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.

Downstream Emergency Department and Hospital Utilization Comparably Low Following In-Person Versus Telemedicine Primary Care for High-Risk Conditions.

BACKGROUND: Telemedicine use expanded greatly during the COVID-19 pandemic. More data is needed to understand how this shift may impact other venues of acute care delivery. OBJECTIVE: We evaluate the association of visit modality (telephone, video, or office) and downstream emergency department (ED) and hospital visits among primary care visits for acute, time-sensitive conditions. DESIGN: Observational study of patient-scheduled primary care telemedicine and office visits for acute conditions (cardiac, gastrointestinal, neurologic, musculoskeletal, and head and neck) in a large, integrated healthcare delivery system. PARTICIPANTS: Adults with a new self-booked primary care appointment for an eligible acute condition from January 1, 2022, to December 31, 2022 (with no primary care, ED, or hospital visits in prior 30 days). INTERVENTIONS: Visit modality, including office, video, or telephone. MAIN MEASURES: Seven-day ED and hospital utilization, adjusted for patient and visit characteristics. KEY RESULTS: Among 258,958 primary care visits by 239,240 adult patients, 57.7% were telemedicine visits; of these, 72.4% were telephone and 27.6% were video. Telephone visits were the timeliest, with over 70% of visits scheduled within 1 day of booking. Rates of 7-day ED utilization were low, and varied by condition group, with cardiac visits having the highest rates (4.8%) and musculoskeletal visits having the lowest (0.8%). There was less than a 1% absolute difference in ED use by visit modality for all condition types; however, telephone visits were associated with slightly higher rates than video visits. The 7-day hospitalization rate was less than 1% and observed between visit type differences varied by clinical condition. CONCLUSIONS: Among office, telephone, and video visits in primary care for potentially high-risk, time-sensitive conditions, downstream ED and hospital use were uncommon. ED utilization was lower for video visits than telephone visits, although telephone visits were timelier and may offer a safe and accessible option for acute care.

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.

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.

Validation of the Pediatric Appendicitis Risk Calculator (pARC) in a Community Emergency Department Setting.

STUDY OBJECTIVE: The pediatric Appendicitis Risk Calculator (pARC) is a validated clinical tool for assessing a child's probability of appendicitis. Our objective was to assess the performance of the pARC in community emergency departments (EDs) and to compare its performance with that of the Pediatric Appendicitis Score (PAS). METHODS: We conducted a prospective validation study from October 1, 2016, to April 30, 2018, in 11 community EDs serving general populations. Patients aged 5 to 20.9 years and with a chief complaint of abdominal pain and less than or equal to 5 days of right-sided or diffuse abdominal pain were eligible for study enrollment. Our primary outcome was the presence or absence of appendicitis within 7 days of the index visit. We reported performance characteristics and secondary outcomes by pARC risk strata and compared the receiver operator characteristic (ROC) curves of the PAS and pARC. RESULTS: We enrolled 2,089 patients with a mean age of 12.4 years, 46% of whom were male patients. Appendicitis was confirmed in 353 patients (16.9%), of whom 55 (15.6%) had perforated appendixes. Fifty-four percent of patients had very low (<5%) or low (5% to 14%) predicted risk, 43% had intermediate risk (15% to 84%), and 4% had high risk (≥85%). In the very-low- and low-risk groups, 1.4% and 3.0% of patients had appendicitis, respectively. The area under the ROC curve was 0.89 (95% confidence interval 0.87 to 0.92) for the pARC compared with 0.80 (95% confidence interval 0.77 to 0.82) for the PAS. CONCLUSION: The pARC accurately assessed appendicitis risk for children aged 5 years and older in community EDs and the pARC outperformed the PAS.

Increasing Safe Outpatient Management of Emergency Department Patients With Pulmonary Embolism: A Controlled Pragmatic Trial.

Background: Many low-risk patients with acute pulmonary embolism (PE) in the emergency department (ED) are eligible for outpatient care but are hospitalized nonetheless. One impediment to home discharge is the difficulty of identifying which patients can safely forgo hospitalization. Objective: To evaluate the effect of an integrated electronic clinical decision support system (CDSS) to facilitate risk stratification and decision making at the site of care for patients with acute PE. Design: Controlled pragmatic trial. (ClinicalTrials.gov: NCT03601676). Setting: All 21 community EDs of an integrated health care delivery system (Kaiser Permanente Northern California). Patients: Adult ED patients with acute PE. Intervention: Ten intervention sites selected by convenience received a multidimensional technology and education intervention at month 9 of a 16-month study period (January 2014 to April 2015); the remaining 11 sites served as concurrent controls. Measurements: The primary outcome was discharge to home from either the ED or a short-term (<24-hour) outpatient observation unit based in the ED. Adverse outcomes included return visits for PE-related symptoms within 5 days and recurrent venous thromboembolism, major hemorrhage, and all-cause mortality within 30 days. A difference-in-differences approach was used to compare pre-post changes at intervention versus control sites, with adjustment for demographic and clinical characteristics. Results: Among 881 eligible patients diagnosed with PE at intervention sites and 822 at control sites, adjusted home discharge increased at intervention sites (17.4% pre- to 28.0% postintervention) without a concurrent increase at control sites (15.1% pre- and 14.5% postintervention). The difference-in-differences comparison was 11.3 percentage points (95% CI, 3.0 to 19.5 percentage points; P = 0.007). No increases were seen in 5-day return visits related to PE or in 30-day major adverse outcomes associated with CDSS implementation. Limitation: Lack of random allocation. Conclusion: Implementation and structured promotion of a CDSS to aid physicians in site-of-care decision making for ED patients with acute PE safely increased outpatient management. Primary Funding Source: Garfield Memorial National Research Fund and The Permanente Medical Group Delivery Science and Physician Researcher Programs.

Outpatient Management of Emergency Department Patients With Acute Pulmonary Embolism: Variation, Patient Characteristics, and Outcomes.

STUDY OBJECTIVE: Outpatient management of emergency department (ED) patients with acute pulmonary embolism is uncommon. We seek to evaluate the facility-level variation of outpatient pulmonary embolism management and to describe patient characteristics and outcomes associated with home discharge. METHODS: The Management of Acute Pulmonary Embolism (MAPLE) study is a retrospective cohort study of patients with acute pulmonary embolism undertaken in 21 community EDs from January 2013 to April 2015. We gathered demographic and clinical variables from comprehensive electronic health records and structured manual chart review. We used multivariable logistic regression to assess the association between patient characteristics and home discharge. We report ED length of stay, consultations, 5-day pulmonary embolism-related return visits and 30-day major hemorrhage, recurrent venous thromboembolism, and all-cause mortality. RESULTS: Of 2,387 patients, 179 were discharged home (7.5%). Home discharge varied significantly between EDs, from 0% to 14.3% (median 7.0%; interquartile range 4.2% to 10.9%). Median length of stay for home discharge patients (excluding those who arrived with a new pulmonary embolism diagnosis) was 6.0 hours (interquartile range 4.6 to 7.2 hours) and 81% received consultations. On adjusted analysis, ambulance arrival, abnormal vital signs, syncope or presyncope, deep venous thrombosis, elevated cardiac biomarker levels, and more proximal emboli were inversely associated with home discharge. Thirteen patients (7.2%) who were discharged home had a 5-day pulmonary embolism-related return visit. Thirty-day major hemorrhage and recurrent venous thromboembolism were uncommon and similar between patients hospitalized and those discharged home. All-cause 30-day mortality was lower in the home discharge group (1.1% versus 4.4%). CONCLUSION: Home discharge of ED patients with acute pulmonary embolism was uncommon and varied significantly between facilities. Patients selected for outpatient management had a low incidence of adverse outcomes.

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.

Pilot trial of an electronic decision support to improve care for emergency department patients with acute heart failure.

AIMS: Emergency department (ED) providers play an important role in the management of patients with acute heart failure (AHF). We present findings from a pilot study of an electronic decision support that includes personalized risk estimates using the STRIDE-HF risk tool and tailored recommendations for initiating guideline directed medical therapy (GDMT) among appropriate patients. METHODS: Among ED patients treated for AHF who were discharged from the ED or the ED-based observation unit in two EDs from 1 January 2023 to 31 July 2023, we assess prescriptions to the four classes of GDMT at two intervals: (1) ED arrival and (2) ED discharge. Specifically, we report active prescriptions for beta-blockers (BBs), renin-angiotensin receptor system inhibitors (RASis), sodium-glucose transport protein 2 inhibitors (SGLT2is) and mineralocorticoid receptor antagonists (MRA) among patients with reduced ejection fraction (HFrEF) and mildly reduced (HFmrEF). Second, we describe rates of 30-day serious adverse events (SAE) (death, cardiopulmonary resuscitation, balloon-pump insertion, intubation, new dialysis, myocardial infarction or coronary revascularization) among patients predicted to be very low risk by STRIDE-HF and discharged home. RESULTS: Among 234 discharged patients, 55% were female and 76% were non-White. We found 51 (21.8%), 21 (9.0%) and 126 (53.8%) had HFrEF, HFmEF and HFpEF, respectively, while 36 (15.4%) were missing EF, and 51 (22%) were very low risk, 82 (35%) were low risk, 60 (26%) were medium risk and 41 (18%) were high risk. Among HFrEF patients, 68.6%, 66.7%, 25.5% and 19.6% were on a RASi, BB, SGLT2i and MRA, respectively, at ED arrival, while 42.9%, 66.7%, 14.3% and 4.8% of HFmrEF patients were on a RASi, BB, SGLT2i and MRA, respectively. Among patients with HFpEF, only 6 (4.8%) were on an SGLT2i at ED arrival. The most prescribed new medication at ED discharge was an SGLT2i, with a nearly 10% increase in the proportion of patients with an active prescription for SGLT2i at ED discharge among HFrEF and HFmEF patients. We observed no 30-day SAE among the 51 patients predicted to be very low risk and discharged home. CONCLUSIONS: Ongoing treatment with GDMT at ED arrival was sub-optimal. Initiation among appropriate patients at discharge may be feasible and safe.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.