Comparison of Short-Term Health Care Utilization Between Telemedicine-Delivered vs In-Person Care Visits for Heart Failure.

Background: Patients with heart failure (HF) are a medically complex population with frequent hospitalizations. Downstream health care utilization following primary care delivered by telemedicine compared to in-person is unknown. Objectives: The purpose of this study was to understand differences in return in-person visits, emergency department (ED) encounters, and hospitalizations following a telemedicine vs an in-person primary care visit for patients with HF seen for a HF-related complaint. Methods: This was an observational study of all primary care visits for HF from January 1, 2022, to December 31, 2022, in an integrated health care delivery system. We compared 7-day in-person follow-up visits, ED visits, and hospitalizations (all-cause and HF-specific) by index visit type. Results: We included 3,902 primary care visits with a primary diagnosis of HF. Most visits utilized telephone or video visits (58.4% total; 44.9% telephone, 13.5% video). After adjustment, telephone visits were associated with more in-person follow-up visits (6.14% vs 4.20%; adjusted OR: 1.08-2.21; P < 0.05) but fewer ED visits (6.12% vs 8.07%; adjusted OR: 0.55-0.97; P < 0.05) compared to in-person visits. Most hospitalized patients (74%) had an admitting diagnosis of HF. There was no difference between 7-day all-cause hospitalization following telephone or video visits compared to in-person visits. Conclusions: Most patients used telemedicine to address HF-specific primary care concerns. Telephone visits were associated with slightly higher short-term in-person primary care follow-up but lower ED utilization. Overall, downstream ED visits and hospitalizations were low. Telephone and video visits appear to offer safe alternatives to in-person care for HF-related primary care and are a promising health care delivery strategy.

Emergency Department Referral of Patients With Chest Pain for Noninvasive Cardiac Testing and 2-Year Clinical Outcomes.

BACKGROUND: Noninvasive cardiac testing (NICT) has been associated with decreased long-term risks of major adverse cardiac events (MACEs) among emergency department patients at high coronary risk. It is unclear whether this association extends to patients without evidence of myocardial injury on initial ECG and cardiac troponin testing. METHODS: A retrospective cohort study was conducted of patients presenting with chest pain between 2013 and 2019 to 21 emergency departments within an integrated health care system in Northern California, excluding patients with ST-segment-elevation myocardial infarction or myocardial injury by serum troponin testing. To account for confounding by indication, we grouped patient encounters by the NICT referral rate of the initially assigned emergency physician relative to local peers within discrete time periods. The primary outcome was MACE within 2 years. Secondary outcomes were coronary revascularization and MACE, inclusive of all-cause mortality. Associations between the NICT referral group (low, intermediate, or high) and outcomes were assessed using risk-adjusted proportional hazards methods with censoring for competing events. RESULTS: Among 144 577 eligible patient encounters, the median age was 58 years (interquartile range, 48-68) and 57% were female. Thirty-day NICT referral was 13.0%, 19.9%, and 27.8% in low, intermediate, and high NICT referral groups, respectively, with a good balance of baseline covariates between groups. Compared with the low NICT referral group, there was no significant decrease in the adjusted hazard ratio of MACE within the intermediate (adjusted hazard ratio, 1.08 [95% CI, 1.02-1.14]) or high (adjusted hazard ratio, 1.05 [95% CI, 0.99-1.11]) NICT referral groups. Results were similar for MACE, inclusive of all-cause mortality, and coronary revascularization, as well as subgroup analyses stratified by estimated risk (history, electrocardiogram, age, risk factors, troponin [HEART] score: percent classified as low risk, 48.2%; moderate risk, 49.2%; and high risk, 2.7%). CONCLUSIONS: Increases in NICT referrals were not associated with changes in the hazard of MACE within 2 years following emergency department visits for chest pain without evidence of acute myocardial injury. These findings further highlight the need for evidence-based guidance regarding the appropriate use of NICT in this population.

Sex-Based Differences in the Epidemiology, Clinical Characteristics, and Outcomes Associated with Worsening Heart Failure Events in a Learning Health System.

BACKGROUND: Differences in demographics, risk factors, and clinical characteristics may contribute to variations in men and women in terms of the prevalence, clinical setting, and outcomes associated with worsening heart failure (WHF) events. We sought to describe sex-based differences in the epidemiology, clinical characteristics, and outcomes associated with WHF events across clinical settings. METHODS AND RESULTS: We examined adults diagnosed with HF from 2010 to 2019 within a large, integrated health care delivery system. Electronic health record data were accessed for hospitalizations, emergency department (ED) visits and observation stays, and outpatient encounters. WHF was identified using validated natural language processing algorithms and defined as ≥1 symptom, ≥2 objective findings (including ≥1 sign), and ≥1 change in HF-related therapy. Incidence rates and associated outcomes for WHF were compared across care setting by sex. We identified 1,122,368 unique clinical encounters with a diagnosis code for HF, with 124,479 meeting WHF criteria. These WHF encounters existed among 102,116 patients, of whom 48,543 (47.5%) were women and 53,573 (52.5%) were men. Women experiencing WHF were older and more likely to have HF with preserved ejection fraction compared with men. The clinical settings of WHF were similar among women and men: hospitalizations (36.8% vs 37.7%), ED visits or observation stays (11.8% vs 13.4%), and outpatient encounters (4.4% vs 4.9%). Women had lower odds of 30-day mortality after an index hospitalization (adjusted odds ratio 0.88, 95% confidence interval 0.83-0.93) or ED visit or observation stay (adjusted odds ratio 0.86, 95% confidence interval 0.75-0.98) for WHF. CONCLUSIONS: Women and men contribute similarly to WHF events across diverse clinical settings despite marked differences in age and left ventricular ejection fraction.

Implementation and effectiveness of a physician-focused peer support program.

BACKGROUND: The practice of medicine faces a mounting burnout crisis. Physician burnout leads to worse mental health outcomes, provider turnover, and decreased quality of care. Peer support, a viable strategy to combat burnout, has been shown to be well received by physicians. METHODS: This study evaluates the Peer Outreach Support Team (POST) program, a physician-focused peer support initiative established in a 2-hospital system, using descriptive statistical methodologies. We evaluate the POST program using the Practical Robust Implementation and Sustainability Model (PRISM) framework to describe important contextual factors including characteristics of the intervention, recipients, implementation and sustainability infrastructure, and external environment, and to assess RE-AIM outcomes including reach, effectiveness, adoption, implementation, and maintenance. RESULTS: This program successfully trained 59 peer supporters across 11 departments in a 2-hospital system over a 3-year period. Trained supporters unanimously felt the training was useful and aided in general departmental culture shift (100% of respondents). After 3 years, 48.5% of physician survey respondents across 5 active departments had had a peer support interaction, with 306 successful interactions recorded. The rate of interactions increased over the 3-year study period, and the program was adopted by 11 departments, representing approximately 60% of all physicians in the 2-hospital system. Important implementation barriers and facilitators were identified. Physician recipients of peer support reported improved well-being, decreased negative emotions and stigma, and perceived positive cultural changes within their departments. CONCLUSIONS: We found that POST, a physician-focused peer support program, had widespread reach and a positive effect on perceived physician well-being and departmental culture. This analysis outlines a viable approach to support physicians and suggests future studies considering direct effectiveness measures and programmatic adaptations. Our findings can inform and guide other healthcare systems striving to establish peer support initiatives to improve physician well-being.

Physicians' Perceptions of Clinical Decision Support to Treat Patients With Heart Failure in the ED.

Importance: Clinical decision support (CDS) could help emergency department (ED) physicians treat patients with heart failure (HF) by estimating risk, collating relevant history, and assisting with medication prescribing if physicians' perspectives inform its design and implementation. Objective: To evaluate CDS usability and workflow integration in the hands of ED physician end users who use it in clinical practice. Design, Setting, and Participants: This mixed-methods qualitative study administered semistructured interviews to ED physicians from 2 community EDs of Kaiser Permanente Northern California in 2023. The interview guide, based on the Usability Heuristics for User Interface Design and the Sociotechnical Environment models, yielded themes used to construct an electronic survey instrument sent to all ED physicians. Main Outcomes and Measures: Main outcomes were physicians' perceptions of using CDS to complement clinical decision-making, usability, and integration into ED clinical workflow. Results: Seven key informant physicians (5 [71.4%] female, median [IQR] 15.0 [9.5-15.0] years in practice) were interviewed and survey responses from 51 physicians (23 [45.1%] female, median [IQR] 14.0 [9.5-17.0] years in practice) were received from EDs piloting the CDS intervention. Response rate was 67.1% (51 of 76). Physicians suggested changes to CDS accessibility, functionality, and workflow integration. Most agreed that CDS would improve patient care and fewer than half of physicians expressed hesitation about their capacity to consistently comply with its recommendations, citing workload concerns. Physicians preferred a passive prompt that encouraged, but did not mandate, interaction with the CDS. Conclusions and Relevance: In this qualitative study of physicians who were using a novel CDS intervention to assist with ED management of patients with acute HF, several opportunities were identified to improve usability as well as several key barriers and facilitators to CDS implementation.

Developing Clinical Risk Prediction Models for Worsening Heart Failure Events and Death by Left Ventricular Ejection Fraction.

Background There is a need to develop electronic health record-based predictive models for worsening heart failure (WHF) events across clinical settings and across the spectrum of left ventricular ejection fraction (LVEF). Methods and Results We studied adults with heart failure (HF) from 2011 to 2019 within an integrated health care delivery system. WHF encounters were ascertained using natural language processing and structured data. We conducted boosted decision tree ensemble models to predict 1-year hospitalizations, emergency department visits/observation stays, and outpatient encounters for WHF and all-cause death within each LVEF category: HF with reduced ejection fraction (EF) (LVEF <40%), HF with mildly reduced EF (LVEF 40%-49%), and HF with preserved EF (LVEF ≥50%). Model discrimination was evaluated using area under the curve and calibration using mean squared error. We identified 338 426 adults with HF: 61 045 (18.0%) had HF with reduced EF, 49 618 (14.7%) had HF with mildly reduced EF, and 227 763 (67.3%) had HF with preserved EF. The 1-year risks of any WHF event and death were, respectively, 22.3% and 13.0% for HF with reduced EF, 17.0% and 10.1% for HF with mildly reduced EF, and 16.3% and 10.3% for HF with preserved EF. The WHF model displayed an area under the curve of 0.76 and mean squared error of 0.13, whereas the model for death displayed an area under the curve of 0.83 and mean squared error of 0.076. Performance and predictors were similar across WHF encounter types and LVEF categories. Conclusions We developed risk prediction models for 1-year WHF events and death across the LVEF spectrum using structured and unstructured electronic health record data and observed no substantial differences in model performance or predictors except for death, despite differences in underlying HF cause.

Automated analysis of unstructured clinical assessments improves emergency department triage performance: A retrospective deep learning analysis.

Objectives: Efficient and accurate emergency department (ED) triage is critical to prioritize the sickest patients and manage department flow. We explored the use of electronic health record data and advanced predictive analytics to improve triage performance. Methods: Using a data set of over 5 million ED encounters of patients 18 years and older across 21 EDs from 2016 to 2020, we derived triage models using deep learning to predict 2 outcomes: hospitalization (primary outcome) and fast-track eligibility (exploratory outcome), defined as ED discharge with <2 resource types used (eg, laboratory or imaging studies) and no critical events (eg, resuscitative medications use or intensive care unit [ICU] admission). We report area under the receiver operator characteristic curve (AUC) and 95% confidence intervals (CI) for models using (1) triage variables alone (demographics and vital signs), (2) triage nurse clinical assessment alone (unstructured notes), and (3) triage variables plus clinical assessment for each prediction target. Results: We found 12.7% of patients were hospitalized (n = 673,659) and 37.0% were fast-track eligible (n = 1,966,615). The AUC was lowest for models using triage variables alone: AUC 0.77 (95% CI 0.77-0.78) and 0.70 (95% CI 0.70-0.71) for hospitalization and fast-track eligibility, respectively, and highest for models incorporating clinical assessment with triage variables for both hospitalization and fast-track eligibility: AUC 0.87 (95% CI 0.87-0.87) for both prediction targets. Conclusion: Our findings highlight the potential to use advanced predictive analytics to accurately predict key ED triage outcomes. Predictive accuracy was optimized when clinical assessments were added to models using simple structured variables alone.

Clinical decision support to Optimize Care of patients with Atrial Fibrillation or flutter in the Emergency department: protocol of a stepped-wedge cluster randomized pragmatic trial (O'CAFÉ trial).

BACKGROUND: Management of adults with atrial fibrillation (AF) or atrial flutter in the emergency department (ED) includes rate reduction, cardioversion, and stroke prevention. Different approaches to these components of care may lead to variation in frequency of hospitalization and stroke prevention actions, with significant implications for patient experience, cost of care, and risk of complications. Standardization using evidence-based recommendations could reduce variation in management, preventable hospitalizations, and stroke risk. METHODS: We describe the rationale for our ED-based AF treatment recommendations. We also describe the development of an electronic clinical decision support system (CDSS) to deliver these recommendations to emergency physicians at the point of care. We implemented the CDSS at three pilot sites to assess feasibility and solicit user feedback. We will evaluate the impact of the CDSS on hospitalization and stroke prevention actions using a stepped-wedge cluster randomized pragmatic clinical trial across 13 community EDs in Northern California. DISCUSSION: We hypothesize that the CDSS intervention will reduce hospitalization of adults with isolated AF or atrial flutter presenting to the ED and increase anticoagulation prescription in eligible patients at the time of ED discharge and within 30 days. If our hypotheses are confirmed, the treatment protocol and CDSS could be recommended to other EDs to improve management of adults with AF or atrial flutter. TRIAL REGISTRATION: ClinicalTrials.gov NCT05009225 .  Registered on 17 August 2021.

Evaluation of the Emergency Severity Index in US Emergency Departments for the Rate of Mistriage.

Importance: Accurate emergency department (ED) triage is essential to prioritize the most critically ill patients and distribute resources appropriately. The most used triage system in the US is the Emergency Severity Index (ESI). Objectives: To derive and validate an algorithm to assess the rate of mistriage and to identify characteristics associated with mistriage. Design, Setting, and Participants: This retrospective cohort study created operational definitions for each ESI level that use ED visit electronic health record data to classify encounters as undertriaged, overtriaged, or correctly triaged. These definitions were applied to a retrospective cohort to assess variation in triage accuracy by facility and patient characteristics in 21 EDs within the Kaiser Permanente Northern California (KPNC) health care system. All ED encounters by patients 18 years and older between January 1, 2016, and December 31, 2020, were assessed for eligibility. Encounters with missing ESI or incomplete ED time variables and patients who left against medical advice or without being seen were excluded. Data were analyzed between January 1, 2021, and November 30, 2022. Exposures: Assigned ESI level. Main Outcomes and Measures: Rate of undertriage and overtriage by assigned ESI level based on a mistriage algorithm and patient and visit characteristics associated with undertriage and overtriage. Results: A total of 5 315 176 ED encounters were included. The mean (SD) patient age was 52 (21) years; 44.3% of patients were men and 55.7% were women. In terms of race and ethnicity, 11.1% of participants were Asian, 15.1% were Black, 21.4% were Hispanic, 44.0% were non-Hispanic White, and 8.5% were of other (includes American Indian or Alaska Native, Native Hawaiian or other Pacific Islander, and multiple races or ethnicities), unknown, or missing race or ethnicity. Mistriage occurred in 1 713 260 encounters (32.2%), of which 176 131 (3.3%) were undertriaged and 1 537 129 (28.9%) were overtriaged. The sensitivity of ESI to identify a patient with high-acuity illness (correctly assigning ESI I or II among patients who had a life-stabilizing intervention) was 65.9%. In adjusted analyses, Black patients had a 4.6% (95% CI, 4.3%-4.9%) greater relative risk of overtriage and an 18.5% (95% CI, 16.9%-20.0%) greater relative risk of undertriage compared with White patients, while Black male patients had a 9.9% (95% CI, 9.8%-10.0%) greater relative risk of overtriage and a 41.0% (95% CI, 40.0%-41.9%) greater relative risk of undertriage compared with White female patients. High relative risk of undertriage was found among patients taking high-risk medications (30.3% [95% CI, 28.3%-32.4%]) and those with a greater comorbidity burden (22.4% [95% CI, 20.1%-24.4%]) and recent intensive care unit utilization (36.7% [95% CI, 30.5%-41.4%]). Conclusions and Relevance: In this retrospective cohort study of over 5 million ED encounters, mistriage with ESI was common. Quality improvement should focus on limiting critical undertriage, optimizing resource allocation by patient need, and promoting equity.

Barriers and Opportunities Regarding Implementation of a Machine Learning-Based Acute Heart Failure Risk Stratification Tool in the Emergency Department.

Hospital admissions for patients with acute heart failure (AHF) remain high. There is an opportunity to improve alignment between patient risk and admission decision. We recently developed a machine learning (ML)-based model that stratifies emergency department (ED) patients with AHF based on predicted risk of a 30-day severe adverse event. Prior to deploying the algorithm and paired clinical decision support, we sought to understand barriers and opportunities regarding successful implementation. We conducted semi-structured interviews with eight front-line ED providers and surveyed 67 ED providers. Audio-recorded interviews were transcribed and analyzed using thematic analysis, and we had a 65% response rate to the survey. Providers wanted decision support to be streamlined into workflows with minimal disruptions. Most providers wanted assistance primarily with ED disposition decisions, and secondarily with medical management and post-discharge follow-up care. Receiving feedback on patient outcomes after risk tool use was seen as an opportunity to increase acceptance, and few providers (<10%) had significant hesitations with using an ML-based tool after education on its use. Engagement with key front-line users on optimal design of the algorithm and decision support may contribute to broader uptake, acceptance, and adoption of recommendations for clinical decisions.

Current Emergency Department Disposition of Patients With Acute Heart Failure: An Opportunity for Improvement.

Emergency department (ED) providers play a critical role in the stabilization and diagnostic evaluation of patients presenting with acute heart failure (AHF), and EDs are key areas for establishing current best practices and future considerations for the disposition of and decision making for patients with AHF. These elements include accurate risk assessment; response to initial treatment and shared decision making concerning optimal venue of care; reframing of physicians' risk perceptions for patients presenting with AHF; exploration of alternative venues of care beyond hospitalization; population-level changes in demographics, management and outcomes of HF patients; development and testing of data-driven pathways to assist with disposition decisions in the ED; and suggested outcomes for measuring success.

Risk adjusted 30-day mortality and serious adverse event rates among a large, multi-center cohort of emergency department patients with acute heart failure.

Background: Admission rates for emergency department (ED) patients with acute heart failure (AHF) remain elevated. Use of a risk stratification tool could improve disposition decision making by identifying low-risk patients who may be safe for outpatient management. Methods: We performed a secondary analysis of a retrospective, multi-center cohort of 26,189 ED patients treated for AHF from January 1, 2017 to December 31, 2018. We applied a 30-day risk model we previously developed and grouped patients into 4 categories (low, low/moderate, moderate, and high) of predicted 30-day risk of a serious adverse event (SAE). SAE consisted of death or cardiopulmonary resuscitation (CPR), intra-aorta balloon pump, endotracheal intubation, renal failure requiring dialysis, or acute coronary syndrome. We measured the 30-day mortality and composite SAE rates among patients by risk category according to ED disposition: direct discharge, discharge after observation, and hospital admission. Results: The observed 30-day mortality and total SAE rates were less than 1% and 2%, respectively, among 25% of patients in the low and low/moderate risk groups. These rates did not vary significantly by ED disposition. An additional 23% of patients were moderate risk and experienced an approximate 2% 30-day mortality rate. Conclusion: Use of a risk stratification tool could help identify lower risk AHF patients who may be appropriate for ED discharge. These findings will help inform prospective testing to determine how this risk tool can augment ED decision making.

Higher intensity of 72-h noninvasive cardiac test referral does not improve short-term outcomes among emergency department patients with chest pain.

BACKGROUND: It is unclear whether referral for cardiac noninvasive testing (NIT) following emergency department (ED) chest pain encounters improves short-term outcomes. METHODS: This was a retrospective cohort study of patients presenting with chest pain, without ST-elevation myocardial infarction or myocardial injury by serum troponin testing, between 2013 and 2019 to 21 EDs within an integrated health care system. We examined the association between NIT referral (within 72 h of the ED encounter) and a primary outcome of 60-day major adverse cardiac events (MACE). Secondary outcomes were 60-day MACE without coronary revascularization (MACE-CR) and 60-day all-cause mortality. To account for confounding by indication for NIT, we grouped patient encounters into ranked tertiles of NIT referral intensity based on the likelihood of 72-h NIT referral associated with the initially assigned emergency physician, relative to local peers and within discrete time periods. Associations between NIT referral-intensity tertile and outcomes were assessed using risk-adjusted multivariable logistic regression. RESULTS: Among 210,948 eligible patient encounters, 72-h NIT referral frequency was 11.9%, 18.3%, and 25.9% in low, intermediate, and high NIT referral-intensity encounters, respectively. Compared with the low referral-intensity tertile, there was a higher risk of 60-day MACE within the high referral-intensity tertile (odds ratio [OR] = 1.11, 95% confidence interval [CI] = 1.04 to 1.17) due to more coronary revascularizations without corresponding differences in MACE-CR or all-cause mortality. In analyses stratified by patients' estimated risk (HEART score; 50.5% lower risk, 38.7% moderate risk, 10.8% higher risk), the difference in 60-day MACE was primarily attributable to moderate-risk encounters (OR = 1.15, 95% CI = 1.08 to 1.24), with no differences among either lower- (OR = 1.10, 95% CI = 0.92 to 1.31) or higher- (OR = 1.01, 95% CI = 0.90 to 1.14) risk encounters. CONCLUSION: Higher referral intensity for 72-h NIT was associated with higher risk of coronary revascularization but no difference in adverse events within 60 days. These findings further call into question the urgency of NIT among ED patients without objective evidence of myocardial injury.

Graded Coronary Risk Stratification for Emergency Department Patients With Chest Pain: A Controlled Cohort Study.

Background Resource utilization among emergency department (ED) patients with possible coronary chest pain is highly variable. Methods and Results Controlled cohort study amongst 21 EDs of an integrated healthcare system examining the implementation of a graded coronary risk stratification algorithm (RISTRA-ACS [risk stratification for acute coronary syndrome]). Thirteen EDs had access to RISTRA-ACS within the electronic health record (RISTRA sites) beginning in month 24 of a 48-month study period (January 2016 to December 2019); the remaining 8 EDs served as contemporaneous controls. Study participants had a chief complaint of chest pain and serum troponin measurement in the ED. The primary outcome was index visit resource utilization (observation unit or hospital admission, or 7-day objective cardiac testing). Secondary outcomes were 30-day objective cardiac testing, 60-day major adverse cardiac events (MACE), and 60-day MACE-CR (MACE excluding coronary revascularization). Difference-in-differences analyses controlled for secular trends with stratification by estimated risk and adjustment for risk factors, ED physician and facility. A total of 154 914 encounters were included. Relative to control sites, 30-day objective cardiac testing decreased at RISTRA sites among patients with low (≤2%) estimated 60-day MACE risk (-2.5%, 95% CI -3.7 to -1.2%, P<0.001) and increased among patients with non-low (>2%) estimated risk (+2.8%, 95% CI +0.6 to +4.9%, P=0.014), without significant overall change (-1.0%, 95% CI -2.1 to 0.1%, P=0.079). There were no statistically significant differences in index visit resource utilization, 60-day MACE or 60-day MACE-CR. Conclusions Implementation of RISTRA-ACS was associated with better allocation of 30-day objective cardiac testing and no change in index visit resource utilization or 60-day MACE. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT03286179.

Clinical characteristics of COVID-19 patients evaluated in the emergency department: A retrospective cohort study of 801 cases.

BACKGROUND: Coronavirus disease 2019 (COVID-19), the disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has extracted devastating tolls. Despite its pervasiveness, robust information on disease characteristics in the emergency department (ED) and how that information predicts clinical course remain limited. METHODS: We conducted a retrospective cohort study of the first ED visit from SARS-CoV-2-positive patients in our health system, from February 21, 2020 to April 5, 2020. We reviewed each patient's ED visit(s) and included the first visit with symptoms consistent with COVID-19. We collected demographic, clinical, and treatment variables from electronic health records and structured manual chart review. We used multivariable logistic regression to examine the association between patient characteristics and 2 primary outcomes: a critical outcome and hospitalization from index visit. Our critical outcome was defined as death or advanced respiratory support (high flow nasal cannula or greater) within 21 days. RESULTS: Of the first 1030 encounters, 801 met our inclusion criteria: 15% were over age 75 years, 47% were female, and 24% were non-Hispanic white. We found 161 (20%) had a critical outcome and 393 (49%) were hospitalized. Independent predictors of a critical outcome included a history of hypertension, abnormal chest x-ray, elevated neutrophil to lymphocyte ratio, elevated blood urea nitrogen (BUN), measured fever, and abnormal respiratory vital signs (respiratory rate, oxygen saturation). Independent predictors of hospitalization included abnormal pulmonary auscultation, elevated BUN, measured fever, and abnormal respiratory vital signs. CONCLUSIONS: In this large, diverse study of ED patients with COVID-19, we have identified numerous clinical characteristics that have independent associations with critical illness and hospitalization.

Outcomes among acute heart failure emergency department patients by preserved vs. reduced ejection fraction.

AIMS: This study aimed to assess short-term outcomes among emergency department (ED) patients with acute heart failure (AHF) by preserved (≥50%) vs. reduced (<50%) ejection fraction (EF). METHODS AND RESULTS: We conducted a retrospective, multicentre study of adult ED patients with AHF from 2017 to 2018 in an integrated healthcare system with 21 hospitals. Among patients with known EF, our primary outcome was 30 day all-cause mortality, comparing patients with heart failure with preserved EF (HFpEF) and heart failure with reduced EF (HFrEF), adjusted for known risk factors. We ran separate multivariate regression models to compare 30 day mortality between HFpEF and HFrEF patients stratified by ED disposition (admit, observe, and discharge). Our secondary outcomes were adjusted 30 day all-cause return hospital admission and rates of non-fatal serious adverse events, including new intra-aorta balloon pump, endotracheal intubation, renal failure requiring dialysis, myocardial infarction, or coronary revascularization. We conducted a sensitivity analysis among patients with EF ≤ 40% and compared our primary and secondary outcomes among patients with EF ≤ 40% with those with EF ≥ 50%. Among the 26 050 total ED encounters for AHF, 15 275 (58.6%) had known EF and 62.4% had HFpEF. The mean age was 76, 49.6% were women, and 60.5% were white. We found that 62.4% of patients were admitted, 18.3% were observed, and 19.3% were discharged from the ED. The 30 day all-cause mortality rate was lowest among discharged patients (3.9%), intermediate among observed patients (5.9%), and highest among admitted patients (13.9%). Overall, the adjusted 30 day mortality rate was significantly higher among HFpEF patients compared with HFrEF patients (10.2% vs. 8.4%, P = 0.0004). HFpEF patients had higher mortality regardless of ED disposition, although the difference was only significant among admitted patients. The adjusted 30 day return hospital admission rates were not significantly different between HFpEF and HFrEF patients (17.9% vs. 17.8%, P = 0.89). The adjusted 30 day non-fatal serious adverse event rates were significantly higher among HFrEF patients compared with HFpEF patients (13.7% vs. 11.1%, P < 0.0001), driven by myocardial infarction and coronary revascularization. We found that 3692 patients had EF ≤ 40%. Patients with EF ≥ 50% had significantly higher adjusted 30 day mortality rates compared with those with EF ≤ 40% (10.2% vs. 8.4%, P < 0.05). CONCLUSION: In a contemporary population, almost three quarters of ED patients with AHF and known EF have HFpEF. These patients have higher 30 day adjusted mortality compared with those with HFrEF. Further studies might evaluate the underlying factors associated with this difference and target interventions to improve outcomes.

Prospective Validation and Comparative Analysis of Coronary Risk Stratification Strategies Among Emergency Department Patients With Chest Pain.

Background Coronary risk stratification is recommended for emergency department patients with chest pain. Many protocols are designed as "rule-out" binary classification strategies, while others use graded-risk stratification. The comparative performance of competing approaches at varying levels of risk tolerance has not been widely reported. Methods and Results This is a prospective cohort study of adult patients with chest pain presenting between January 2018 and December 2019 to 13 medical center emergency departments within an integrated healthcare delivery system. Using an electronic clinical decision support interface, we externally validated and assessed the net benefit (at varying risk thresholds) of several coronary risk scores (History, ECG, Age, Risk Factors, and Troponin [HEART] score, HEART pathway, Emergency Department Assessment of Chest Pain Score Accelerated Diagnostic Protocol), troponin-only strategies (fourth-generation assay), unstructured physician gestalt, and a novel risk algorithm (RISTRA-ACS). The primary outcome was 60-day major adverse cardiac event defined as myocardial infarction, cardiac arrest, cardiogenic shock, coronary revascularization, or all-cause mortality. There were 13 192 patient encounters included with a 60-day major adverse cardiac event incidence of 3.7%. RISTRA-ACS and HEART pathway had the lowest negative likelihood ratios (0.06, 95% CI, 0.03-0.10 and 0.07, 95% CI, 0.04-0.11, respectively) and the greatest net benefit across a range of low-risk thresholds. RISTRA-ACS demonstrated the highest discrimination for 60-day major adverse cardiac event (area under the receiver operating characteristic curve 0.92, 95% CI, 0.91-0.94, P<0.0001). Conclusions RISTRA-ACS and HEART pathway were the optimal rule-out approaches, while RISTRA-ACS was the best-performing graded-risk approach. RISTRA-ACS offers promise as a versatile single approach to emergency department coronary risk stratification. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT03286179.

Use of Machine Learning to Develop a Risk-Stratification Tool for Emergency Department Patients With Acute Heart Failure.

STUDY OBJECTIVE: We use variables from a recently derived acute heart failure risk-stratification rule (STRATIFY) as a basis to develop and optimize risk prediction using additional patient clinical data from electronic health records and machine-learning models. METHODS: Using a retrospective cohort design, we identified all emergency department (ED) visits for acute heart failure between January 1, 2017, and December 31, 2018, among adult health plan members of a large system with 21 EDs. The primary outcome was any 30-day serious adverse event, including death, cardiopulmonary resuscitation, balloon-pump insertion, intubation, new dialysis, myocardial infarction, or coronary revascularization. Starting with the 13 variables from the STRATIFY rule (base model), we tested whether predictive accuracy in a different population could be enhanced with additional electronic health record-based variables or machine-learning approaches (compared with logistic regression). We calculated our derived model area under the curve (AUC), calculated test characteristics, and assessed admission rates across risk categories. RESULTS: Among 26,189 total ED encounters, mean patient age was 74 years, 51.7% were women, and 60.7% were white. The overall 30-day serious adverse event rate was 18.8%. The base model had an AUC of 0.76 (95% confidence interval 0.74 to 0.77). Incorporating additional variables led to improved accuracy with logistic regression (AUC 0.80; 95% confidence interval 0.79 to 0.82) and machine learning (AUC 0.85; 95% confidence interval 0.83 to 0.86). We found that 11.1%, 25.7%, and 48.9% of the study population had predicted serious adverse event risk of less than or equal to 3%, less than or equal to 5%, and less than or equal to 10%, respectively, and 28% of those with less than or equal to 3% risk were admitted. CONCLUSION: Use of a machine-learning model with additional variables improved 30-day risk prediction compared with conventional approaches.