Index Emergency Department Research Articles

Using HEART2 score to risk stratify chest pain patients in the Emergency Department: an observational study

BackgroundA significant number of chest pain patients had previous cardiac imaging tests (CIT) performed before being presented to the Emergency Department (ED). The HEART (history, electrocardiogram, age, risk factors, and troponin) score has been used to risk-stratify chest pain patients in the ED, but not particularly for patients with CIT performed. We aim to modify the current HEART score with the addition of most recent CIT findings (referred to as HEART2 score), to predict a 30-day major adverse cardiac event (MACE) among ED chest pain patients, compare the performance accuracy of using HEART versus HEART2 score for 30-day MACE outcome predictions, and further determine the value of HEART2 in a subset group of ED chest pain patients (i.e., ones with previous CIT).MethodsThis is a single-center observational study. We included chest pain patients with HEART scores calculated during their index ED visits. A modified HEART2 score was developed with the addition of CIT findings as one of the HEART2 components. Patients were divided into three groups, including low (≤ 3), moderate (4–6), and high-risk HEART/HEART2 scores (≥ 7). MACE occurrence of a patient with different risks of HEART and HEART2 scores and overall performance accuracy of HEART versus HEART2 score predicting MACE outcomes were compared.ResultsWe included a total of 9419 chest pain patients at ED, among which one out of five patients (1874/9419) had previous CIT performed. Fewer (38.2%) of such patients had low-risk HEART scores in comparison to 55.5% of low-risk HEART2 scores (p < 0.001). The MACE outcomes were similar in low-risk HEART patients compared with low-risk HEART2 patients (2.2% versus 3.1%, p = 0.3021). The overall performance accuracy of using the HEART2 score to stratify chest pain patients with previous CIT was better than using the HEART score’s (AUC 0.74 versus 0.71, p = 0.0082).ConclusionsUsing the HEART2 score might be suitable to stratify low-to-moderate risk chest pain patients at ED with a similar 30-days MACE occurrence compared to the HEART score. More importantly, with the use of similar low-risk criteria (HEART2 ≤ 3), over 45% more chest pain patients with previous CIT performed could be discharged directly from ED.

Real-world evaluation of the impact of two anti-SARS-CoV-2 monoclonal antibody regimens on COVID-19 hospitalizations in older adults.

Evidence from clinical trials suggest anti‐SARS‐CoV‐2 monoclonal antibodies (mABs) may reduce coronavirus disease 2019 (COVID‐19)‐related hospitalizations. The purpose of this study was to assess the real‐world impact of mAB administration on COVID‐19 hospitalization among patients 65 years or older. This was a retrospective, propensity‐matched cohort study that included patients aged 65 years and older who presented to the emergency department (ED) within 10 days of symptom onset of mild to moderate COVID‐19 infection. Outcomes were compared between those who did and did not receive mAB therapy. The primary endpoint was the rate of hospitalization for COVID‐19 within 30 days of index ED visit. A total of 137 patients receiving mABs were matched to 137 controls. Hospitalization occurred in 2.9% of mAB‐treated patients compared to 14.6% of patients of the standard of care (SOC) arm (odds ratio: 0.20 [95% CI: 0.07–0.59]). There were zero intubations and zero deaths compared to 3 (2.2%) and 2 (1.5%) in the SOC group. Among the 223 patients receiving mAB in the overall cohort, adverse drug events occurred in 10 (4.5%). Treatment with mAB therapy for mild to moderate COVID‐19 was associated with a substantially reduced risk of hospitalization among patients at least 65 years of age.

Downstream Acute Care Utilization Following Initial Prescription of an Opioid Pain Reliever Among Emergency Department Patients With Low-Severity Conditions

We sought to investigate the association between receipt of an opioid pain reliever (OPR) in the emergency department (ED) and downstream acute health care utilization. Within Kaiser Permanente Northern California, we identified opioid-naïve patients, ages 18-64, who were treated and discharged from the ED for a painful, low-severity condition between January 1, 2017, and December 31, 2017. We also identified patients who received an OPR, either administered in the ED or obtained at a Kaiser Permanente Northern California pharmacy within 7 days of ED arrival, and investigated subsequent acute care utilization in cases with at least 1 ED, urgent care, or inpatient visit within 1 month or 3 months of the index encounter or 2 visits within 12 months. Of the 39,468 adults included in our study, 50.7% were female, 55.0% were non-White, and 25.2% received an OPR in association with their index ED encounter. After adjustment, we found that patients who received an OPR had greater odds of downstream acute care utilization than those who did not, with odds ratios of 1.68, 1.53, and 1.50 at 1, 3, and 12 months, respectively (all p < 0.05). Patients who received an OPR at their index encounter had substantially increased odds of a subsequent ED, urgent care, or inpatient visit. This effect was most pronounced early in follow-up and persisted for the duration of the study period. Receipt of an OPR among opioid-naïve adults for a painful, low-severity condition is associated with increased downstream acute care utilization.

Risk of malignancy following emergency department Bell's palsy diagnosis in children.

To quantify the risk of malignancy following the emergency department (ED) diagnosis of Bell's Palsy (BP) using a large retrospective cohort. We performed a cohort study using the Pediatric Health Information System database. We included all children (6months - 17years) from 2011 to 2020 with an ED diagnosis of BP. We excluded children with previous neurologic chronic condition or malignancy diagnosed during or prior to the index visit. Our primary outcome was diagnosis of malignancy within 60days following the index ED visit. We compared clinical characteristics between children with and without new-onset malignancy. Of 12,272 encounters for BP, 41 had a new oncologic diagnosis within 60days (0.33%, 95% confidence interval [CI]: 0.25-0.45%). Median time to oncologic diagnosis was 22days. Primary CNS malignancy (59%) and leukemia (17.1%) were the most common diagnoses. Younger children had a higher incidence of new oncologic diagnosis compared with older children. Incidences were 0.68% (95% CI 0.36-1.3%), 0.70% (95% CI 0.38-1.3%), 0.26% (95% CI 0.15-0.47%), and 0.21% (95% CI 0.12-0.37%) for children aged <2years, 2-5years, 6-11years, and 12-17years respectively. We found a small but potentially clinically significant rate of new-onset oncologic diagnosis within 60days after BP diagnosis in the ED, especially in children younger than 5years. Further studies of the diagnostic utility of laboratory testing or neuroimaging and the risk of empiric steroids in children with BP are needed.

Disparities in cardiovascular outcomes among emergency department patients with mental illness

BackgroundPatients with mental illness have been shown to receive lower quality of care and experience worse cardiovascular (CV) outcomes compared to those without mental illness. This present study examined mental health-related disparities in CV outcomes after an Emergency Department (ED) visit for chest pain. MethodsThis retrospective cohort included adult Medicaid beneficiaries in Washington state discharged from the ED with a primary diagnosis of unspecified chest pain in 2010–2017. Outcomes for patients with any mental illness (any mental health diagnosis or mental-health specific service use within 1 year of an index ED visit) and serious mental illness (at least two claims (on different dates of service) within 1 year of an index ED visit with a diagnosis of schizophrenia, other psychotic disorder, or major mood disorder) were compared to those of patients without mental illness. Our outcomes of interest were the incidence of major adverse cardiac events (MACE) within 30 days and 6 months of discharge of their ED visit, defined as a composite of death, acute myocardial infarction (AMI), CV rehospitalization, or revascularization. Secondary outcomes included cardiovascular diagnostic testing (diagnostic angiography, stress testing, echocardiography, and coronary computed tomography (CT) angiography) rates within 30 days of ED discharge. Only treat-and-release visits were included for outcomes assessment. Hierarchical logistic random effects regression models assessed the association between mental illness and the outcomes of interest, controlling for age, gender, race, ethnicity, Elixhauser comorbidities, and health care use in the past year, as well as fixed year effects. ResultsThere were 98,812 treat-and-release ED visits in our dataset. At 30 days, enrollees with any mental illness had no differences in rates of MACE (AOR 0.96; 95% CI, 0.72–1.27) or any of the individual components. At 6 months, enrollees with any mental illness (AOR 1.86; 95% CI, 1.11–3.09) and serious mental illness (AOR 2.60; 95% CI 1.33–5.13) were significantly more likely to be hospitalized for a CV condition compared to those without mental illness. Individuals with any mental illness had higher rates of testing at 30 days (AOR 1.16; 95% CI 1.07–1.27). ConclusionPatients with mental illness have similar rates of MACE, but higher rates of certain CV outcomes, such as CV hospitalization and diagnostic testing, after an ED visit for chest pain.

Long-term treatment retention of an emergency department initiated medication for opioid use disorder program

IntroductionMedication for Opioid Use Disorder (MOUD) has been shown to decrease mortality, reduce overdoses, and increase treatment retention for patients with opioid use disorder (OUD) and has become the state-of-the-art treatment strategy in the emergency department (ED). There is little evidence on long-term (6 and 12 month) treatment retention outcomes for patients enrolled in MOUD from the ED. MethodsA prospective observational study used a convenience sample of patients seen at one community hospital ED over 12 months. Patients >18 years with OUD were eligible for MOUD enrollment. After medical screening, patients were evaluated by the addiction care coordinator (ACC) who evaluated and counselled the patient and if eligible, directly connected them with an addiction medicine appointment. Once enrolled, the patient received treatment with buprenorphine in the ED. A chart review was completed for all enrollments during the first year of the program. Treatment retention was determined by review of the prescription drug monitoring program and defined as patients receiving regular suboxone prescriptions at 6 and 12 months after index ED visit date. ResultsFrom June 2018 - May 2019 the ACCs evaluated patients during 691 visits, screening 571 unique patients. Of the 571 unique patients screened, 279 (48.9%) were enrolled into the MOUD program. 210 (75.3%) attended their first addiction medicine appointment, 151 (54.1%) were engaged in treatment at 1 month, 120 (43.0%) at 3 months, 105 (37.6%) at 6 months, and 97 (34.8%) at 12 months post index ED visit. Self-pay insurance status was associated with a significantly decrease in the odds of long-term treatment retention. ConclusionOur ED-initiated MOUD program, in partnership with local addiction medicine services, produced high rates of long-term treatment retention.

A randomized clinical trial of strengths-based case management to link emergency department patients to opioid use disorder treatment

BackgroundDespite the existence of effective pharmacotherapies, rates of opioid use disorder and opioid overdose deaths have continued to increase. Emergency department (ED) visits provide an important opportunity to engage in treatment patients with untreated opioid use disorder (OUD). Case management implemented in other settings is effective in linking those with opioid and other drug use disorders to longer-term treatment, but research has not established its efficacy in the ED. Here we report the results of a trial of Strengths-Based Case Management (SBCM) for people with untreated OUD who are identified during ED visits, with the primary goal of linking them to pharmacologic treatment. MethodsThe study identified patients with untreated OUD during a treatment episode at a large urban ED. The study randomly assigned three hundred participants in 1:1 ratio to receive SBCM or screening, assessment, and referral (SAR) to OUD treatment. Those assigned to SBCM received up to six sessions of SBCM with the primary goal of linkage to treatment. Primary outcomes were initiation of treatment and engagement in pharmacotherapy for OUD. The study defined a “successful outcome” for opioid use as a 3-month urine negative for illicit opioids and no more than 2 days of self-reported opioid misuse in the 4 weeks prior to the 3-month interview. ResultsRates of treatment initiation were not significantly different in the SBCM and SAR groups (57.4% vs. 49.7%, respectively, p > 0.05), nor did engagement in pharmacotherapy differ significantly between groups (p > 0.05). During the 90 days following the index ED visit, SBCM and SAR participants engaged in pharmacotherapy for a mean of 21.8% (SD = 35.1%) versus 17.7% (SD = 31.0%) of days, respectively. Likewise, no significant difference occurred between groups in rates of “successful opioid use outcome” as defined a priori (p > 0.05), although self-reported opioid use over the entire 6-month follow-up period was lower in the SBCM group (10.8 vs. 13.4 days/month, p = 0.042). ConclusionsSBCM-ED did not improve OUD treatment initiation and engagement in this ED study. Although these findings do not necessarily generalize to all EDs, other approaches, such as direct referral or initiation of treatment in the ED, have considerable empirical support, and should be implemented where they are feasible.

Posttraumatic stress disorder symptoms after respiratory and cardiovascular emergencies predict risk of hospital readmission: A prospective cohort study.

Twenty-five percent of patients presenting to the emergency department (ED) for a respiratory or cardiovascular medical emergency develop clinically significant posttraumatic stress disorder (PTSD) symptoms. It is possible that development of PTSD symptoms in this cohort is associated with subsequent adverse physical health events. Our objective was to test whether clinically significant PTSD symptoms 30days postdischarge are associated with increased risk for hospital readmission within 24months after discharge among patients presenting to the ED for a respiratory or cardiovascular emergency. This was a prospective cohort study conducted between January 1, 2018, and December 31, 2020, at a U.S. academic medical center, including adult patients presenting with acute respiratory failure or cardiovascular instability requiring a potentially life-sustaining intervention in the ED. PTSD symptoms 30days postdischarge were measured using the PTSD Checklist for the Diagnostic and Statistical Manual of Mental Disorders-5. The primary outcome was all-cause hospital readmission over the subsequent 24months after hospital discharge from the index ED visit. Of the 99 patients included, 73% (95% confidence interval [CI]= 63% to 81%) had a hospital readmission within 24months. In a multivariable Cox proportional hazards model adjusting for potential confounders (e.g., age, severity of illness during index ED visit, preexisting comorbid conditions) presence of clinically significant PTSD symptoms at 30days was independently associated with increased risk for all-cause hospital readmission at 24months (hazards ratio=2.19, 95% CI= 1.30 to 3.69). These results remained statistically significant across multiple sensitivity analyses. Hospital readmission is common among survivors of acute respiratory failure and cardiovascular instability, and PTSD symptoms 30days postdischarge are an independent predictor of hospital readmission. Survivors of medical emergencies may warrant follow-up evaluation for PTSD symptoms, and future research is warranted to better understand the relationship between psychological trauma and hospital readmission.

Derivation of the Pediatric Acute Gastroenteritis Risk Score to Predict Moderate-to-Severe Acute Gastroenteritis.

Although most acute gastroenteritis (AGE) episodes in children rapidly self-resolve, some children go on to experience more significant and prolonged illness. We sought to develop a prognostic score to identify children at risk of experiencing moderate-to-severe disease after an index emergency department (ED) visit. Data were collected from a cohort of children 3 to 48 months of age diagnosed with AGE in 16 North American pediatric EDs. Moderate-to-severe AGE was defined as a Modified Vesikari Scale (MVS) score ≥9 during the 14-day post-ED visit. A clinical prognostic model was derived using multivariable logistic regression and converted into a simple risk score. The model's accuracy was assessed for moderate-to-severe AGE and several secondary outcomes. After their index ED visit, 19% (336/1770) of participants developed moderate-to-severe AGE. Patient age, number of vomiting episodes, dehydration status, prior ED visits, and intravenous rehydration were associated with MVS ≥9 in multivariable regression. Calibration of the prognostic model was strong with a P value of 0.77 by the Hosmer-Lemenshow goodness-of-fit test, and discrimination was moderate with an area under the receiver operator characteristic curve of 0.68 (95% confidence interval [CI] 0.65-0.72). Similarly, the model was shown to have good calibration when fit to the secondary outcomes of subsequent ED revisit, intravenous rehydration, or hospitalization within 72 hours after the index visit. After external validation, this new risk score may provide clinicians with accurate prognostic insight into the likely disease course of children with AGE, informing disposition decisions, anticipatory guidance, and follow-up care.

Effectiveness of an algorithm-based care pathway for patients with non-valvular atrial fibrillation presenting to the emergency department.

ObjectiveAtrial fibrillation (AF) carries substantial morbidity and mortality. Evidence‐based guidelines have been synthesized into emergency department (ED) AF care pathways, but the effectiveness and scalability of such approaches are not well established. We thus evaluated the impacts of an algorithmic care pathway for ED management of non‐valvular AF (EDAFMP) on hospital use and care process measures.MethodsWe deployed a voluntary‐use EDAFMP in 4 EDs (1 tertiary hospital, 1 cardiac hospital, 2 community hospitals) of an integrated delivery organization using a multifaceted implementation approach. We compared outcomes between patients with AF treated using the EDAFMP and historical and contemporaneous “usual care” controls, using a propensity‐score adjusted generalized estimating equation. Patients with an index ED encounter for a primary visit reason of non‐valvular AF (and no excluding concurrent diagnoses) were eligible for inclusion.ResultsPreimplementation (January 1, 2016–December 31, 2016), 628 AF patients were eligible; postimplementation (September 1, 2017–June 30, 2019), 1296, including 271 (20.9%) treated with the EDAFMP, were eligible. EDAFMP patients were less likely to be admitted than both historical (adjusted odds ratio [aOR], 95% confidence interval [CI]: 0.45, 0.29–0.71) and contemporaneous controls (aOR, 95%CI: 0.63, 0.46–0.86). ED visits and hospital readmissions over 90 days subsequent to index ED encounters were similar between postimplementation EDAFMP and usual care groups. EDAFMP patients were more likely to be prescribed anticoagulation (38% v. 5%, P < 0.001) and be referred to a cardiologist (93% vs 29%, P < 0.001) versus the comparator group.ConclusionEDAFMP use is associated with decreased hospital admission during an index ED encounter for non‐valvular AF, and improved delivery of AF care processes.

Abstract WMP55: Short-term Stroke Risk After Emergency Department Treat-and-release Headache Visit

Introduction: When a stroke hospitalization follows soon after an Emergency Department (ED) treat-and-release visit for non-specific neurological complaints, a diagnostic error may have occurred. In this study, we sought to evaluate potential stroke misdiagnoses after ED treat-and-release headache visits. Methods: We conducted a retrospective cohort study using state-wide administrative claims data for all ED visits and admissions at nonfederal hospitals in Florida 2005-2018 and New York 2005-2016. Using standard ICD codes, we identified adult patients discharged home from the ED with a benign headache diagnosis (cohort of interest) as well as those with a diagnosis of back pain or renal colic (negative control cohorts). The primary study outcome was hospitalization within 30 days for stroke (ischemic or hemorrhagic), defined using validated ICD codes. We used Cox proportional hazards modeling to assess the relationship between the index ED visit reason and stroke hospitalization adjusting for demographics and vascular risk factors. Results: We identified 1,458,904 patients with an ED treat-and-release headache visit; mean age was 41 (SD: 17) and 70% were female. A total of 2,636 (0.18%) headache patients were hospitalized for stroke within 30 days. Stroke risk was higher among headache patients compared to patients diagnosed with renal colic (HR: 2.7; 95% CI, 2.3-3.1) or back pain (HR: 3.8; 95% CI, 3.6-4.1; Figure). Among patients &lt;40 years of age, stroke risk was even higher among headache as compared to back pain (HR: 10; 95% CI, 7.7-13.1); no strokes occurred in renal colic patients &lt;40 years of age. Conclusion: Approximately 1 in 500 patients discharged home from the ED with a headache diagnosis had a stroke in the following month. Stroke risk was 3-4 times higher after an ED visit for headache compared to back pain or renal colic. There may be opportunities to reduce diagnostic error among patients with ED visits for headache, particularly for those &lt;40 years of age.

Abstract TMP38: Using Natural Language Processing To Investigate Diagnostic Error In Acute Stroke

Introduction: Diagnostic error occurs in approximately 10% of acute stroke (AS) presentations. The diagnostic process includes history, physical examination, and test performance and interpretation. However, critical information for diagnosis is contained in unstructured clinical notes. Hypothesis: We hypothesized that natural language processing (NLP) can identify features in unstructured clinical notes associated with potential diagnostic error during ED “catch and release” (CR) encounters prior to AS admissions. Methods: Using a retrospective case-control design and ICD-10 codes, we identified index emergency department (ED) admissions with a diagnosis of first-time stroke (cases) and age and sex-matched gastroenteritis (controls) who had an ED CR encounter in prior 30 days. Notes were processed using cTAKES to identify concept unique identifiers (CUI) among clinical narratives from the CR encounters. Regression analysis was utilized to determine CUI terms from the CR encounter that were associated with stroke cases compared to controls. These CUI terms were grouped by clinical experts into 3 aspects of the diagnostic process: history (e.g., risk factors, medications, symptoms), neurologic examination (e.g., mental status exam, cranial nerves, pronator drift), and tests (e.g., labs, CT, MRI). Results: In an analytic cohort of 319 stroke cases and 319 gastroenteritis controls, a non-cerebrovascular neurologic diagnosis at the CR encounter was noted in 20.2% of cases versus 6.0% in controls (P&lt;0.01). We identified 120 terms at the CR encounter associated with stroke (OR &gt;2.0 and p&lt;0.05). Grouped by themes, tests accounted for 50 (41.7%), examination for 37 (30.1%), and history for 33 (27.5%) terms. Terms related to neurologic examination had the highest median OR (median OR 6.7, IQR 2.7-11.5) followed by history (median OR 3.8, IQR 3.2-4.9) and tests (median OR 3.5, IQR 2.8-4.6). Conclusions: Neurologic presentations to the ED preceded 20% of stroke cases suggesting some of these may represent missed diagnoses for minor stroke and TIA. NLP may be a useful surveillance approach to identify neurologic symptoms, deficits, and tests present at CR encounters and trigger interventions to reduce diagnostic error prior to stroke.

Association of substance use characteristics and future homelessness among emergency department patients with drug use or unhealthy alcohol use: Results from a linked data longitudinal cohort analysis

Background: Homelessness and substance use are intricately related, and both are prevalent among emergency department (ED) patients. This study examined the longitudinal association of substance use characteristics with future homeless shelter entry among ED patients with any drug use or unhealthy alcohol use. Methods: We present results from a longitudinal cohort study of public hospital ED patients who screened positive for drug use or unhealthy alcohol use and who were not homeless at their baseline (index) ED visit. The primary outcome was homeless shelter entry within 12 months of baseline, ascertained in city homeless shelter administrative data. Primary independent variables of interest were alcohol use severity (AUDIT), drug use severity (DAST-10), and types of drugs used, as reported on baseline survey questionnaires. Results: Analyses included 1,210 ED patients. By 12 months following the baseline ED visit, 114 (9.4%) had entered a homeless shelter. Among patients with the most severe problems related to drug use (DAST-10 score 9–10), 40.9% entered a shelter within 12 months. Past shelter use was the strongest predictor of future shelter entry; once adjusting for historic shelter use the relationship of AUDIT and DAST-10 scores with future shelter entry was no longer statistically significant in multivariable models. Conclusions: ED patients with past year drug use or unhealthy alcohol use had relatively high likelihood of future shelter entry. Risk for homelessness should be addressed in future interventions with this population. Findings illustrate the complexity of relationships between substance use and homelessness.

Characteristics of frequent users of emergency departments living with major neurocognitive disorders: a cohort study

Objective: This study aimed to describe and compare the characteristics of community-dwelling older adults living with or without major neurocognitive disorders who made frequent use of emergency departments. Methods: This is a retrospective cohort study based on a secondary analysis of provincial health administrative data in Quebec, Canada. We included community-dwelling older adults from Quebec who were considered frequent emergency department users (a minimum of 4 visits in the year following an index emergency department visit chosen randomly between January 1, 2012, and December 31, 2013) and who had been diagnosed with at least one chronic condition. We compared characteristics of frequent users living with or without major neurocognitive disorders using chi-square and Kruskal-Wallis tests. Results: The study cohort consisted of 21 393 frequent emergency department users, of which 3051 (14.26%) were identified as having a major neurocognitive disorder. The results highlight a higher burden of chronic conditions, polypharmacy, antipsychotic use, and past use of healthcare services among these individuals. The results also reveal a higher proportion of conditions associated with geriatric syndromes such as trauma and injury, malnutrition, orthostatic hypertension, and gait disorders. Conclusion: Frequent emergency department users living with major neurocognitive disorders represent a complex population. Our results highlight the importance of systematically addressing their needs in appropriate settings and through customized interventions.

A comparative evaluation of the strengths of association between different emergency department crowding metrics and repeat visits within 72hours.

We sought to compare strengths of association among multiple emergency department (ED) input, throughput and output metrics and the outcome of 72-h ED re-visits. This database analysis used healthcare administrative data from three urban, university-affiliated EDs in Calgary, Canada, calendar years 2010-2014. We used data from all patients presenting to participating EDs during the study period, and the primary analysis was performed on patients discharged from the ED. Regression models quantified the association between input, throughput and output metrics and the risk of return ED visit within 72h of discharge from the index ED encounter. Strength of association between the crowding metrics and 72-h ED re-visits was compared using Akaike's Information Criterion. The findings of this study are based on data from 845,588 patient encounters ending in discharge. The input metric with the strongest association with 72-h re-visits was median ED waiting time. The throughput metric with the strongest association with 72-h re-visits was the ED occupancy. The output metric with the strongest association with 72-h re-visits was the median inpatient boarding time. Input, throughput and output metrics are all associated with 72-h re-visits. Delays in any of these operational phases have detrimental effects on patient outcomes. ED waiting time, ED occupancy, and boarding times are the most meaningful input, throughput and output metrics. These should be the preferred metrics for quantifying ED crowding in research and quality improvement efforts, and for clinicians to monitor ED crowding in real time.

Predicting Unscheduled Emergency Department Revisits Leading to Acute Hospital Admissions Among Older Adults

Background: Unscheduled emergency department (ED) revisits leading to acute hospital admission (RVA) are tantamount to a failed discharge, associated with physician error, mis-prognosis, and inadequate care planning. Previous research has shown RVA to be associated with adverse outcomes such as ICU admissions, long hospitalizations and mortality. Given the limited impact of pre-existing screening tools for older adults, we developed and validated a machine learning model to predict individual patient risk of RVA within 72 hours and 9 days of index ED visits. Method: A machine learning model was applied to retrospective electronic health record (EHR) data of patients presenting to 2 geographically and demographically divergent urban EDs in 2019. 478 clinically meaningful EHR data variables were included: socio-demographics, ED and comorbidity diagnoses, therapeutics, laboratory test orders and test results, diagnostic imaging test orders, vital signs, and utilization and operational data. Multiple machine learning algorithms were constructed; models were compared against a pre-existing adult ED-RVA risk score as a baseline. Results: A total of 62,154 patients were included in the analysis, with 508 (0.82%) and 889 (1.4%) having 72-hour and 9-day RVA. The best-performing model, combining deep significance clustering (DICE) and regularized logistic regression, achieved AUC of 0.86 and 0.79 for 72-hour and 9-day ED-RVA for older adult patients, respectively, outperforming the pre-existing RVA risk score (0.704 and 0.694). Discussion: Machine learning models to screen for and predict older adults at high-risk for ED-RVA may be useful in directing interventions to reduce adverse events in older adults discharged from the ED.

Exploring differential response to an emergency department-based care transition intervention.

To identify multivariable subgroups of patients with differential responses to a nurse-delivered care transition intervention after an emergency department (ED) visit in a randomized controlled trial (RCT) using an emerging data-driven method. Secondary analysis of RCT. 512 individuals enrolled in an RCT of a nurse-delivered care transition intervention after an ED visit. All 512 participants were included in a pre-specified subgroup analysis, and 451 of these had sufficient complete case data to be included in a model-based recursive (MoB) partitioning analysis. The primary outcome was having at least one ED visit in 30 days after the index ED visit. Two analytical methods explored heterogeneity of treatment effects: data driven model-based recursive partitioning (MoB) using 37 candidate baseline variables, and a contextual point of comparison with prespecified subgroups defined by ED super-user status (≥ 3 ED visits in previous 6 months or not), sex (male/female), and age, individually examined via treatment arm by subgroup interaction terms in logistic regression models. Internal validation of the MoB analysis via bootstrap resampling with an optimism corrected c-statistic was conducted to provide a bias-corrected estimate. MoB detected treatment effect heterogeneity in a single subgroup, marital status. Unmarried patients randomized to the intervention had a repeat ED use rate of 22% compared to 34% in the usual care group; married patients randomized to the intervention had a 27% ED return rate compared to 12% in the usual care group. Internal validation demonstrated an optimism corrected c-statistic of 0.54. No treatment-by-covariate subgroup interactions were identified among the 3 prespecified subgroups. Although exploratory, the results of the MoB analysis suggest that patient factors related to social relationships such as marital status may be important contributors to differential response to a care transition intervention after an ED visit. These were characteristics that the investigators had not anticipated or planned to examine in the individual prespecified subgroup analysis. Data-driven methods can yield unexpected findings and contribute to a more complete understanding of differential treatment effects in subgroup analysis, which can inform further work on development of effective care transition interventions in the ED setting.

Emergency Department Visit Count: A Practical Tool to Predict Asthma Hospitalization in Children

To evaluate whether the frequency of asthma-related emergency department (ED) visits could predict future asthma hospitalization in the pediatric population.The study included 2669 children between the ages of 2 and 16.99 years with asthma visits to the ED at the Children’s Hospital of Eastern Ontario between September 2012 to August 2015.This was a retrospective cohort study in which health administrative data were used to identify all pediatric asthma visits to the ED from 2012 to 2015. The first asthma ED visit within the 3-year inclusion period was defined as index ED visit. The primary exposure was the number of asthma ED visits in the preceding 12 months. Each patient was managed for 12 months after the index ED visit to identify the number of asthma-related hospitalizations and subsequent ED visits. The severity of asthma symptoms at each visit was assessed by using the Canadian Triage and Acuity Scale.The number of asthma ED visits in the preceding year was associated with an increased risk of hospitalization in the subsequent 12 months in a dose-dependent manner. The risk of hospitalization was 2.9 (95% confidence interval: 1.6 to 5) times higher in children with 1 previous ED visit and 4.4 (95% confidence interval: 1.9 to 10.4) times higher in children with ≥2 previous ED visits, compared with that of children with no ED visits. Asthma severity on the basis of Canadian Triage and Acuity Scale level was also a risk factor for future asthma hospitalization. The number of previous asthma ED visits was associated with an increased risk of repeat asthma ED visits in the following year.The number of asthma ED visits was identified as an independent marker of future asthma-related hospitalizations and repeat ED visits in pediatric patients.A major goal of asthma management is to reduce the risk of exacerbations leading to ED visits and hospitalization. Poor asthma control leads to school absenteeism and increased health care use. Identification of a reliable marker to predict future asthma risk could help health care providers target interventions to children at high risk. In this study, the authors identified ED visit count as a predictor of future asthma-related hospitalization in pediatric patients.

CCEDRRN COVID-19 Infection Score (CCIS): development and validation in a Canadian cohort of a clinical risk score to predict SARS-CoV-2 infection in patients presenting to the emergency department with suspected COVID-19

ObjectivesTo develop and validate a clinical risk score that can accurately quantify the probability of SARS-CoV-2 infection in patients presenting to an emergency department without the need for laboratory testing.DesignCohort...

Development and validation of a prediction model for estimating one-month mortality of adult COVID-19 patients presenting at emergency department with suspected pneumonia: a multicenter analysis.

There are only a few models developed for risk-stratifying COVID-19 patients with suspected pneumonia in the emergency department (ED). We aimed to develop and validate a model, the COVID-19 ED pneumonia mortality index (CoV-ED-PMI), for predicting mortality in this population. We retrospectively included adult COVID-19 patients who visited EDs of five study hospitals in Texas and who were diagnosed with suspected pneumonia between March and November 2020. The primary outcome was 1-month mortality after the index ED visit. In the derivation cohort, multivariable logistic regression was used to develop the CoV-ED-PMI model. In the chronologically split validation cohort, the discriminative performance of the CoV-ED-PMI was assessed by the area under the receiver operating characteristic curve (AUC) and compared with other existing models. A total of 1678 adult ED records were included for analysis. Of them, 180 patients sustained 1-month mortality. There were 1174 and 504 patients in the derivation and validation cohorts, respectively. Age, body mass index, chronic kidney disease, congestive heart failure, hepatitis, history of transplant, neutrophil-to-lymphocyte ratio, lactate dehydrogenase, and national early warning score were included in the CoV-ED-PMI. The model was validated with good discriminative performance (AUC: 0.83, 95% confidence interval [CI]: 0.79–0.87), which was significantly better than the CURB-65 (AUC: 0.74, 95% CI: 0.69–0.79, p-value: < 0.001). The CoV-ED-PMI had a good predictive performance for 1-month mortality in COVID-19 patients with suspected pneumonia presenting at ED. This free tool is accessible online, and could be useful for clinical decision-making in the ED.Supplementary InformationThe online version contains supplementary material available at 10.1007/s11739-021-02882-x.