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Background: Despite advances in medical therapy for heart failure with reduced ejection fraction (HFrEF), major gaps in medication adherence to guideline-directed medical therapies (GDMT) remain. Greater continuity of care may impact medication adherence and reduced hospitalizations., Methods: We conducted a cross-sectional study of adults with a diagnosis of HF and EF ≤40% with ≥2 outpatient encounters between January 1, 2017 and January 10, 2021, prescribed ≥1 of the following GDMT: 1) Beta Blocker, 2) Angiotensin Converting Enzyme Inhibitor/Angiotensin Receptor Blocker/Angiotensin Receptor Neprilysin Inhibitor, 3) Mineralocorticoid Receptor Antagonist, 4) Sodium Glucose Cotransporter-2 Inhibitor. Continuity of care was calculated using the Bice-Boxerman Continuity of Care Index (COC) and the Usual Provider of Care (UPC) index, categorized by quantile. The primary outcome was adherence to GDMT, defined as average proportion of days covered ≥80% over 1 year. Secondary outcomes included all-cause and HF hospitalization at 1-year. We performed multivariable logistic regression analyses adjusted for demographics, insurance status, comorbidity index, number of visits and neighborhood SES index., Results: Overall, 3,971 individuals were included (mean age 72 years (SD 14), 71% male, 66% White race). In adjusted analyses, compared to individuals in the highest COC quartile, individuals in the third COC quartile had higher odds of GDMT adherence (OR 1.26, 95% CI 1.03-1.53, P = .024). UPC tertile was not associated with adherence (all P > .05). Compared to the highest quantiles, the lowest UPC and COC quantiles had higher odds of all-cause (UPC: OR 1.53, 95%CI 1.23-1.91; COC: OR 2.54, 95%CI 1.94-3.34) and HF (UPC: OR 1.81, 95%CI 1.23-2.67; COC: OR 1.77, 95%CI 1.09-2.95) hospitalizations., Conclusions: Continuity of care was not associated with GDMT adherence among patients with HFrEF but lower continuity of care was associated with increased all-cause and HF-hospitalizations., (Published by Elsevier Inc.)

Background: Electronic health record (EHR) tools can improve prescribing of guideline-recommended therapies for heart failure with reduced ejection fraction (HFrEF), but their effectiveness may vary by physician workload., Objectives: This paper aims to assess whether physician workload modifies the effectiveness of EHR tools for HFrEF., Methods: This was a prespecified subgroup analysis of the BETTER CARE-HF (Building Electronic Tools to Enhance and Reinforce Cardiovascular Recommendations for Heart Failure) cluster-randomized trial, which compared effectiveness of an alert vs message vs usual care on prescribing of mineralocorticoid antagonists (MRAs). The trial included adults with HFrEF seen in cardiology offices who were eligible for and not prescribed MRAs. Visit volume was defined at the cardiologist-level as number of visits per 6-month study period (high = upper tertile vs non-high = remaining). Analysis at the patient-level used likelihood ratio test for interaction with log-binomial models., Results: Among 2,211 patients seen by 174 cardiologists, 932 (42.2%) were seen by high-volume cardiologists (median: 1,853; Q1-Q3: 1,637-2,225 visits/6 mo; and median: 10; Q1-Q3: 9-12 visits/half-day). MRA was prescribed to 5.5% in the high-volume vs 14.8% in the non-high-volume groups in the usual care arm, 10.3% vs 19.6% in the message arm, and 31.2% vs 28.2% in the alert arm, respectively. Visit volume modified treatment effect (P for interaction = 0.02) such that the alert was more effective in the high-volume group (relative risk: 5.16; 95% CI: 2.57-10.4) than the non-high-volume group (relative risk: 1.93; 95% CI: 1.29-2.90)., Conclusions: An EHR-embedded alert increased prescribing by >5-fold among patients seen by high-volume cardiologists. Our findings support use of EHR alerts, especially in busy practice settings. (Building Electronic Tools to Enhance and Reinforce Cardiovascular Recommendations for Heart Failure [BETTER CARE-HF]; NCT05275920)., Competing Interests: Funding Support and Author Disclosures This study was funded by the National Center for Advancing Translational Sciences (NIH/NCATS UL1TR001445). Dr Mukhopadhyay is supported by an American Heart Association Career Development Award (23CDA1042602), outside the scope of the present work. Dr Reynolds has received in-kind donations for unrelated research from Abbott Vascular, Philips, SHL Telemedicine, and Siemens. Dr Phillips has received consulting fees from Novo Nordisk. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2024. Published by Elsevier Inc.)

Importance: Medication nonadherence is common among patients with heart failure with reduced ejection fraction (HFrEF) and can lead to increased hospitalization and mortality. Patients living in socioeconomically disadvantaged areas may be at greater risk for medication nonadherence due to barriers such as lower access to transportation or pharmacies., Objective: To examine the association between neighborhood-level socioeconomic status (nSES) and medication nonadherence among patients with HFrEF and to assess the mediating roles of access to transportation, walkability, and pharmacy density., Design, Setting, and Participants: This retrospective cohort study was conducted between June 30, 2020, and December 31, 2021, at a large health system based primarily in New York City and surrounding areas. Adult patients with a diagnosis of HF, reduced EF on echocardiogram, and a prescription of at least 1 guideline-directed medical therapy (GDMT) for HFrEF were included., Exposure: Patient addresses were geocoded, and nSES was calculated using the Agency for Healthcare Research and Quality SES index, which combines census-tract level measures of poverty, rent burden, unemployment, crowding, home value, and education, with higher values indicating higher nSES., Main Outcomes and Measures: Medication nonadherence was obtained through linkage of health record prescription data with pharmacy fill data and was defined as proportion of days covered (PDC) of less than 80% over 6 months, averaged across GDMT medications., Results: Among 6247 patients, the mean (SD) age was 73 (14) years, and majority were male (4340 [69.5%]). There were 1011 (16.2%) Black participants, 735 (11.8%) Hispanic/Latinx participants, and 3929 (62.9%) White participants. Patients in lower nSES areas had higher rates of nonadherence, ranging from 51.7% in the lowest quartile (731 of 1086 participants) to 40.0% in the highest quartile (563 of 1086 participants) (P < .001). In adjusted analysis, patients living in the lower 2 nSES quartiles had significantly higher odds of nonadherence when compared with patients living in the highest nSES quartile (quartile 1: odds ratio [OR], 1.57 [95% CI, 1.35-1.83]; quartile 2: OR, 1.35 [95% CI, 1.16-1.56]). No mediation by access to transportation and pharmacy density was found, but a small amount of mediation by neighborhood walkability was observed., Conclusions and Relevance: In this retrospective cohort study of patients with HFrEF, living in a lower nSES area was associated with higher rates of GDMT nonadherence. These findings highlight the importance of considering neighborhood-level disparities when developing approaches to improve medication adherence.

Purpose: Clinic-based or community-based interventions can improve adherence to guideline-directed medication therapies (GDMTs) among patients with heart failure (HF). However, opportunities for such interventions are frequently missed, as providers may be unable to recognise risk patterns for medication non-adherence. Machine learning algorithms can help in identifying patients with high likelihood of non-adherence. While a number of multilevel factors influence adherence, prior models predicting non-adherence have been limited by data availability. We have established an electronic health record (EHR)-based cohort with comprehensive data elements from multiple sources to improve on existing models. We linked EHR data with pharmacy refill data for real-time incorporation of prescription fills and with social determinants data to incorporate neighbourhood factors., Participants: Patients seen at a large health system in New York City (NYC), who were >18 years old with diagnosis of HF or reduced ejection fraction (<40%) since 2017, had at least one clinical encounter between 1 April 2021 and 31 October 2022 and active prescriptions for any of the four GDMTs (beta-blocker, ACEi/angiotensin receptor blocker (ARB)/angiotensin receptor neprilysin inhibitor (ARNI), mineralocorticoid receptor antagonist (MRA) and sodium-glucose cotransporter 2 inhibitor (SGLT2i)) during the study period. Patients with non-geocodable address or outside the continental USA were excluded., Findings to Date: Among 39 963 patients in the cohort, the average age was 73±14 years old, 44% were female and 48% were current/former smokers. The common comorbid conditions were hypertension (77%), cardiac arrhythmias (56%), obesity (33%) and valvular disease (33%). During the study period, 33 606 (84%) patients had an active prescription of beta blocker, 32 626 (82%) had ACEi/ARB/ARNI, 11 611 (29%) MRA and 7472 (19%) SGLT2i. Ninety-nine per cent were from urban metropolitan areas., Future Plans: We will use the established cohort to develop a machine learning model to predict medication adherence, and to support ancillary studies assessing associates of adherence. For external validation, we will include data from an additional hospital system in NYC., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Mineralocorticoid receptor antagonists (MRAs) are underprescribed for patients with heart failure with reduced ejection fraction (HFrEF)., Objectives: This study sought to compare effectiveness of 2 automated, electronic health record-embedded tools vs usual care on MRA prescribing in eligible patients with HFrEF., Methods: BETTER CARE-HF (Building Electronic Tools to Enhance and Reinforce Cardiovascular Recommendations for Heart Failure) was a 3-arm, pragmatic, cluster-randomized trial comparing the effectiveness of an alert during individual patient encounters vs a message about multiple patients between encounters vs usual care on MRA prescribing. This study included adult patients with HFrEF, no active MRA prescription, no contraindication to MRAs, and an outpatient cardiologist in a large health system. Patients were cluster-randomized by cardiologist (60 per arm)., Results: The study included 2,211 patients (alert: 755, message: 812, usual care [control]: 644), with average age 72.2 years, average ejection fraction 33%, who were predominantly male (71.4%) and White (68.9%). New MRA prescribing occurred in 29.6% of patients in the alert arm, 15.6% in the message arm, and 11.7% in the control arm. The alert more than doubled MRA prescribing compared to usual care (relative risk: 2.53; 95% CI: 1.77-3.62; P < 0.0001) and improved MRA prescribing compared to the message (relative risk: 1.67; 95% CI: 1.21-2.29; P = 0.002). The number of patients with alert needed to result in an additional MRA prescription was 5.6., Conclusions: An automated, patient-specific, electronic health record-embedded alert increased MRA prescribing compared to both a message and usual care. These findings highlight the potential for electronic health record-embedded tools to substantially increase prescription of life-saving therapies for HFrEF. (Building Electronic Tools to Enhance and Reinforce Cardiovascular Recommendations-Heart Failure [BETTER CARE-HF]; NCT05275920)., Competing Interests: Funding Support and Author Disclosures The project described was supported by the National Center for Advancing Translational Sciences (NCATS), National Institutes of Health, through Grant Award Number UL1TR001445. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. The learning health system program was funded by Allen Thorpe. In-kind contributions were provided by New York University Langone Health. Dr Mukhopadhyay is supported by the National Heart, Lung, and Blood Institute (NIH/NHLBI 2T32HL098129-11). Dr Reynolds has received in-kind donations for unrelated research from Abbott Vascular, Philips, and Siemens. Dr Phillips has served as a consultant for Novo Nordisk. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2023 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Background: Beart failure with reduced ejection fraction (HFrEF) is a leading cause of morbidity and mortality. However, shortfalls in prescribing of proven therapies, particularly mineralocorticoid receptor antagonist (MRA) therapy, account for several thousand preventable deaths per year nationwide. Electronic clinical decision support (CDS) is a potential low-cost and scalable solution to improve prescribing of therapies. However, the optimal timing and format of CDS tools is unknown., Methods and Results: We developed two targeted CDS tools to inform cardiologists of gaps in MRA therapy for patients with HFrEF and without contraindication to MRA therapy: (1) an alert that notifies cardiologists at the time of patient visit, and (2) an automated electronic message that allows for review between visits. We designed these tools using an established CDS framework and findings from semistructured interviews with cardiologists. We then pilot tested both CDS tools (n = 596 patients) and further enhanced them based on additional semistructured interviews (n = 11 cardiologists). The message was modified to reduce the number of patients listed, include future visits, and list date of next visit. The alert was modified to improve noticeability, reduce extraneous information on guidelines, and include key information on contraindications., Conclusions: The BETTER CARE-HF (Building Electronic Tools to Enhance and Reinforce CArdiovascular REcommendations for Heart Failure) trial aims to compare the effectiveness of the alert vs. the automated message vs. usual care on the primary outcome of MRA prescribing. To our knowledge, no study has directly compared the efficacy of these two different types of electronic CDS interventions. If effective, our findings can be rapidly disseminated to improve morbidity and mortality for patients with HFrEF, and can also inform the development of future CDS interventions for other disease states. (Trial registration: Clinicaltrials.gov NCT05275920)., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Background Angiotensin receptor neprilysin inhibitors (ARNI) reduce mortality and hospitalization for patients with heart failure. However, relatively high copayments for ARNI may contribute to suboptimal adherence, thus potentially limiting their benefits. Methods and Results We conducted a retrospective cohort study within a large, multi-site health system. We included patients with: ARNI prescription between November 20, 2020 and June 30, 2021; diagnosis of heart failure or left ventricular ejection fraction ≤40%; and available pharmacy or pharmacy benefit manager copayment data. The primary exposure was copayment, categorized as $0, $0.01 to $10, $10.01 to $100, and >$100. The primary outcome was prescription fill nonadherence, defined as the proportion of days covered <80% over 6 months. We assessed the association between copayment and nonadherence using multivariable logistic regression, and nonbinarized proportion of days covered using multivariable Poisson regression, adjusting for demographic, clinical, and neighborhood-level covariates. A total of 921 patients met inclusion criteria, with 192 (20.8%) having $0 copayment, 228 (24.8%) with $0.01 to $10 copayment, 206 (22.4%) with $10.01 to $100, and 295 (32.0%) with >$100. Patients with higher copayments had higher rates of nonadherence, ranging from 17.2% for $0 copayment to 34.2% for copayment >$100 ( P <0.001). After multivariable adjustment, odds of nonadherence were significantly higher for copayment of $10.01 to $100 (odds ratio [OR], 1.93 [95% CI, 1.15-3.27], P =0.01) or >$100 (OR, 2.58 [95% CI, 1.63-4.18], P <0.001), as compared with $0 copayment. Similar associations were seen when assessing proportion of days covered as a proportion. Conclusions We found higher rates of not filling ARNI prescriptions among patients with higher copayments, which persisted after multivariable adjustment. Our findings support future studies to assess whether reducing copayments can increase adherence to ARNI and improve outcomes for heart failure.

Background: Guideline-directed medical therapy (GDMT) dramatically improves outcomes in heart failure with reduced ejection fraction (HFrEF). Our goal was to examine GDMT use in community patients with newly diagnosed HFrEF., Methods and Results: We performed a population-based, retrospective cohort study of all Olmsted County, Minnesota, residents with newly diagnosed HFrEF (EF ≤ 40%) 2007-2017. We excluded patients with contraindications to medication initiation. We examined the use of beta-blockers, HF beta-blockers (metoprolol succinate, carvedilol, bisoprolol), angiotensin converting enzyme inhibitors (ACEis), angiotensin receptor blockers (ARBs), angiotensin receptor neprilysin inhibitors (ARNIS), and mineralocorticoid receptor antagonists (MRAs) in the first year after HFrEF diagnosis. We used Cox models to evaluate the association of being seen in an HF clinic with the initiation of GDMT. From 2007 to 2017, 1160 patients were diagnosed with HFrEF (mean age 69.7 years, 65.6% men). Most eligible patients received beta-blockers (92.6%) and ACEis/ARBs/ARNIs (87.0%) in the first year. However, only 63.8% of patients were treated with an HF beta-blocker, and few received MRAs (17.6%). In models accounting for the role of an HF clinic in initiation of these medications, being seen in an HF clinic was independently associated with initiation of new GDMT across all medication classes, with a hazard ratio (95% CI) of 1.54 (1.15-2.06) for any beta-blocker, 2.49 (1.95-3.20) for HF beta-blockers, 1.97 (1.46-2.65) for ACEis/ARBs/ARNIs, and 2.14 (1.49-3.08) for MRAs., Conclusions: In this population-based study, most patients with newly diagnosed HFrEF received beta-blockers and ACEis/ARBs/ARNIs. GDMT use was higher in patients seen in an HF clinic, suggesting the potential benefit of referral to an HF clinic for patients with newly diagnosed HFrEF., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Background: National registries reveal significant gaps in medical therapy for patients with heart failure and reduced ejection fraction (HFrEF), but may not accurately (or fully) characterize the population eligible for therapy., Objective: We developed an automated, electronic health record-based algorithm to identify HFrEF patients eligible for evidence-based therapy, and extracted treatment data to assess gaps in therapy in a large, diverse health system., Methods: In this cross-sectional study of all NYU Langone Health outpatients with EF ≤ 40% on echocardiogram and an outpatient visit from 3/1/2019 to 2/29/2020, we assessed prescription of the following therapies: beta-blocker (BB), angiotensin converting enzyme inhibitor (ACE-I)/angiotensin receptor blocker (ARB)/angiotensin receptor neprilysin inhibitor (ARNI), and mineralocorticoid receptor antagonist (MRA). Our algorithm accounted for contraindications such as medication allergy, bradycardia, hypotension, renal dysfunction, and hyperkalemia., Results: We electronically identified 2732 patients meeting inclusion criteria. Among those eligible for each medication class, 84.8% and 79.7% were appropriately prescribed BB and ACE-I/ARB/ARNI, respectively, while only 23.9% and 22.7% were appropriately prescribed MRA and ARNI, respectively. In adjusted models, younger age, cardiology visit and lower EF were associated with increased prescribing of medications. Private insurance and Medicaid were associated with increased prescribing of ARNI (OR = 1.40, 95% CI = 1.02-2.00; and OR = 1.70, 95% CI = 1.07-2.67)., Conclusions: We observed substantial shortfalls in prescribing of MRA and ARNI therapy to ambulatory HFrEF patients. Subspecialty care setting, and Medicaid insurance were associated with higher rates of ARNI prescribing. Further studies are warranted to prospectively evaluate provider- and policy-level interventions to improve prescribing of these evidence-based therapies., (© 2022. The Author(s).)

Background: Some patients with heart failure (HF) will go on to develop advanced HF, characterized by severe HF symptoms despite attempts to optimize medical therapy. The goals of this study were to examine the risk of developing advanced HF in patients with newly diagnosed HF, identify risk factors for developing advanced HF, and evaluate the impact of advanced HF on outcomes., Methods: This was a population-based, retrospective cohort study of Olmsted County, Minnesota, residents with a new clinical diagnosis of HF between 2007 and 2017. Risk factors for the development of advanced HF (2018 European Society of Cardiology criteria) were examined using cause-specific Cox proportional hazard regression models. The associations of development of advanced HF with risks of hospitalization and mortality were examined using the Andersen-Gill and Cox models, respectively., Results: There were 4597 residents with incident HF from 2007 to 2017. The cumulative incidence of advanced HF was 11.5% (95% CI, 10.5%-12.5%) at 6 years after incident HF diagnosis overall and was 14.4% (95% CI, 12.3%-16.9%), 11.4% (95% CI, 8.9%-14.6%), and 11.7% (95% CI, 10.3%-13.2%) in patients with incident HF with reduced, mildly reduced, and preserved ejection fraction, respectively. Key demographics, comorbidities, and echocardiographic characteristics were independently associated with the development of advanced HF. Development of advanced HF was associated with increased risks of all-cause hospitalization (adjusted hazard ratio, 3.0 [95% CI, 2.7-3.4]; P <0.001), HF hospitalization (hazard ratio, 10.2 [95% CI, 8.7-12.1]), all-cause mortality (hazard ratio, 5.0 [95% CI, 4.5-5.6]; P <0.001), and cardiovascular mortality (hazard ratio, 7.8 [95% CI, 6.7-9.1])., Conclusions: In this population-based study, development of advanced HF was common and was associated with markedly increased morbidity and mortality.

Objectives: The goal of this study was to evaluate the prevalence, characteristics, and outcomes of patients with advanced heart failure (HF) in a geographically defined population., Background: Some patients with HF progress to advanced HF, characterized by debilitating HF symptoms refractory to therapy. Limited data are available on the epidemiology and outcomes of patients with advanced HF., Methods: This was a population-based cohort study of all Olmsted County, Minnesota, adults with and without HF from 2007 to 2017. The 2018 European Society of Cardiology advanced HF diagnostic criteria were operationalized and applied to all patients with HF. Hospitalization and mortality in advanced HF, overall and according to ejection fraction (EF) type (reduced EF <40% [HFrEF], mid-range EF 40%-49% [HFmrEF], and preserved EF ≥50% [HFpEF]) were examined using Andersen-Gill and Cox models., Results: Of 6,836 adults with HF, 936 (13.7%) met criteria for advanced HF. The prevalence of advanced HF increased with age and was higher in men. At advanced HF diagnosis, 396 (42.3%) patients had HFrEF, 134 (14.3%) had HFmrEF, and 406 (43.4%) had HFpEF. The median (interquartile range) time from advanced HF diagnosis to death was 12.2 months (3.7-29.9 months). The mean rate of hospitalization was 2.91 (95% CI: 2.78-3.06) per person-year in the first year after advanced HF diagnosis. There were no differences in risks of all-cause mortality or hospitalization by EF. Patients with advanced HFpEF were at lower risk for cardiovascular mortality compared with advanced HFrEF (HR: 0.79; 95% CI: 0.65-0.97)., Conclusions: In this population-based study, more than one-half of patients with advanced HF had mid-range or preserved EF, and survival was poor regardless of EF., Competing Interests: Funding Support and Author Disclosures This study was funded by the National Institutes of Health (R01 HL144529; Principal Investigator: Dr Dunlay) and made possible by using the resources of the Rochester Epidemiology Project, which is supported by the National Institute on Aging of the National Institutes of Health (R01 AG034676). The authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2021 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Large registries, administrative data, and the electronic health record (EHR) offer opportunities to identify patients with heart failure, which can be used for research purposes, process improvement, and optimal care delivery. Identification of cases is challenging because of the heterogeneous nature of the disease, which encompasses various phenotypes that may respond differently to treatment. The increasing availability of both structured and unstructured data in the EHR has expanded opportunities for cohort construction. This article reviews the current literature on approaches to identification of heart failure, and looks toward the future of machine learning, big data, and phenomapping., Competing Interests: Disclosure The authors have nothing to disclose., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Background: Evidence-based therapy for heart failure remains underutilized at hospital discharge, particularly for patients with heart failure who are hospitalized for another cause. We developed clinical decision support (CDS) to recommend an angiotensin converting enzyme (ACE) inhibitor during hospitalization to promote its continuation at discharge. The CDS was designed to be implemented in both interruptive and non-interruptive versions., Objectives: To compare the effectiveness and implementation of interruptive and non-interruptive versions of a CDS to improve care for heart failure., Methods: Hospitalizations of patients with reduced ejection fraction were pseudo-randomized to deliver interruptive or non-interruptive CDS alerts to providers based on even or odd medical record number. We compared discharge utilization of an ACE inhibitor or angiotensin receptor blocker (ARB) for these two implementation approaches. We also assessed adoption and implementation fidelity of the CDS., Results: Of 958 hospitalizations, interruptive alert hospitalizations had higher rates of discharge utilization of ACE inhibitors or ARBs than non-interruptive alert hospitalizations (79.6% vs. 74.2%, p = 0.05). Utilization was higher for interruptive alert versus non-interruptive alert hospitalizations which were principally for causes other than heart failure (79.8% vs. 73.4%; p = 0.05) but no difference was observed among hospitalizations with a principal heart failure diagnosis (85.9% vs.81.7%; p = 0.49). As compared to non-interruptive hospitalizations, interruptive alert hospitalizations were more likely to have had: an alert with any response (40.6% vs. 13.1%, p < 0.001), contraindications reported (33.1% vs 11.3%, p < 0.001), and an ACE inhibitor ordered within twelve hours of the alert (17.6% vs 10.3%, p < 0.01). The response rate for the interruptive alert was 1.7%, and a median (25 th , 75 th percentile) of 14 (5,32) alerts were triggered per hospitalization., Conclusions: A CDS implemented as an interruptive alert was associated with improved quality of care for heart failure. Whether the potential benefits of CDS in improving cardiovascular care were worth the high burden of interruptive alerts deserves further consideration. CLINICALTRIALS., Gov Identifier: NCT02858674., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Background: Mineralocorticoid receptor antagonists (MRA) are an underutilized therapy for heart failure with a reduced ejection fraction (HFrEF), but the current impact of hospitalization on MRA use is not well characterized. The objective of this study was to describe contemporary MRA prescription for heart failure patients before and after the full scope of hospitalizations and the association between MRA discharge prescription and post-hospitalization outcomes., Methods: We conducted a retrospective cohort study at an academic hospital system in 2013-2016. Among 1500 included hospitalizations of 1009 unique patients with HFrEF and without MRA contraindication, the mean age was 71.9 ± 13.6 years and 443 (29.5%) were female. We compared MRA prescription before and after hospitalizations with McNemar's test and between patients with principal and secondary diagnoses of HFrEF with the chi-square test, and association of MRA discharge prescription with 30-day and 180-day mortality and readmissions using generalized estimating equations., Results: MRA prescriptions increased from 303 (20.2%) to 375 (25.0%) at discharge (+4.8%, p < 0.0001). More patients with principal diagnosis of HFrEF compared to those hospitalized for other reasons received MRA (34.9% versus 21.3%, p < 0.0001) and had them initiated (21.8% versus 9.7%, p < 0.0001). MRA prescription at discharge was not associated with mortality or readmission at 30 and 180 days, and there was no interaction with principal/secondary diagnosis., Conclusions: Among hospitalized HFrEF patients, 75% did not receive MRA before or after hospitalization, and nearly 90% of eligible patients did not have MRA initiated. As we found no signal for short-term harm after discharge, hospitalization may represent an opportunity to initiate guideline-directed heart failure therapy.

Background: The Medicare Hospital Readmissions Reduction Program has led to fewer readmissions following hospitalizations with a principal diagnosis of heart failure (HF). Patients with HF are frequently hospitalized for other causes., Objectives: This study sought to compare trends in Medicare risk-adjusted, 30-day readmissions following principal HF hospitalizations and other hospitalizations with HF., Methods: This was a retrospective study of 12,973,853 Medicare hospitalizations with a principal or secondary diagnosis of HF between January 2008 and June 2015. Hospitalizations were categorized as follows: principal HF hospitalizations; principal acute myocardial infarction or pneumonia hospitalizations with secondary HF; and other hospitalizations with secondary HF. The study examined trends in risk-adjusted, 30-day, all-cause readmission rates for each cohort and trends in differences in readmission rates among cohorts by using linear spline regression models., Results: Before passage of the Affordable Care Act in March 2010, risk-adjusted, 30-day readmission rates were stable for all 3 cohorts, with mean monthly rates of 26.1%, 24.9%, and 24.4%, respectively. Risk-adjusted readmission rates started declining after passage of the Affordable Care Act by 1.09% (95% confidence interval [CI]: 0.51% to 1.68%), 1.24% (95% CI: 0.92% to 1.57%), and 1.05% (95% CI: 0.52% to 1.58%) per year, respectively, until implementation of the Hospital Readmissions Reduction Program in October 2012 and then stabilized for all 3 cohorts., Conclusions: Patients with HF are often hospitalized for other causes, and these hospitalizations have high readmission rates. Policy changes led to decreases in readmission rates for both principal and secondary HF hospitalizations. Readmission rates in both groups remain high, suggesting that initiatives targeting all hospitalized patients with HF continue to be warranted., (Copyright © 2019 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Background: Interventions to reduce readmissions after acute heart failure hospitalization require early identification of patients. The purpose of this study was to develop and test accuracies of various approaches to identify patients with acute decompensated heart failure (ADHF) with the use of data derived from the electronic health record., Methods and Results: We included 37,229 hospitalizations of adult patients at a single hospital during 2013-2015. We developed 4 algorithms to identify hospitalization with a principal discharge diagnosis of ADHF: 1) presence of 1 of 3 clinical characteristics, 2) logistic regression of 31 structured data elements, 3) machine learning with unstructured data, and 4) machine learning with the use of both structured and unstructured data. In data validation, algorithm 1 had a sensitivity of 0.98 and positive predictive value (PPV) of 0.14 for ADHF. Algorithm 2 had an area under the receiver operating characteristic curve (AUC) of 0.96, and both machine learning algorithms had AUCs of 0.99. Based on a brief survey of 3 providers who perform chart review for ADHF, we estimated that providers spent 8.6 minutes per chart review; using this this parameter, we estimated that providers would spend 61.4, 57.3, 28.7, and 25.3 minutes on secondary chart review for each case of ADHF if initial screening were done with algorithms 1, 2, 3, and 4, respectively., Conclusions: Machine learning algorithms with unstructured notes had the best performance for identification of ADHF and can improve provider efficiency for delivery of quality improvement interventions., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Objectives: This study sought to determine whether racial and ethnic differences exist among patients with similar access to care. We examined outcomes after heart failure hospitalization within a large municipal health system., Background: Racial and ethnic disparities in heart failure outcomes are present in administrative data, and one explanation is differential access to care., Methods: We performed a retrospective cohort study of 8,532 hospitalizations of adults with heart failure at 11 hospitals in New York City from 2007 to 2010. Primary exposure was ethnicity and race, and outcomes were 30- and 90-day readmission and 30-day and 1-year mortality rates. Generalized estimating equations were used to test for associations between ethnicity and race and outcomes with covariate adjustment., Results: Of the number of hospitalizations included, 4,305 (51%) were for blacks, 2,449 (29%) were for Hispanics, 1,494 (18%) were for whites, and 284 (3%) were for Asians. Compared to whites, blacks and Asians had lower 1-year mortality, with adjusted odds ratios (aORs) of 0.75 (95% confidence interval [CI]: 0.59 to 0.94) and 0.57 (95% CI: 0.38 to 0.85), respectively, and rates for Hispanics were not significantly different (aOR: 0.81; 95% CI: 0.64 to 1.03). Hispanics had higher odds of readmission than whites (aOR: 1.27; 95% CI: 1.03 to 1.57) at 30 (aOR: 1.40; 95% CI: 1.15 to 1.70) and 90 days. Blacks had higher odds of readmission than whites at 90 days (aOR:1.21; 95% CI: 1.01 to 1.47)., Conclusions: Racial and ethnic differences in outcomes after heart failure hospitalization were present within a large municipal health system. Access to a municipal health system may not be sufficient to eliminate disparities in heart failure outcomes., Competing Interests: None of the authors have relevant relationships with industry or conflicts of interest., (Copyright © 2016 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Background: Comorbid diabetes is common in heart failure and associated with increased hospitalization and mortality. Nonetheless, the association between glycemic control and outcomes among patients with heart failure and diabetes remains poorly characterized, particularly among low income and minority patients., Methods: We performed a retrospective cohort study of outpatients with heart failure and diabetes in the New York City Health and Hospitals Corporation, the largest municipal health care system in the United States. Cox proportional hazard models were used to measure the association between HbA1c levels and outcomes of all-cause hospitalization, heart failure hospitalization, and mortality., Results: Of 4723 patients with heart failure and diabetes, 42.6 % were black, 30.5 % were Hispanic/Latino, 31.4 % were Medicaid beneficiaries and 22.9 % were uninsured. As compared to patients with an HbA1c of 8.0-8.9 %, patients with an HbA1c of <6.5, 6.5-6.9, 7.0-7.9, and ≥9.0 % had an adjusted hazard ratio (aHR) (95 % CI) for all-cause hospitalization of 1.03 (0.90-1.17), 1.05 (0.91-1.22), 1.03 (0.90-1.17), and 1.13 (1.00-1.28), respectively. An HbA1c ≥ 9.0 % was also associated with an increased risk of heart failure hospitalization (aHR 1.33; 95 % CI 1.11-1.59) and a non-significant increased risk in mortality (aHR 1.20; 95 % CI 0.99-1.45) when compared to HbA1c of 8.0-8.9 %., Conclusions: Among a cohort of primarily minority and low income patients with heart failure and diabetes, an increased risk of hospitalization was observed only for an HbA1c greater than 9 %.

Background: Evidence regarding the association of anger proneness with incidence of heart failure is lacking., Methods and Results: Anger proneness was ascertained among 13,171 black and white participants of the Atherosclerosis Risk in Communities (ARIC) study cohort with the use of the Spielberger Trait Anger Scale. Incident heart failure events, defined as occurrence of ICD-9-CM code 428.x, were ascertained from participants' medical records during follow-up in the years 1990-2010. Relative hazard of heart failure across categories of trait anger was estimated with the use of Cox proportional hazard models. Study participants (mean age 56.9 [SD 5.7] years) experienced 1,985 incident HF events during 18.5 (SD 4.9) years of follow-up. Incidence of HF was greater among those with high, as compared to those with low or moderate trait anger, with higher incidence observed for men than for women. The relative hazard of incident HF was modestly high among those with high trait anger, compared with those with low or moderate trait anger (age-adjusted hazard ratio for men: 1.44 (95% confidence interval [CI] 1.23-1.69). Adjustment for comorbidities and depressive symptoms attenuated the estimated age-adjusted relative hazard in men to 1.26 (95% CI 1.00-1.60)., Conclusions: Assessment of anger proneness may be necessary in successful prevention and clinical management of heart failure, especially in men., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Background: Treatment of acute heart failure in the emergency department (ED) or observation unit is an alternative to hospitalization. Both ED management and observation unit management have been associated with reduced costs and may be used to avoid penalties related to rehospitalizations. The purpose of this study was to examine trends in ED visits for heart failure and disposition following such visits., Methods: We used the National Hospital Ambulatory Medical Care Survey, a representative sample of ED visits in the United States, to estimate rates and characteristics of ED visits for heart failure between 2002 and 2010. The primary outcome was the discharge disposition from the ED. Regression models were fit to estimate trends and predictors of hospitalization and admission to an observation unit., Results: The number of ED visits for heart failure remained stable over the period, from 914,739 in 2002 to 848,634 in 2010 (annual change -0.7%, 95% CI -3.7% to +2.5%). Of these visits, 74.2% led to hospitalization, wheras 3.1% led to observation unit admission. The likelihood of hospitalization did not change during the period (adjusted prevalence ratio 1.00, 95% CI 0.99-1.01 for each additional year), whereas admission to the observation unit increased annually (adjusted prevalence ratio 1.12, 95% CI 1.01-1.25). We observed significant regional differences in likelihood of hospitalization and observation admission., Conclusions: The number of ED visits for heart failure and the high proportion of ED visits with subsequent inpatient hospitalization have not changed in the last decade. Opportunities may exist to reduce hospitalizations by increasing short-term management of heart failure in the ED or observation unit., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Objectives: The study sought to assess the quality of care for heart failure patients who are hospitalized for all causes., Background: Performance measures for heart failure target patients with a principal diagnosis of heart failure. However, patients with heart failure are commonly hospitalized for other causes and may benefit from treatments such as angiotensin-converting enzyme (ACE) inhibitors for left ventricular (LV) systolic dysfunction., Methods: We assessed rates of compliance with care measures for patients hospitalized with acute or chronic heart failure in the ARIC (Atherosclerosis Risk In Communities) study surveillance catchment area from 2005 to 2009. Rates of compliance were compared between patients with a principal discharge diagnosis of heart failure and those with another principal discharge diagnosis., Results: Of 4,345 hospitalizations of heart failure patients, 39.6% carried a principal diagnosis of heart failure. Patients with a principal heart failure diagnosis had higher rates of LV function assessment (89.1% vs. 82.5%; adjusted prevalence ratio [aPR]: 1.07; 95% confidence interval [CI]: 1.04 to 1.10) and discharge ACE inhibitor/angiotensin receptor blocker (ARB) in LV dysfunction (64.1% vs. 56.3%; aPR: 1.11; 95% CI: 1.03 to 1.20) as compared to patients hospitalized for another cause. LV assessment and ACE inhibitor/ARB use were associated with reductions in 1-year post-discharge mortality (adjusted odds ratio: 0.66, 95% CI: 0.51 to 0.85; adjusted odds ratio: 0.72, 95% CI: 0.54 to 0.96, respectively) that did not differ for patients with versus without a principal heart failure diagnosis., Conclusions: Compared with individuals hospitalized with a principal diagnosis of heart failure, heart failure patients hospitalized for other causes were less likely to receive guideline recommended care. Quality initiatives may improve care by targeting hospitalizations with either principal or secondary heart failure diagnoses., (Copyright © 2014 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Objectives: This study sought to characterize temporal trends in hospitalizations with heart failure as a primary or secondary diagnosis., Background: Heart failure patients are frequently admitted for both heart failure and other causes., Methods: Using the Nationwide Inpatient Sample (NIS), we evaluated trends in heart failure hospitalizations between 2001 and 2009. Hospitalizations were categorized as either primary or secondary heart failure hospitalizations based on the location of heart failure in the discharge diagnosis. National estimates were calculated using the sampling weights of the NIS. Age- and sex-standardized hospitalization rates were determined by dividing the number of hospitalizations by the U.S. population in a given year and using direct standardization., Results: The number of primary heart failure hospitalizations in the United States decreased from 1,137,944 in 2001 to 1,086,685 in 2009, whereas secondary heart failure hospitalizations increased from 2,753,793 to 3,158,179 over the same period. Age- and sex-adjusted rates of primary heart failure hospitalizations decreased steadily from 2001 to 2009, from 566 to 468 per 100,000 people. Rates of secondary heart failure hospitalizations initially increased from 1,370 to 1,476 per 100,000 people from 2001 to 2006, then decreased to 1,359 per 100,000 people in 2009. Common primary diagnoses for secondary heart failure hospitalizations included pulmonary disease, renal failure, and infections., Conclusions: Although primary heart failure hospitalizations declined, rates of hospitalizations with a secondary diagnosis of heart failure were stable in the past decade. Strategies to reduce the high burden of hospitalizations of heart failure patients should include consideration of both cardiac disease and noncardiac conditions.

Background: Diabetes is associated with increased risk of mortality in heart failure. We examined the association of diabetes with expenditures, hospitalizations, and procedures among Medicare beneficiaries with heart failure during the last 6 months of life., Methods and Results: In a 5% national Medicare sample, the prevalence of diabetes was 41.7% among 16,613 beneficiaries who died in 2007 with a diagnosis of heart failure. Diabetes was associated with higher expenditures during the last 6 months of life (mean $39,042 vs $29,003; P < .001), even after adjusting for covariates, including age, sex, race, geographic location, comorbidities, and preceding hospitalizations (cost ratio 1.08, 95% CI 1.05-1.12). For both diabetic and nondiabetic adults, more than one-half of Medicare expenditures were related to hospitalization costs (mean $22,516 vs $15,721; P < .001). Compared with their counterparts without diabetes, beneficiaries with diabetes had higher rates of hospitalization (adjusted incidence rate ratio 1.09, 95% CI 1.05-1.12) and days spent in the intensive care unit., Conclusions: Comorbid diabetes was common in heart failure and associated with higher expenditures, much of which was driven by increased rates of hospitalizations. Programs that focus on prevention of hospitalizations may reduce the substantial costs associated with heart failure near the end of life., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Background: Although hospice use may be increasing among heart failure patients, its association with both cost and intensity of care in this population has not been well examined., Objective: To assess the association of hospice care with resource utilization among a national sample of Medicare beneficiaries with heart failure during the last 6 months of life., Methods: We performed a cross-sectional analysis of the 5% sample of Medicare claims data. Negative binomial regression models were used to compare expenditures, hospitalization rates, and intensive care unit (ICU) days between hospice and nonhospice beneficiaries. We used Poisson regression models to compare utilization of certain procedures between hospice and nonhospice beneficiaries., Results: Among 16613 Medicare beneficiaries who died with heart failure in 2007, 6436 (38.7%) received hospice care during the last 6 months of life. The mean total medical expenditures were $31,793 (SD 25,691) among decedents with hospice care, in comparison to $34,067 (SD 40,561) among decedents without hospice care. However, after adjustments for covariates, hospice care was associated with 4% higher expenditures (cost ratio, 1.04; 95% confidence interval, CI: 1.01-1.07). Hospice use was associated with reduced hospitalizations (adjusted incidence rate ratio, 0.87, 95% CI: 0.84-0.89), ICU days (adjusted incidence rate ratio, 0.68, 95% CI: 0.63-0.73), and procedures, including cardiac catheterization, noninvasive ventilation, and mechanical ventilation., Conclusions: Despite lower rates of hospitalization, ICU days, and invasive procedures, hospice care was not associated with reduced expenditures in heart failure. Financial savings related to reduced intensive medical care seems to be offset by the expenditures related to hospice care itself.

Background: Albuminuria has been associated with cardiovascular risk, but the relationship of high-normal albuminuria to subsequent heart failure has not been well established., Study Design: Prospective observational study, the Atherosclerosis Risk in Communities (ARIC) Study., Setting & Participants: 10,975 individuals free from heart failure were followed up from the fourth ARIC Study visit (1996-1998) through January 2006., Predictor: Urinary albumin-creatinine ratio (UACR), analyzed continuously and categorically as optimal (<5 mg/g), intermediate-normal (5-9 mg/g), high-normal (10-29 mg/g), microalbuminuria (30-299 mg/g), and macroalbuminuria (≥300 mg/g)., Outcomes & Measurements: Incident heart failure was defined as a heart failure-related hospitalization or death. Cox proportional hazard models were used to calculate the HR of heart failure after adjustment for age, race, sex, estimated glomerular filtration rate (eGFR), and other cardiovascular risk factors., Results: Individuals were followed up for a median of 8.3 years and experienced 344 heart failure events. Compared with normal UACR, albuminuria was associated with a progressively increased risk of heart failure from intermediate-normal (adjusted HR, 1.54; 95% CI, 1.12-2.11) and high-normal UACR (adjusted HR, 1.91; 95% CI, 1.38-2.66) to microalbuminuria (adjusted HR, 2.49; 95% CI, 1.77-3.50) and macroalbuminuria (adjusted HR, 3.47; 95% CI, 2.10-5.72). Results were similar in secondary analyses of participants censored at the time of coronary heart disease event and along a range of eGFRs., Limitations: UACR was measured as a single random sample., Conclusions: Albuminuria is associated with subsequent heart failure, even in individuals with few cardiovascular risk factors and UACR within the normal range. Our results suggest that the association between albuminuria and heart failure may not be mediated fully by ischemic heart disease or kidney disease, measured using eGFR., (Copyright © 2011 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.)

Objective: This study sought to investigate an association of HbA1c (A1C) with incident heart failure among individuals without diabetes and compare it to fasting glucose., Research Design and Methods: We studied 11,057 participants of the Atherosclerosis Risk in Communities (ARIC) Study without heart failure or diabetes at baseline and estimated hazard ratios of incident heart failure by categories of A1C (<5.0, 5.0-5.4 [reference], 5.5-5.9, and 6.0-6.4%) and fasting glucose (<90, 90-99 [reference], 100-109, and 110-125 mg/dl) using Cox proportional hazards models., Results: A total of 841 cases of incident heart failure hospitalization or deaths (International Classification of Disease, 9th/10th Revision, 428/I50) occurred during a median follow-up of 14.1 years (incidence rate 5.7 per 1,000 person-years). After the adjustment for covariates including fasting glucose, the hazard ratio of incident heart failure was higher in individuals with A1C 6.0-6.4% (1.40 [95% CI, 1.09-1.79]) and 5.5-6.0% (1.16 [0.98-1.37]) as compared with the reference group. Similar results were observed when adjusting for insulin level or limiting to heart failure cases without preceding coronary events or developed diabetes during follow-up. In contrast, elevated fasting glucose was not associated with heart failure after adjustment for covariates and A1C. Similar findings were observed when the top quartile (A1C, 5.7-6.4%, and fasting glucose, 108-125 mg/dl) was compared with the lowest quartile (<5.2% and <95 mg/dl, respectively)., Conclusions: Elevated A1C (> or =5.5-6.0%) was associated with incident heart failure in a middle-aged population without diabetes, suggesting that chronic hyperglycemia prior to the development of diabetes contributes to development of heart failure.

Objective: To examine the association between severe mental illness (SMI) and quality of care in heart failure., Methods: We conducted a cohort study between 2001 and 2004 of disabled Maryland Medicaid participants with heart failure. Quality measures and clinical outcomes were compared for individuals with and without SMI., Results: Of 1801 individuals identified with heart failure, 341 had comorbid SMI. SMI was not associated with differences in quality measures, including left ventricular assessment [adjusted relative risk (aRR) 0.99; 95% CI 0.91-1.07], utilization of angiotensin converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) (aRR 1.04; 95% CI 0.92-1.17), or beta-blocker use (aRR 1.13; 95% CI 0.99-1.29). During the study period, 52.2% of individuals in the cohort filled a prescription for an ACE inhibitor or ARB and 45.5% filled a beta-blocker prescription. Individuals with and without SMI had similar rates of clinical outcomes, including hospitalizations, readmissions, and mortality. Both medication interventions were associated with improved mortality., Conclusions: In this sample of disabled Medicaid recipients with heart failure, persons with SMI received similar quality of care as those without SMI. Both groups had low rates of beneficial medical treatments. Quality improvement programs should consider how best to target these vulnerable populations., (Copyright 2010 Elsevier Inc. All rights reserved.)

The article presents a study that examined the risk factors in seasonal differences in relation to hospital admission or due to seasonal variations in risk strata. It explores the predicted risk among hospitalized Medicare beneficiaries in seasonal variation for readmission of patients with cardiorespiratory conditions especially in winter months. The high prevalent cardiorespiratory conditions include heart failure, pneumonia, and chronic obstructive pulmonary disease (COPD).

Sodium-glucose cotransporter 2 (SGLT2) inhibitors reduce heart failure (HF) hospitalizations, recurrent cardiovascular events, and chronic kidney disease (CKD) progression, and thus constitute a Class 1a recommendation in people with diabetes and atherosclerotic cardiovascular disease, HF, or CKD and in people with severe albuminuria or HF, regardless of diabetes status. The purpose of this study was to comprehensibly characterize the rate of SGLT2 inhibitor prescriptions among people with a Class 1a recommendation for SGLT2 inhibitor use. Among 3,189,827 adults from 28 U.S. health systems within Optum Labs Data Warehouse between April 1, 2022, and March 31, 2023, we assessed SGLT2 inhibitor prescription rates, stratified by presence of diabetes and Class 1a recommendation. Among 716,387 adults with diabetes, 63.4% had a Class 1a recommendation for SGLT2 inhibitor therapy. There was little difference by Class 1a recommendation status (present: 11.9%; 95% CI: 11.9%-12.0% vs absent: 11.4%; 95% CI: 11.3%-11.6%; standardized mean difference: 1.3%). Among 2,473,440 adults without diabetes, 6.2% had a Class 1a recommendation for SGLT2 inhibitor therapy, and 3.1% (3.0%-3.2%) of those received a prescription. Internists/family practitioners initiated SGLT2 inhibitor prescriptions most commonly among people with diabetes, whereas specialists initiated SGLT2 inhibitor prescriptions most commonly among people without diabetes. No health system had >25% SGLT2 inhibitor prescription rate among people with a Class 1a recommendation. Health systems with higher proportions of patients with commercial insurance and lower proportions with Medicare had higher SGLT2 inhibitor prescription rates. In this analysis of U.S. data from 2022 to 2023, SGLT2 inhibitor prescription among people with a Class 1a recommendation is low. Interventions are needed to increase uptake of guideline-recommended SGLT2 inhibitor use. [ABSTRACT FROM AUTHOR]