Effect of a Self-care Intervention on 90-Day Outcomes in Patients With Acute Heart Failure Discharged From the Emergency Department: A Randomized Clinical Trial | Cardiology | JAMA Cardiology | JAMA Network
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Figure 1.  Screening, Enrollment, and Follow-up in the Get With the Guidelines in Emergency Department Patients With Heart Failure Clinical Trial
Screening, Enrollment, and Follow-up in the Get With the Guidelines in Emergency Department Patients With Heart Failure Clinical Trial
Figure 2.  Cardiovascular Death and Heart Failure Adverse Events Over 90 Days Stratified by Study Arm
Cardiovascular Death and Heart Failure Adverse Events Over 90 Days Stratified by Study Arm
Figure 3.  Kansas City Cardiomyopathy Questionnaire-12 (KCCQ-12) Summary Scores (SS) at Baseline and Study Days by Study Arm
Kansas City Cardiomyopathy Questionnaire-12 (KCCQ-12) Summary Scores (SS) at Baseline and Study Days by Study Arm

A, KCCQ-12 SS at baseline and 30 days. B, KCCQ-12 SS at baseline and 90 days. Boxes range from the 25th to 75th percentile, and the lower and upper whiskers represent 1.5 times the interquartile range.

Table 1.  Patient Demographic and Clinical Characteristics by Study Arma
Patient Demographic and Clinical Characteristics by Study Arma
Table 2.  30-Day and 90-Day Global Rank Primary Outcome Adjusted for Known Measures of HF Severity
30-Day and 90-Day Global Rank Primary Outcome Adjusted for Known Measures of HF Severity
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Original Investigation
November 18, 2020

Effect of a Self-care Intervention on 90-Day Outcomes in Patients With Acute Heart Failure Discharged From the Emergency Department: A Randomized Clinical Trial

Author Affiliations
  • 1Department of Emergency Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
  • 2Geriatric Research, Education, and Clinical Center, Tennessee Valley Healthcare System, Nashville
  • 3Department of Emergency Medicine, Detroit Medical Center, Detroit, Michigan
  • 4Department of Emergency Medicine, Indiana University Medical Center, Indianapolis
  • 5Department of Emergency Medicine, Thomas Jefferson University Medical Center, Philadelphia, Pennsylvania
  • 6Department of Emergency Medicine, Washington University Medical Center in St Louis, St Louis, Missouri
  • 7Department of Emergency Medicine, University of Texas Southwestern Medical Center, Dallas
  • 8Department of Emergency Medicine, University of Cincinnati Medical Center, Cincinnati, Ohio
  • 9Department of Emergency Medicine, Wake Forest University Medical Center, Winston-Salem, North Carolina
  • 10Department of Emergency Medicine, Virginia Commonwealth University Medical Center, Richmond, Virginia
  • 11Department of Emergency Medicine, American Heart Association
  • 12Department of Emergency Medicine, University of Iowa Medical Center, Iowa City
  • 13Department of Emergency Medicine, Icahn School of Medicine at Mount Sinai, New York, New York
  • 14School of Nursing, Emory University, Atlanta, Georgia
  • 15Department of Emergency Medicine, Baylor College of Medicine, Houston, Texas
  • 16School of Medicine, Emory University, Atlanta, Georgia
  • 17Department of Emergency Medicine, Metro Health Medical Center, Cleveland, Ohio
  • 18Department of Emergency Medicine, Stony Brook University Medical Center, Stony Brook, New York
  • 19Department of Medicine, University of Mississippi Medical Center, Jackson
  • 20Patient Representative, Stockbridge, Georgia
JAMA Cardiol. 2021;6(2):200-208. doi:10.1001/jamacardio.2020.5763
Key Points

Question  Does self-care coaching improve heart failure events and quality of life in patients with acute heart failure discharged after emergency department–based management?

Findings  In this randomized clinical trial including 479 patients with acute heart failure, there were no significant differences in the global rank primary outcome at 90 days between the intervention and usual care arms. However, there were significant differences in 30-day global rank and health status favoring the intervention arm.

Meaning  These data suggest that a self-care management plan does not impact 90-day events but may provide short-term improvements in heart failure outcomes and health status after emergency department–based management and discharge.

Abstract

Importance  Up to 20% of patients who present to the emergency department (ED) with acute heart failure (AHF) are discharged without hospitalization. Compared with rates in hospitalized patients, readmission and mortality are worse for ED patients.

Objective  To assess the impact of a self-care intervention on 90-day outcomes in patients with AHF who are discharged from the ED.

Design, Setting, and Participants  Get With the Guidelines in Emergency Department Patients With Heart Failure was an unblinded, parallel-group, multicenter randomized trial. Patients were randomized 1:1 to usual care vs a tailored self-care intervention. Patients with AHF discharged after ED-based management at 15 geographically diverse EDs were included. The trial was conducted from October 28, 2015, to September 5, 2019.

Interventions  Home visit within 7 days of discharge and twice-monthly telephone-based self-care coaching for 3 months.

Main Outcomes and Measures  The primary outcome was a global rank of cardiovascular death, HF-related events (unscheduled clinic visit due to HF, ED revisit, or hospitalization), and changes in the Kansas City Cardiomyopathy Questionnaire-12 (KCCQ-12) summary score (SS) at 90 days. Key secondary outcomes included the global rank outcome at 30 days and changes in the KCCQ-12 SS score at 30 and 90 days. Intention-to-treat analysis was performed for the primary, secondary, and safety outcomes. Per-protocol analysis was conducted including patients who completed a home visit and had scheduled outpatient follow-up in the intervention arm.

Results  Owing to slow enrollment, 479 of a planned 700 patients were randomized: 235 to the intervention arm and 244 to the usual care arm. The median age was 63.0 years (interquartile range, 54.7-70.2), 302 patients (63%) were African American, 305 patients (64%) were men, and 178 patients (37%) had a previous ejection fraction greater than 50%. There was no significant difference in the primary outcome between patients in the intervention vs usual care arm (hazard ratio [HR], 0.89; 95% CI, 0.73-1.10; P = .28). At day 30, patients in the intervention arm had significantly better global rank (HR, 0.80; 95% CI, 0.64-0.99; P = .04) and a 5.5-point higher KCCQ-12 SS (95% CI, 1.3-9.7; P = .01), while at day 90, the KCCQ-12 SS was 2.7 points higher (95% CI, −1.9 to 7.2; P = .25).

Conclusions and Relevance  The self-care intervention did not improve the primary global rank outcome at 90 days in this trial. However, benefit was observed in the global rank and KCCQ-12 SS at 30 days, suggesting that an early benefit of a tailored self-care program initiated at an ED visit for AHF was not sustained through 90 days.

Trial Registration  ClinicalTrials.gov Identifier: NCT02519283

Introduction

In the US, there are approximately 1 million emergency department (ED) visits for acute heart failure (AHF) each year, and more than 80% of these patients are hospitalized.1 This finding is in contrast to the 14% admission rate among the general ED population.2 Up to 50% of patients hospitalized with AHF may lack high-risk features, suggesting that some hospitalizations may be avoidable.3,4 Among the reasons for this high rate of AHF admissions is the lack of standard post-ED care pathways, especially in patients with limited access to outpatient care.5,6 The ED is the safety net, frequently serving as a primary source of care for patients who are uninsured or underinsured or who have poor access to care. Over 50% of AHF care occurs at safety net hospitals.1 Patients with AHF without insurance are more likely to be discharged from the ED.1 Previous studies have suggested that education interventions reduce readmissions in uninsured and underinsured patients and support the important role of the ED.7 African American patients are more likely to present to the ED than to be directly admitted, underscoring the disparities in access to outpatient care.8 Thus, the ED is the primary access point for most patients with AHF, especially for those of minority ethnicity and race and those who lack access to primary care.

These factors underscore the importance of emergency care clinician–targeted transition of care initiatives to avoid unnecessary hospitalization while ensuring patient safety and well-being. Initiatives to improve transitions of care at hospital discharge for inpatients are well established, but individuals with AHF discharged after ED care without hospitalization are not included in these transition programs.9,10 Optimal transition of care includes ensuring guideline-recommended care by clinicians, the ability to adhere to prescribed therapy, and other self-care behaviors.11-13 Strategies for care transition and safe discharge from the ED are an unmet need. We conducted a randomized clinical trial of patients with AHF discharged after ED-based management to determine the impact of a transition program and a self-care intervention on clinical and patient-oriented outcomes.

Methods
Trial Design and Participants

Detailed study methods have been reported previously for Get With the Guidelines in Emergency Department Patients With Heart Failure (GUIDED-HF) and describe the involvement of patients, caregivers, and stakeholders.14 Outcomes were adjudicated by a clinical event committee, and an independent data and safety monitoring board oversaw trial safety and efficacy. All participants provided written informed consent, and data were deidentified. The institutional review board of each participating institution approved the study. This study followed the Consolidated Standards of Reporting Trials (CONSORT) reporting guideline. The study protocol is provided in Supplement 1.

Patients were screened in 15 geographically diverse, academically affiliated EDs in the US by emergency research personnel with experience in both HF and clinical trials. Patients who presented with signs or symptoms of AHF were screened for inclusion. Key inclusion criteria were (1) presence of AHF as determined by the ED clinician, (2) planned discharge within 23 hours or less, (3) age of 21 years or older, and (4) history of HF. Key exclusion criteria were (1) inability to adhere to the protocol, (2) systolic blood pressure lower than 100 mm Hg at randomization, (3) evidence of acute coronary syndrome, and (4) current outpatient inotrope infusion. Patients with both reduced and preserved left ventricular ejection fraction were eligible. Patients treated in an ED-based observation unit were eligible if total ED time remained less than 29 hours. Stratification by site and randomization at the patient level was done using random permuted blocks in a 1:1 ratio to a post-ED discharge transition plan (intervention group) vs structured usual care (control group). Study coordinators received treatment assignment by accessing a password-protected electronic randomization module. Patients and study team members who were assigned as self-care coaches were aware of the treatment arm assignment. Outcomes assessors at the sites were blinded to treatment arm assignment.

Trial Interventions and Measures

Patients randomized to the usual care (control) group received a structured discharge process including HF medication reconciliation, HF medication prescriptions, and an appointment for a 7-day follow-up with an HF clinician.

Patients randomized to the intervention group also received structured usual care plus a 4-component tailored discharge plan based on their individual barriers to outpatient management. The goal of the 4-component plan was to identify self-care deficiencies and address them in a stepwise manner starting with the home visit and continuing through the biweekly coaching calls. The study team visited the patient at home within 7 days of ED discharge to begin a tailored self-care plan based on perceived self-care barriers identified during the in-home study team assessment. If a patient was unable to schedule a home visit within 7 days, a telehealth visit was performed. Areas evaluated included eating habits, recording daily weight, instructions on how to use a weekly medication organizer, and recognition of early signs and symptoms of worsening HF. The study team contacted the patients twice per month via telephone to conduct self-care coaching. These calls helped to identify persistent self-care deficiencies and strategize ways to overcome them.

The primary trial outcome was a 90-day global rank composite outcome15,16 based on a prespecified hierarchical ranking of (1) cardiovascular (CV)-associated death, (2) HF-related events (hospitalization or ED visit for AHF, or clinic visit for AHF during which intravenous diuretics were used), and (3) change in the Kansas City Cardiomyopathy Questionnaire-12 (KCCQ-12)17 summary score (SS), including physical limitations, symptom frequency, quality of life, and social limitation subdomains, with a score range of 0 to 100. Patients with earliest CV death or hospitalization ranked the lowest (worst). The second hierarchy included patients alive at 90 days but with any of the HF-related events, also based on time to earliest occurrence of any of the HF-related events. The remaining patients who did not experience CV death or HF-related events by day 90 were ranked based on 90-day changes in KCCQ-12 SS; patients with the largest decrease ranked the lowest and largest increase ranked the highest. Patients who died owing to non-CV causes or were lost to follow-up within 90 days were censored in the first hierarchy. Patients not ranked in the first 2 hierarchies and with missing 90-day changes in KCCQ-12 SS were censored at the highest rank in the second hierarchy. Key secondary outcomes included the global rank outcome at 30 days, time to CV death or HF-related events (days to CV death or HF adverse events) over 30 and 90 days, and changes in KCCQ-12 SS at days 30 and 90. Our safety outcome was the time to first all-cause ED visit, all-cause hospital admission, or all-cause death over 90 days.

Populations and Data Collection

The impact of the intervention within the overall population as well as vulnerable populations was assessed. Health literacy data were collected, and participant address information enabled the use of geocoding to define low socioeconomic status via the area deprivation index (ADI).18 Vulnerable populations were defined as (1) non-White race/ethnicity, (2) brief health literacy score less than 9,19 or (3) a national ADI score greater than 85.20

Details of data collection have been published previously.14 Medical records review and patient or caregiver telephone calls on day 30 ± 7 and day 90 ± 14 were conducted to assess outcome events. To maintain blinding of reviewers, each site had separate study personnel collecting data on 30- and 90-day events who did not perform the self-care coaching. Cardiovascular death and HF events were adjudicated by the clinical event committee, which included 2 emergency physicians and 1 cardiologist. If the 2 reviewers disagreed, a third reviewer adjudicated disagreements. Reviewers were blinded and records were redacted to remove identifiable information or reveal the randomized allocation. The data and safety monitoring board met regularly to ensure participant safety.

Statistical Analysis

The power calculation was based on a time-to-event analysis of CV death or HF-related events over 90 days using a Cox proportional hazards (PH) model.21 The power calculation was conducted based on expected event rates of 62% in the usual care arm and censoring rates of 4% at 90 days based on existing literature.22-25 The study was stopped early owing to slower-than-expected enrollment. With lower-than-expected event rates and less than targeted accrual of 700 patients, the executive committee, with funding agency approval, changed the primary outcome to a global rank composite before database lock. At the end of the enrollment period, a sample size of 530 participants randomized 1:1 provided 87% power to detect a 20% relative rate reduction keeping type I error at 5%.26-28

Descriptive statistics are presented as medians (interquartile ranges [IQRs]), counts, and proportions as appropriate. The Wilcoxon rank sum and Pearson χ2 tests were used to compare continuous and categorical data, respectively. Intention-to-treat analysis was performed for the primary, secondary, and safety outcomes. Intervention effects among the vulnerable populations (minority racial/ethnic groups, low socioeconomic status, and low health literacy) were assessed. A per-protocol analysis was conducted including patients who completed the home visit and had scheduled outpatient follow-up in the intervention arm. Adjusted analyses controlled for age, sex, systolic blood pressure, left ventricular ejection fraction, estimated glomerular filtration rate, KCCQ-12 SS, race/ethnicity, brief health literacy score, and national ADI rank. Missing covariates were imputed with predictive mean matching.29 Since the primary global rank outcome was subject to censoring, a ranked-based semiparametric approach using a PH model was adopted. The PH model was also used for time to CV death and HF-related events and the safety outcome. Hazard ratios (HRs) and 95% CIs were calculated from the PH models. Changes in the KCCQ-12 SS were not linear and were therefore modeled at the 2 time points separately using linear regression models at days 30 and 90, while adjusting for baseline KCCQ-12 SS. All tests were 2-tailed and considered statistically significant if P < .05. Statistical analysis was performed using R Statistical Software, version 3.5.2 (R Foundation).

Results
Sites and Participants

From October 28, 2015, to September 5, 2019, 7148 patients were screened at 15 sites, and a total of 491 patients (6.9%) were randomized (245 to usual care and 246 to the intervention arm). Common reasons for exclusion among patients with AHF were hospital admission and new-onset HF (Figure 1). Twelve patients withdrew consent (1 in the usual care arm and 11 in the intervention arm) after ED discharge but before the 30-day follow-up, leaving 479 patients (244 in the usual care arm and 235 in the intervention arm) available for analysis.

Median age of the cohort was 63.0 years (IQR, 54.7-70.2), 302 patients (63%) were African American, 305 patients (64%) were men, 174 patients (36%) were women, and 178 patients (40%) had a prior ejection fraction greater than 50%. Comorbidities and laboratory values, including renal function and b-type natriuretic peptide levels, were balanced between the 2 arms (Table 1). Of 466 patients discharged with an initial troponin value available, 74 patients (15.9%) had a troponin value above the site-specific cutoff for myocardial injury. The proportion of patients with low health literacy scores (brief health literacy score <9) was 14% in the usual care arm and 11% in the intervention arm. The median ADI was 83 for each arm (IQR, 58-96 overall, 58-95 for the control group, and 58-96 for the intervention group). Based on a cutoff of 85 for low socioeconomic status,20 216 patients (45%) had low socioeconomic status.

In-person (184 [78%]) or telehealth (25 [11%]) home visits were completed for 209 participants (89%) in the intervention arm. Coaching calls were completed for 187 patients (80%) in the first 30 days and 175 patients (74%) for the 30- to 90-day window. The time to complete the home visit and twice-monthly calls was variable depending on the patient’s needs but was estimated to be less than 10 hours per patient. Guideline-directed medical therapy for HF was prescribed in a large proportion of patients without meaningful imbalance between the groups (Table 1). Data for CV death and HF-related events were available on all patients, and paired baseline and follow-up KCCQ-12 SS were available for 350 patients (73%) at 30 days and 345 patients (72%) at 90 days.

There was no significant difference in the primary outcome of efficacy between the 2 arms (HR, 0.89; 95% CI, 0.73-1.10; P = .28) (Table 2). There was no significant difference in unadjusted 90-day CV and HF events (36% usual care vs 32% intervention, P = .21) (eTable in Supplement 2; Figure 2) and in adjusted 90-day CV and HF events (HR, 0.78; 95% CI, 0.57-1.06; P = .11). There was a 20% risk reduction in the 30-day global rank outcome in favor of the intervention (HR, 0.80; 95% CI, 0.64-0.99; P = .04) (Table 2) and no significant risk reduction in 30-day CV death and HF events (18% vs 14%, P = .18).

There were no significant differences in all-cause death or ED revisit or hospital admission, which occurred in 58% of participants in both arms at 90 days. Patients with an elevated troponin value experienced no significant difference in CV death and a 6% increase in 90-day ED revisit or HF hospitalization (33% vs 39%, P = .28) compared with those with a troponin value within the reference range. In the treatment arm, there was a 12% difference in CV death and HF events between those who received in-person vs telehealth home visits (32% vs 20%; P = .23).

Median change in the KCCQ-12 SS in the intervention vs usual care arms was 9.5 points (median, −7.3; IQR, 5.7-16.5) vs 5.7 points (median, −1.6; IQR, 9.5-22.9) at day 30 (P = .048) and 10.9 (median, −2.6; IQR, 9.4-25.4) vs 9.4 points (median, −2.6; IQR, 10.9-25.8) (P = .75) at day 90 (Figure 3A and B). Changes in the KCCQ-12 SS were not linear and increased within 30 days and plateaued thereafter (eFigure in Supplement 2). After adjustment for baseline KCCQ-12 SS, 30-day changes were 5.5 points higher in the intervention group (95% CI, 1.3-9.7; P = .01), but no significant difference was observed at day 90 (2.7 points; 95% CI, −1.9 to 7.2; P = .25).

Within the combined vulnerable population (368/479 [77%] minority race/ethnicity, low socioeconomic status, and low brief health literacy), there were no significant differences associated with the intervention arm (HR, 0.94; 95% CI, 0.74-1.19; P = .61) for the primary outcome. Our adjusted analysis at 30 days showed results similar to our overall findings for the global rank outcome (HR, 0.83; 95% CI, 0.65-1.06; P = .13) and changes in KCCQ-12 SS (5.21 points; P = .02).

A per-protocol analysis among patients in the intervention arm who completed a home visit, had an outpatient visit scheduled, and received at least 1 coaching call showed no risk reduction at day 90 in CV death and HF events (36% vs 34%, P = .57). Our adjusted analysis also showed no reduction in relative risk for our global rank primary outcome in the intervention arm (HR, 0.93; 95% CI, 0.73-1.18; P = .55).

Discussion

To our knowledge, this was the first randomized clinical trial in patients with AHF discharged after ED-based management. We collected 30- and 90-day outcomes to test an HF self-care intervention. Our primary 90-day global rank outcome was not significantly different between the 2 arms, nor was the 90-day rate of CV death and HF events. There was a 20% reduction in global rank outcome at 30 days and a clinically important improvement in KCCQ-12 SS at day 30 that dissipated by day 90.

Our study was smaller than prior HF trials with less power to achieve statistical significance. This difference may explain why differences in outcomes at 90 days did not reach statistical significance. Alternatively, 30-day outcomes for both our global rank outcome and KCCQ-12 SS improved, which may indicate that ED-based interventions are more likely to impact outcomes closest to the ED encounter and their impact wanes with time.30-33 The Kaplan-Meier curves diverged early but did not continue to separate further over time. These findings suggest that either the current self-care strategy may benefit from additional home visits after the 30-day follow-up period to potentially prevent the apparent diminished effect of our intervention over time or the HF clinician visit in the first 7 days was an important component of our intervention. Consistent with prior predictors of adverse events, enrollment systolic blood pressure level and baseline KCCQ-12 SS were also associated with 30- and 90-day events.3,34,35

To our knowledge, this is the first study to report an extensive evaluation of the effect of a randomized intervention on the trajectory of health status at both 30 and 90 days for patients with AHF who are not hospitalized. Data on KCCQ as an indicator of health status in patients with AHF seen in the ED have been published, but most patients were admitted to the hospital,36 making our present findings unique. Our 30-day changes in the KCCQ-12 SS were over 5 points higher in the intervention arm, suggesting statistically and clinically important differences,37,38 and are similar to those seen in HF trials and registries.27,39-41 Changes in the KCCQ-12 SS were not linear, and it appears that most of the benefit from our intervention occurred in the first 30 days.

We enrolled a large proportion of vulnerable patients who often use the ED as their main source of health care. We projected that 75% of patients enrolled would be classified as vulnerable and 77% (n = 368) fulfilled this criterion. Vulnerable patients in the intervention arm experienced similar early benefit consistent with the overall population effect.

The low 90-day CV death and HF-related events in both arms suggest that care for patients with AHF can be safely transitioned from the ED to an outpatient setting. Overall 90-day CV event rates were much lower than previously reported.23-25,42 The enrollment criteria allowed a broad population to be included and provides guidance for identifying a patient cohort that potentially could be safely managed in the outpatient setting. Moreover, patients with increased cardiac troponin values were eligible to be enrolled provided the increase was not due to an acute coronary syndrome. Chronically elevated troponin values are often encountered in patients with AHF seen in the ED setting, and studies suggest that this presentation factors into the clinician’s decision to admit the patient.43,44 However, those studies were limited by being conducted in hospitalized patients rather than those who were discharged, and the studies also lacked intermediate-term follow-up. Taken in total, the lower than previously reported 90-day event rates can encourage safe transitions from the ED to the outpatient setting in a greater proportion of patients with AHF seen in the ED.

We developed and tested a tailored intervention delivered by a broad range of health care professionals during the in-person and virtual home visits. A key component of our self-care coaching strategy was tailoring the intervention to the evolving needs of the patient. Helping patients navigate through both HF- and non–HF-related medical challenges allows them to focus on their self-care. Furthermore, we found that virtual visits facilitate access to patients regardless of how far they live from their health care professional and avoid exposure to other ill patients. The ability to provide virtual visits in patients discharged from the ED has become increasingly important in the severe acute respiratory syndrome coronavirus pandemic. While all study teams followed our structured outline and goals for home visits and coaching, the role of the self-care coach was filled by nurses, study coordinators, and paramedics. Having many options to fulfill this role will likely facilitate implementation and dissemination into a variety of health care settings, using personnel already part of existing ED teams.

Limitations

There are several limitations of this study. First, we had projected CV death, hospital admission, and ED revisit event rates of 62% in the usual care arm,23-25,42 but noted only 36%, limiting our power to detect differences. Participant withdrawal in the intervention arm was greater than in the usual care arm. This difference suggests that certain patients may be more amenable to self-care coaching and our results may be most applicable to this group. Furthermore, our overall accrual rate was slower than expected, resulting in an extension of study duration and, after a discussion with the funding agency, resulted in a sample size adjustment and a change in our primary outcome. We were unable to reach our targeted accrual of 700 patients owing to less than anticipated enrollment at some sites. This lower-than-expected ED discharge rate suggests that our intervention may be of greatest utility at ED sites where a high proportion of patients are discharged home after ED-based management. In addition, the consent rate of 56% suggests that patients may still be hesitant to allow virtual or in-person home visits. The receptivity to telehealth may change as a result of the severe acute respiratory syndrome coronavirus pandemic.

Conclusions

This study implemented a strategy of self-care in patients with AHF discharged after ED-based management. Our intervention strategy was delivered by a variety of health care professionals, suggesting that this strategy could be integrated in ED settings where a large proportion of patients are discharged without the need for hiring personnel specific for this transition program. The intervention did not result in an improvement in our primary global rank outcome at 90 days. We found improvements in KCCQ-12 SS health status and the global rank outcome at 30 days that were not sustained at 90 days.

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Article Information

Accepted for Publication: September 2, 2020.

Published Online: November 18, 2020. doi:10.1001/jamacardio.2020.5763

Correction: This article was corrected on November 24, 2021, to fix an error of an omitted affiliation in the byline.

Corresponding Author: Sean P. Collins, MD, MSc, Department of Emergency Medicine, Vanderbilt University Medical Center, 1313 21st Ave S, Nashville, TN 37232 (sean.collins@vumc.org).

Author Contributions: Drs Collins and Liu had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Collins, Liu, Storrow, Levy, Fermann, Hiestand, Khan, Lindenfeld, Miller, Robichaux, Self, Singer, Walsh, Butler.

Acquisition, analysis, or interpretation of data: Collins, Liu, Jenkins, Storrow, Levy, Pang, Chang, Char, Diercks, Fermann, Han, Hiestand, Hogan, Kampe, Lee, Lindenfeld, Martindale, McNaughton, Miller, Miller-Reilly, Moser, Peacock, Rothman, Schrock, Singer, Sterling, Ward, Butler.

Drafting of the manuscript: Collins, Liu, Storrow, Pang, Chang, Diercks, Fermann, Khan, Lee, McNaughton, Miller, Moser, Schrock, Butler.

Critical revision of the manuscript for important intellectual content: Collins, Liu, Jenkins, Storrow, Levy, Pang, Chang, Char, Diercks, Fermann, Han, Hiestand, Hogan, Kampe, Khan, Lee, Lindenfeld, Martindale, McNaughton, Miller-Reilly, Peacock, Robichaux, Rothman, Schrock, Self, Singer, Sterling, Ward, Walsh, Butler.

Statistical analysis: Liu, Jenkins, Char, Han, Martindale.

Obtained funding: Collins, Storrow, Levy, Fermann, Han, Butler.

Administrative, technical, or material support: Collins, Storrow, Levy, Pang, Chang, Char, Fermann, Hogan, Kampe, Khan, Lindenfeld, McNaughton, Peacock, Rothman, Schrock, Self, Singer, Sterling.

Supervision: Collins, Chang, Diercks, Lindenfeld, Peacock, Robichaux, Schrock, Walsh, Butler.

Conflict of Interest Disclosures: Dr Collins reported receiving grants from the National Institutes of Health (NIH), Agency for Healthcare Research and Quality (AHRQ), American Heart Association (AHA), Ortho Clinical Diagnostics, Bristol Myers Squibb, Novartis, and AstraZeneca, and personal fees from Ortho Clinical Diagnostics, Boehringer Ingelheim, Roche, Bristol Myers Squibb, and Vixiar outside the submitted work. Dr Jenkins reported receiving grants from Patient-Centered Outcomes Research Institute (PCORI) during the conduct of the study. Dr Storrow reported other support from PCORI during the conduct of the study. Dr Levy reported receiving grants from PCORI during the conduct of the study, and other support from the American College of Cardiology, grants from Amgen, personal fees from Astra Zeneca, personal fees from Baim Institute, grants and personal fees from Bristol Myers Squibb, personal fees from Cardionomics, grants from Edwards Lifesciences, other support from Emergencies in Medicine, grants and personal fees from Novartis Pharmaceuticals, personal fees from Ortho Diagnostics, personal fees from Quidel Cardiovascular, grants and personal fees from Roche Diagnostics, and personal fees from Siemens outside the submitted work. Dr Pang reported receiving grants from PCORI during the conduct of the study; personal fees and nonfinancial support from Merck, Roche, and Baxter; grants from the AHA; other grants from the American College of Cardiology; grants, personal fees, and nonfinancial support from Novartis and Bristol Myers Squibb; grants from AHRQ, and grants from the NIH National Heart, Lung, and Blood Institute outside the submitted work. Dr Chang reported receiving grants from PCORI during the conduct of the study; grants from Ortho Clinical Diagnostics, grants from Beckman Coulter, personal fees from Roche, and grants from Siemens outside the submitted work. Dr Char reported receiving grants from PCORI during the conduct of the study. Dr Fermann reported receiving grants and personal fees from Janssen, personal fees from Milestone Pharmaceuticals, and grants and personal fees from Portola outside the submitted work. Dr Han reported receiving grants from the Geriatric Research, Education, and Clinical Center during the conduct of the study. Dr Hiestand reported receiving personal fees from PCORI during the conduct of the study and other fees from Siemens outside the submitted work. Dr Hogan reported receiving grants from Vanderbilt University during the conduct of the study. Dr Lee reported receiving grants from the Network for Investigation of Delirium: Unifying Scientist outside the submitted work. Dr Lindenfeld reported receiving grants from AstraZeneca and Sensible Medical and personal fees from Abbott, AstraZeneca, Boehringer Ingelheim, Edwards Lifesciences, CVRx, Volumetrix, VWave, and Boston Scientific outside the submitted work. Dr Rothman reported receiving grants from PCORI during the conduct of the study and personal fees from Abbott and EdLogics outside the submitted work. Dr Sterling reported receiving grants and other support from the National Institute of General Medical Sciences outside the submitted work. Dr Butler reported receiving other fees from Abbott, Amgen, Applied Therapeutics, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol Myers Squib, CVRx, Janssen, LivaNova, Luitpold, Medtronic, Merck, Novartis, NovoNordisk, Relypsa, and Vifor outside the submitted work. No other disclosures were reported.

Funding/Support: This study was supported by grant AD-1409-21656 from the PCORI.

Role of the Funder/Sponsor: The PCORI had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Data Sharing Statement: See Supplement 3.

Additional Contributions: We thank the study team members at the following sites: Vanderbilt University Medical Center and the Nashville VA, Metro Health, University of Mississippi Medical Center, Indiana University, Wayne State University, University of Iowa, Washington University, State University of New York-Stony Brook, Virginia Commonwealth University, University of Texas Southwestern, University of Cincinnati, Baylor Medical Center, Emory University, and Thomas Jefferson University. We also thank the American Heart Association and their Citizen Scientist Taskforce for their substantial contributions.

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