Cause-Specific Health Care Costs Following Hospitalization for Heart Failure and Cost Offset With SGLT2i Therapy.

BACKGROUND: Little is known regarding differences in cause-specific costs between heart failure (HF) with ejection fraction (EF) ≤40% vs >40%, and potential cost implications of sodium glucose co-transporter 2 inhibitor (SGLT2i) therapy. OBJECTIVES: This study sought to compare cause-specific health care costs following hospitalization for HF with EF ≤40% vs >40% and estimate the cost offset with implementation of SGLT2i therapy. METHODS: This study examined Medicare beneficiaries hospitalized for HF in the Get With The Guidelines-Heart Failure registry from 2016 to 2020. Mean per-patient total (excluding drug costs) and cause-specific costs from discharge through 1-year follow-up were calculated and compared between EF ≤40% vs >40%. Next, risk reductions on total all-cause and HF hospitalizations were estimated in a trial-level meta-analysis of 5 pivotal trials of SGLT2is in HF. Finally, these relative treatment effects were applied to Medicare beneficiaries eligible for SGLT2i therapy to estimate the projected cost offset with implementation of SGLT2i, excluding drug costs. RESULTS: Among 146,003 patients, 50,598 (34.7%) had EF ≤40% and 95,405 (65.3%) had EF >40%. Mean total cost through 1 year was $40,557. Total costs were similar between EF groups overall but were higher for EF ≤40% among patients surviving the 1-year follow-up period. Patients with EF >40% had higher costs caused by non-HF and noncardiovascular hospitalizations, and skilled nursing facilities (all P < 0.001). Trial-level meta-analysis of the 5 SGLT2i clinical trials estimated 11% (rate ratio: 0.89; 95% CI: 0.84-0.93; P < 0.001) and 29% (rate ratio: 0.71; 95% CI: 0.66-0.76; P < 0.001) relative reductions in rates of total all-cause and HF hospitalizations, respectively, regardless of EF. Reductions in all-cause and HF hospitalizations were projected to reduce annual costs of readmission by $2,451 to $2,668 per patient with EF ≤40% and $1,439 to $2,410 per patient with EF >40%. CONCLUSIONS: In this large cohort of older U.S. adults hospitalized for HF, cause-specific costs of care differed among patients with EF ≤40% vs >40%. SGLT2i significantly reduced the rate of HF and all-cause hospitalizations irrespective of EF in clinical trials, and implementation of SGLT2i therapy in clinical practice is projected to reduce costs by $1,439 to $2,668 per patient over the 1 year post-discharge, excluding drug costs.

Torsemide Versus Furosemide After Discharge in Patients Hospitalized With Heart Failure Across the Spectrum of Ejection Fraction: Findings From TRANSFORM-HF.

BACKGROUND: The TRANSFORM-HF trial (Torsemide Comparison With Furosemide for Management of Heart Failure) found no significant difference in all-cause mortality or hospitalization among patients randomized to a strategy of torsemide versus furosemide following a heart failure (HF) hospitalization. However, outcomes and responses to some therapies differ by left ventricular ejection fraction (LVEF). Thus, we sought to explore the effect of torsemide versus furosemide by baseline LVEF and to assess outcomes across LVEF groups. METHODS: We compared baseline patient characteristics and randomized treatment effects for various end points in TRANSFORM-HF stratified by LVEF: HF with reduced LVEF, ≤40% versus HF with mildly reduced LVEF, 41% to 49% versus HF with preserved LVEF, ≥50%. We also evaluated associations between LVEF and clinical outcomes. Study end points were all-cause mortality or hospitalization at 30 days and 12 months, total hospitalizations at 12 months, and change from baseline in Kansas City Cardiomyopathy Questionnaire clinical summary score. RESULTS: Overall, 2635 patients (median 64 years, 36% female, 34% Black) had LVEF data. Compared with HF with reduced LVEF, patients with HF with mildly reduced LVEF and HF with preserved LVEF had a higher prevalence of comorbidities. After adjusting for covariates, there was no significant difference in risk of clinical outcomes across the LVEF groups (adjusted hazard ratio for 12-month all-cause mortality, 0.91 [95% CI, 0.59-1.39] for HF with mildly reduced LVEF versus HF with reduced LVEF and 0.91 [95% CI, 0.70-1.17] for HF with preserved LVEF versus HF with reduced LVEF; P=0.73). In addition, there was no significant difference between torsemide and furosemide (1) for mortality and hospitalization outcomes, irrespective of LVEF group and (2) in changes in Kansas City Cardiomyopathy Questionnaire clinical summary score in any LVEF subgroup. CONCLUSIONS: Despite baseline demographic and clinical differences between LVEF cohorts in TRANSFORM-HF, there were no significant differences in the clinical end points with torsemide versus furosemide across the LVEF spectrum. There was a substantial risk for all-cause mortality and subsequent hospitalization independent of baseline LVEF. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03296813.

Contemporary Use of Sodium-Glucose Cotransporter-2 Inhibitor Therapy Among Patients Hospitalized for Heart Failure With Reduced Ejection Fraction in the US: The Get With The Guidelines-Heart Failure Registry.

Importance: Clinical guidelines for patients with heart failure with reduced ejection fraction (HFrEF) strongly recommend treatment with a sodium-glucose cotransporter-2 inhibitor (SGLT2i) to reduce cardiovascular mortality or HF hospitalization. Nationwide adoption of SGLT2i for HFrEF in the US is unknown. Objective: To characterize patterns of SGLT2i use among eligible US patients hospitalized for HFrEF. Design, Setting, and Participants: This retrospective cohort study analyzed 49 399 patients hospitalized for HFrEF across 489 sites in the Get With The Guidelines-Heart Failure (GWTG-HF) registry between July 1, 2021, and June 30, 2022. Patients with an estimated glomerular filtration rate less than 20 mL/min/1.73 m2, type 1 diabetes, and previous intolerance to SGLT2i were excluded. Main Outcomes and Measures: Patient-level and hospital-level prescription of SGLT2i at hospital discharge. Results: Of 49 399 included patients, 16 548 (33.5%) were female, and the median (IQR) age was 67 (56-78) years. Overall, 9988 patients (20.2%) were prescribed an SGLT2i. SGLT2i prescription was less likely among patients with chronic kidney disease (CKD; 4550 of 24 437 [18.6%] vs 5438 of 24 962 [21.8%]; P < .001) but more likely among patients with type 2 diabetes (T2D; 5721 of 21 830 [26.2%] vs 4262 of 27 545 [15.5%]; P < .001) and those with both T2D and CKD (2905 of 12 236 [23.7%] vs 7078 vs 37 139 [19.1%]; P < .001). Patients prescribed SGLT2i therapy were more likely to be prescribed background triple therapy with an angiotensin-converting enzyme inhibitor/angiotensin receptor blocker/angiotensin receptor-neprilysin inhibitor, ß-blocker, and mineralocorticoid receptor antagonist (4624 of 9988 [46.3%] vs 10 880 of 39 411 [27.6%]; P < .001), and 4624 of 49 399 total study patients (9.4%) were discharged with prescriptions for quadruple medical therapy including SGLT2i. Among 461 hospitals with 10 or more eligible discharges, 19 hospitals (4.1%) discharged 50% or more of patients with prescriptions for SGLT2i, whereas 344 hospitals (74.6%) discharged less than 25% of patients with prescriptions for SGLT2i (including 29 [6.3%] that discharged zero patients with SGLT2i prescriptions). There was high between-hospital variance in the rate of SGLT2i prescription in unadjusted models (median odds ratio, 2.53; 95% CI, 2.36-2.74) and after adjustment for patient and hospital characteristics (median odds ratio, 2.51; 95% CI, 2.34-2.71). Conclusions and Relevance: In this study, prescription of SGLT2i at hospital discharge among eligible patients with HFrEF was low, including among patients with comorbid CKD and T2D who have multiple indications for therapy, with substantial variation among US hospitals. Further efforts are needed to overcome implementation barriers and improve use of SGLT2i among patients with HFrEF.

Quality of Care and Outcomes Among Patients Hospitalized for Heart Failure in Rural vs Urban US Hospitals: The Get With The Guidelines-Heart Failure Registry.

Importance: Prior studies have suggested patients with heart failure (HF) from rural areas have worse clinical outcomes. Contemporary differences between rural and urban hospitals in quality of care and clinical outcomes for patients hospitalized for HF remain poorly understood. Objective: To assess quality of care and clinical outcomes for US patients hospitalized for HF at rural vs urban hospitals. Design, Setting, and Participants: This retrospective cohort study analyzed 774 419 patients hospitalized for HF across 569 sites in the Get With The Guidelines-Heart Failure (GWTG-HF) registry between January 1, 2014, and September 30, 2021. Postdischarge outcomes were assessed in a subset of 161 996 patients linked to Medicare claims. Data were analyzed from August 2022 to January 2023. Main Outcomes and Measures: GWTG-HF quality measures, in-hospital mortality, length of stay, and 30-day mortality and readmission outcomes. Results: This study included 19 832 patients (2.6%) and 754 587 patients (97.4%) hospitalized at 49 rural hospitals (8.6%) and 520 urban hospitals (91.4%), respectively. Of 774 419 included patients, 366 161 (47.3%) were female, and the median (IQR) age was 73 (62-83) years. Compared with patients at urban hospitals, patients at rural hospitals were older (median [IQR] age, 74 [64-84] years vs 73 [61-83] years; standardized difference, 10.63) and more likely to be non-Hispanic White (14 572 [73.5%] vs 498 950 [66.1%]; standardized difference, 34.47). In adjusted models, patients at rural hospitals were less likely to be prescribed cardiac resynchronization therapy (adjusted risk difference [aRD], -13.5%; adjusted odds ratio [aOR], 0.44; 95% CI, 0.22-0.92), angiotensin-converting enzyme inhibitor or angiotensin receptor blocker (aRD, -3.7%; aOR, 0.71; 95% CI, 0.53-0.96), and an angiotensin receptor-neprilysin inhibitor (aRD, -5.0%; aOR, 0.68; 95% CI, 0.47-0.98) at discharge. In-hospital mortality was similar between rural and urban hospitals (460 of 19 832 [2.3%] vs 20 529 of 754 587 [2.7%]; aOR, 0.86; 95% CI, 0.70-1.07). Patients at rural hospitals were less likely to have a length of stay of 4 or more days (aOR, 0.75; 95% CI, 0.67-0.85). Among Medicare beneficiaries, there were no significant differences between rural and urban hospitals in 30-day HF readmission (adjusted hazard ratio [aHR], 1.03; 95% CI, 0.90-1.19), all-cause readmission (aHR, 0.97; 95% CI, 0.91-1.04), and all-cause mortality (aHR, 1.05; 95% CI, 0.91-1.21). Conclusions and Relevance: In this large contemporary cohort of US patients hospitalized for HF, care at rural hospitals was independently associated with lower use of some guideline-recommended therapies at discharge and shorter length of stay. In-hospital mortality and 30-day postdischarge outcomes were similar at rural and urban hospitals.

Self-Care of African Immigrant Adults with Chronic Illness.

This cross-sectional study aims to describe the self-care of adult African immigrants in the US with chronic illness and explore the relationship between acculturation and self-care. A total of 88 African immigrants with chronic illness were enrolled. Self-care was measured with the Self Care of Chronic Illness Inventory v3 and the Self-Care Self-Efficacy scale. Scores are standardized 0 to 100 with scores >70 considered adequate. Acculturation was measured using a modified standardized acculturation instrument and predefined acculturation proxies. The self-care scores showed adequate self-care, with the mean scores of 78.6, 77.9, and 75.6 for self-care maintenance, monitoring, and management. Self-care self-efficacy mean score was 81.3. Acculturation was not significantly associated with self-care. Self-care self-efficacy was a strong determinant of self-care maintenance (p < .0001), monitoring (p < .0001), and management (p < .0001). The perception of inadequate income was a significant determinant of poor self-care management (p = .03). Self-care self-efficacy and perceived income adequacy were better determinants of self-care than acculturation.

Leveraging Electronic Health Records and Machine Learning to Tailor Nursing Care for Patients at High Risk for Readmissions.

BACKGROUND: Electronic health record-derived data and novel analytics, such as machine learning, offer promising approaches to identify high-risk patients and inform nursing practice. PURPOSE: The aim was to identify patients at risk for readmissions by applying a machine-learning technique, Classification and Regression Tree, to electronic health record data from our 300-bed hospital. METHODS: We conducted a retrospective analysis of 2165 clinical encounters from August to October 2017 using data from our health system's data store. Classification and Regression Tree was employed to determine patient profiles predicting 30-day readmission. RESULTS: The 30-day readmission rate was 11.2% (n = 242). Classification and Regression Tree analysis revealed highest risk for readmission among patients who visited the emergency department, had 9 or more comorbidities, were insured through Medicaid, and were 65 years of age and older. CONCLUSIONS: Leveraging information through the electronic health record and Classification and Regression Tree offers a useful way to identify high-risk patients. Findings from our algorithm may be used to improve the quality of nursing care delivery for patients at highest readmission risk.