emergency department (ED) performance. Investigating factors that influence LOS could thus improve healthcare delivery and patient safety. Previous studies have focused on patient-level factors to explain LOS variation, with little research into service-related factors. This study examined the association between LOS and multi-level factors including patient-, service- and organization-level factors.Design/methodology/approachThis study uses a retrospective observational design to identify a cohort of patients from arrival to discharge from ED. A year-long data regarding patients flow trhoguh ED were analyzed using analytics techniques and multi-regression models. The response variable was patient LOS, and the independent variables were patient characteristics, service-related factors and organizational variables.FindingsThe findings of this study showed that older patients, middle triage and hospitalization were all associated with longer LOS. Service-related factors such as complexity of care provided, initial ward designation and ward transfer had a significant impact as well. Finally, prolonged LOS was associated with a higher ratio of patients per medical doctor and per nurse. In contrast, a higher number of residents in the ED were associated with longer patient LOS.Originality/valuePrevious studies on patient LOS have focused on patient-level factors, with little research on service-related factors. This study has addressed that gap by examining the association between LOS and multi-level factors including patient-, service- and organization-level factors. Patient-level factors included demographics, acuity, arrival shift, arrival mode and discharge type. Service-level factors consisted of first ward, ward transfer and complexity of care provided. Organizational factors consisted of three ratios: patients per MD, patients per nurse and patients per resident. The results add to the current understanding of factors that increase patient LOS in EDs and contribute to the body of knowledge on ED performance, operation management and quality of care. The study also provides practical and managerial insights that could be used to improve patient flow in EDs and reduce LOS.

Study protocol for a multisite randomized controlled trial of a peer navigator intervention for emergency department patients with nonfatal opioid overdose

BackgroundPatients presenting to emergency departments (EDs) after a nonfatal opioid-involved overdose are at high risk for future overdose and death. Responding to this risk, the New York City (NYC) Department of Health and Mental Hygiene operates the Relay initiative, which dispatches trained peer “Wellness Advocates” to meet patients in the ED after a suspected opioid-involved overdose and follow them for up to 90 days to provide support, education, referrals to treatment, and other resources using a harm reduction framework. MethodsIn this article, we describe the protocol for a multisite randomized controlled trial of Relay. Study participants are recruited from four NYC EDs and are randomized to receive the Relay intervention or site-directed care (the control arm). Outcomes are assessed through survey questionnaires conducted at 1-, 3-, and 6-months after the baseline visit, as well as through administrative health data. The primary outcome is the number of opioid-related adverse events, including any opioid-involved overdose or any other substance use-related ED visit, in the 12 months post-baseline. Secondary and exploratory outcomes will also be analyzed, as well as hypothesized mediators and moderators of Relay program effectiveness. ConclusionWe present the protocol for a multisite randomized controlled trial of a peer-delivered OD prevention intervention in EDs. We describe how the study was designed to minimize disruption to routine ED operations, and how the study was implemented and adapted during the COVID-19 pandemic. This trial is registered with ClinicalTrials.gov [NCT04317053].

Operations Factors Associated with Emergency Department Length of Stay: Analysis of a National Operations Database.

Prolonged emergency department (ED) length of stay (LOS) has been shown to adversely affect patient care. We sought to determine factors associated with ED LOS via analysis of a large, national, ED operations database. We performed retrospective, multivariable, linear regression modeling using the 2019 Emergency Department Benchmarking Alliance survey results to identify associated factors of ED LOS for admitted and discharged patients. A total of 1,052 general and adult-only EDs responded to the survey. Median annual volume was 40,946. The median admit and discharge LOS were 289 minutes and 147 minutes, respectively. R-squared values for the admit and discharge models were 0.63 and 0.56 with out-of-sample R-squared values of 0.54 and 0.59, respectively. Both admit and discharge LOS were associated with academic designation, trauma level designation, annual volume, proportion of ED arrivals occurring via emergency medical services, median boarding, and use of a fast track. Additionally, admit LOS was associated with transfer-out percentage, and discharge LOS was associated with percentage of high Current Procedural Terminology, percentage of patients <18 years old, use of radiographs and computed tomography, and use of an intake physician. Models derived from a large, nationally representative cohort identified diverse associated factors of ED length of stay, several of which were not previously reported. Dominant within the LOS modeling were patient population characteristics and other factors extrinsic to ED operations, including boarding of admitted patients, which was associated with both admitted and discharged LOS. The results of the modeling have significant implications for ED process improvement and appropriate benchmarking.