Principal Diagnosis Of Heart Failure Research Articles

Hospital admissions and outcomes for systolic and diastolic heart failure in Spain between 2016 and 2019: A population-based study

Background and purposeIn Spain there is a lack of population data that specifically compare hospitalization for systolic and diastolic heart failure (HF). We assessed clinical characteristics, in-hospital mortality and 30-day cardiovascular readmission rates differentiating by HF type. MethodsWe conducted a retrospective observational study of patients discharged with the principal diagnosis of HF from The National Health System’ acute hospital during 2016–2019, distinguishing between systolic and diastolic HF. The source of the data was the Minimum Basic Data Set. The risk-standardized in-hospital mortality ratio and risk-standardized 30-day cardiovascular readmission ratio were calculated using multilevel risk adjustment models. Results190,200 episodes of HF were selected. Of these, 163,727 (86.1%) were classified as diastolic HF and were characterized by older age, higher proportion of women, diabetes mellitus, dementia and renal failure than those with systolic HF. In the multilevel risk adjustment models, diastolic HF was a protective factor for both in-hospital mortality (Odds ratio-OR-: 0.79; 95% confidence interval [CI], 0.75−0.83; p < 0.001) and 30-day cardiovascular readmission versus systolic HF (OR: 0.93; 95%CI: 0.88−0.97; p = 0.002). ConclusionsIn Spain, between 2016 and 2019, hospitalization episodes for HF were mostly due to diastolic HF. According to the multilevel risk adjustment models, diastolic HF compared to systolic HF was a protective factor for both in-hospital mortality and 30-day cardiovascular readmission.

Ingresos en fines de semana y festivos por insuficiencia cardiaca descompensada y mortalidad intrahospitalaria. ¿Un efecto acumulativo de los «días no laborables»?

Introduction and objectivesThe aim of this study was to analyze whether nonelective admissions in patients with heart failure (HF) on nonworking days (NWD) are associated with higher in-hospital mortality. MethodsWe conducted a retrospective (2018-2019) observational study of episodes of nonelective admissions in patients aged 18 years and older discharged with a principal diagnosis of HF in acute general hospitals of the Spanish National Health System. NWD at admission were defined as Fridays after 14:00hours, Saturdays, Sundays, and national and regional holidays. In-hospital mortality was analyzed with logistic regression models. The length of NWD was considered as an independent continuous variable. Propensity score matching was used as a sensitivity analysis. ResultsWe selected 235 281 episodes of nonelective HF admissions. When the NWD periods were included in the in-hospital mortality model, the increases in in-hospital mortality compared with weekday admission were as follows: 1 NWD day (OR, 1.11; 95%CI, 1.07-1.16); 2 days (OR, 1.13; 95%CI, 1.09-1.17); 3 (OR, 1.16; 95%CI, 1.05-1.27); and ≥4 days (OR, 1.20; 95%CI, 1.09-1.32). There was a statistically significant association between a linear increase in NWD and higher risk-adjusted in-hospital mortality (chi-square trend P=.0002). After propensity score matching, patients with HF admitted on NWD had higher in-hospital mortality than those admitted on weekdays (OR, 1.11; average treatment effect, 12.2% vs 11.1%; P<.001). ConclusionsWe found an association between admissions for decompensated HF on an NWD and higher in-hospital mortality. The excess mortality is likely not explained by differences in severity. In this study, the “weekend effect” tended to increase as the NWD period became longer.Full English text available from:www.revespcardiol.org/en

Hospitalizaciones y eventos por insuficiencia cardiaca sistólica y diastólica en España entre 2016 y 2019. Un estudio de base poblacional

Background and purposeIn Spain there is a lack of population data that specifically compare hospitalization for systolic and diastolic heart failure (HF). We assessed clinical characteristics, in-hospital mortality and 30-day cardiovascular readmission rates differentiating by HF type. MethodsWe conducted a retrospective observational study of patients discharged with the principal diagnosis of HF from The National Health System’ acute hospital during 2016-2019, distinguishing between systolic and diastolic HF. The source of the data was the Minimum Basic Data Set. The risk-standardized in-hospital mortality ratio and risk-standardized 30-day cardiovascular readmission ratio were calculated using multilevel risk adjustment models. ResultsThe 190,200 episodes of HF were selected. Of these, 163,727 (86.1%) were classified as diastolic HF and were characterized by older age, higher proportion of women, diabetes mellitus, dementia and renal failure than those with systolic HF. In the multilevel risk adjustment models, diastolic HF was a protective factor for both in-hospital mortality (odds ratio [OR]: 0.79; 95% confidence interval [CI]: 0.75-0.83; P<.001) and 30-day cardiovascular readmission versus systolic HF (OR: 0.93; 95% CI: 0.88-0.97; P=.002). ConclusionsIn Spain, between 2016 and 2019, hospitalization episodes for HF were mostly due to diastolic HF. According to the multilevel risk adjustment models, diastolic HF compared to systolic HF was a protective factor for both in-hospital mortality and 30-day cardiovascular readmission.

Abstract 15810: Relationship Between Left Ventricular Ejection Fraction and ICD-10 Codes Among Patients Hospitalized for Heart Failure

Introduction: International Classification of Diseases (ICD)-10 codes are routinely used to classify patients with heart failure (HF). Although these codes play an important role with case identification and reimbursement, they are perceived to lack clinical specificity. Goals/Aims: We sought to describe the relationship between HF type (based on left ventricular ejection fraction [LVEF]) and assigned HF ICD-10 code in a large real-world dataset. Methods: We performed a retrospective cross-sectional analysis of patients admitted to a large health system within the western US between 1/1/18 and 10/1/2022 with a principal diagnosis of HF (ICD-10 codes: I50.2, systolic HF; I50.3, diastolic HF; I50.4, combined systolic and diastolic HF; I11.0, hypertensive heart disease with HF; and I13.0 and I13.2, hypertensive heart disease with HF and chronic kidney disease [CKD]). The analysis was further limited to patients with an LVEF by echocardiography in the 3 months preceding hospital discharge. Results: Over nearly 5 years, 61,238 HF hospitalizations occurred, of which 49,772 (81%) had an LVEF available. Most patients admitted with systolic HF (4.4% of the cohort) as well as systolic and diastolic HF (3.2% of the cohort) had an LVEF ≤40% (86.2% and 74.8%, respectively); similarly, most patients admitted with diastolic HF (3.1% of the cohort) had an LVEF ≥50% (94.0%) (Figure). Those admitted with hypertensive heart disease with HF (36.3% of the cohort) and hypertensive heart disease with HF and CKD (52.9% of the cohort) had a much wider LVEF distribution (Figure). Conclusions: Although relatively good concordance was noted between LVEF and ICD-10 codes for systolic HF, diastolic HF, and systolic and diastolic HF, this was not the case for most HF hospitalizations. This should be considered when performing analyses with HF ICD-10 codes.

Abstract 12291: Impact of History of Mental Health Disorder on In-Hospital Mortality in Patients With Heart Failure. A Population-Based Cohort Study

Introduction: Mental health disorders are associated with lower life expectancy and patients with mental disorders are at an increased risk of heart failure. Data on the prognostic impact of mental disorders on heart failure outcomes is limited and inconclusive. Hypothesis: Mental health disorders are associated with increased risk of in-hospital mortality in patients with heart failure. Methods: The study population were patients aged ≥18 years in acute care hospitals with heart failure as principal diagnosis in Texas for years 2016 through 2021. Three prespecified models were applied to estimate the association between mental disorders and in-hospital mortality. Multilevel, multivariable logistic regression with propensity adjustment was the primary analysis approach with propensity score matching and multivariable logistic regression without propensity adjustment applied as alternative analyses. Additional analyses were completed for patient subgroups, categories of mental disorders, and classifications of heart failures. Results: Out of 513,565 heart failure hospitalizations, 103,675 (20.2%) had mental disorders. Heart failure hospitalizations with vs without mental disorders were more commonly female (61.3% vs 46.0%), white (55.3% vs 46.9%), and obese (31.6% vs 26.4%), but had less frequent need for mechanical ventilation (1.8% vs 2.1%); p &lt; 0.0001 for each. Unadjusted in-hospital mortality among heart failure hospitalizations with and without mental disorders was 1.7% vs 2.2%. On adjusted analyses, mental disorders remained associated with lower odds of in-hospital mortality (adjusted odds ratio 0.8650 [95% CI 0.8149-0.9183]). The results were similar for the alternative modeling approaches, subgroup analyses, and classifications of heart failure. Conclusion: Mental disorders were associated with substantially lower risk of in-hospital mortality for patients with a principal diagnosis of heart failure.

Weekend and holiday admissions for decompensated heart failure and in-hospital mortality. A cumulative effect of “nonworking” days?

Introduction and objectives: The aim of this study was to analyze whether nonelective admissions in patients with heart failure (HF) on nonworking days (NWD) are associated with higher in-hospital mortality.Methods: We conducted a retrospective (2018-2019) observational study of episodes of nonelective admissions in patients aged 18 years and older discharged with a principal diagnosis of HF in acute general hospitals of the Spanish National Health System. NWD at admission were defined as Fridays after 14:00 hours, Saturdays, Sundays, and national and regional holidays. In-hospital mortality was analyzed with logistic regression models. The length of NWD was considered as an independent continuous variable. Propensity score matching was used as a sensitivity analysis.Results: We selected 235 281 episodes of nonelective HF admissions. When the NWD periods were included in the in-hospital mortality model, the increases in in-hospital mortality compared with weekday admission were as follows: 1 NWD day (OR, 1.11; 95%CI, 1.07-1.16); 2 days (OR, 1.13; 95%CI, 1.09-1.17); 3 (OR, 1.16; 95%CI, 1.05-1.27); and ≥ 4 days (OR, 1.20; 95%CI, 1.09-1.32). There was a statistically significant association between a linear increase in NWD and higher risk-adjusted in-hospital mortality (chi-square trend P = .0002). After propensity score matching, patients with HF admitted on NWD had higher in-hospital mortality than those admitted on weekdays (OR, 1.11; average treatment effect, 12.2% vs 11.1%; P < .001).Conclusions: We found an association between admissions for decompensated HF on an NWD and higher in-hospital mortality. The excess mortality is likely not explained by differences in severity. In this study, the “weekend effect” tended to increase as the NWD period became longer.

Impact of end stage renal disease on the clinical outcomes of diabetics admitted for heart failure: Analysis of national inpatient sample

Introduction: Patients with diabetes and heart failure (HF) can have varying outcomes depending on whether they also have End Stage Renal Disease (ESRD). This study aimed to compare the outcomes of patients with diabetes and HF with and without ESRD. Methods: Data from the National Inpatient Sample (NIS) 2016-2018 was analyzed to find hospitalizations for patients with HF as the main diagnosis and diabetes as a secondary diagnosis, with and without ESRD. Multivariable logistic and linear regression analysis was used to adjust for confounding factors. Results: In the total cohort of 12215 patients with a principal diagnosis of heart failure and secondary diagnosis of type 2 diabetes, the in-hospital mortality rate was 2.5%. Patients with ESRD had higher odds of in-hospital mortality (1.37x) compared to those without ESRD. The mean difference in length of stay was higher for patients with ESRD (0.49 days) and in total hospital charges (13360 US$). Patients with ESRD had higher odds of developing acute pulmonary edema, cardiac arrest, and requiring endotracheal intubation. However, they had lower odds of developing cardiogenic shock or requiring an intra-aortic balloon pump insertion. Conclusion: The results suggest that ESRD leads to higher in-patient mortality, length of stay, and total hospital charges for patients with diabetes admitted for HF. The lower incidence of cardiogenic shock and intra-aortic balloon pump insertion in patients with ESRD may be due to timely dialysis.

Abstract P580: Cannabis Use Among Young Females of Ages 15 to 35 Admitted for Heart Failure in the United States

Introduction: Cannabis legalization in many states has led to an increase in the substance’s usage among the younger population, prompting patients, physicians, and policy-makers to seek more information. This study uses the 2019 National Inpatient Sample (NIS) to compare patient characteristics, comorbidities, and the presence of certain cardiac arrhythmias among young females admitted with heart failure and using cannabis compared to those not using cannabis. Hypothesis: We assessed the hypothesis that cannabis use among young females aged 15-35 with heart failure is linked to an increased baseline cardiovascular risk and a higher chance of cardiac events during hospitalization for heart failure. Method: Females of ages 15 to 35 with a principal diagnosis of heart failure were pooled from the 2019 NIS. The usage of cannabis was also identified using recommendations from past studies. Different patient characteristics were compared via Chi-Square tests, and the presence and risk of cardiac arrhythmias were also studied via logistic models. Results: Among 7780 cases of heart failure identified in women between the ages of 15 to 35, 425 (5.5%) were cannabis users. The study showed that a larger proportion of cannabis users were racially classified as Blacks (67.5%) and Medicaid was the predominant insurer (57.6%). They also had a higher prevalence of smoking (74.1% vs. 35.2%, p&lt;0.01), hypertension (27.1% vs. 22.0%, p=0.014), and peripheral vascular disease (4.7% vs 2.0%, p&lt;0.01). However, non-users had a higher prevalence of obesity (29.4% vs. 40.9%, p&lt;0.01), diabetes mellitus (21.2% vs. 31.7%, p&lt;0.01), hyperlipidemia (11.8% vs. 16.2%, p=0.016), chronic pulmonary disease (16.5% vs. 23.8%, p&lt;0.01), arthropathies (4.7% vs. 11.5%, p&lt;0.01), and hypothyroidism (5.9% vs. 10.4%, p&lt;0.01). More cannabis users reported ventricular tachycardia (9.4% vs 5.5%, aOR 1.887, 95% confidence interval 1.272-2.798, p=0.002)) and paroxysmal atrial fibrillation (4.7% vs. 2.1%, aOR 1.926, 95% confidence interval 1.089-3.438, p=0.027) during their hospitalization. On the contrary, the length of stay (LOS) in the hospital was shorter for cannabis users compared to non-users (mean stay of 5.07 days vs. 5.86 days). Conclusion: While young female cannabis users with heart failure had a shorter hospitalization, they were more prone to report arrhythmic events such as ventricular tachycardia and paroxysmal atrial tachycardia. Although differences in baseline cardiovascular risk associations were noted among this population, further clinical and laboratory studies are encouraged to help understand the pathophysiologic mechanisms behind such differences.

Abstract P585: Impact of Thrombocytopenia on the Outcomes of Patients Admitted With Heart Failure: Analysis of the National Inpatient Sample

Background: Thrombocytopenia is known to be a marker of adverse clinical outcomes in acute coronary syndromes, pulmonary hypertension and critically ill patients. Its impact on heart failure (HF) patients has not been well characterized. We aim to compare the clinical outcomes in patients admitted for HF with and without thrombocytopenia. Methods: A retrospective cohort study was designed using data obtained from the 2016-2019 National Inpatient Sample (NIS) database. Adult patients (age &gt;18) with a principal diagnosis of Heart Failure (HF) were identified using the International Classification of Diseases code, tenth revision (ICD-10), and were divided into two cohorts based on a secondary diagnosis of Thrombocytopenia. Primary outcomes evaluated were in-patient mortality, Length Of Stay (LOS) and Total Hospitalization Charges(THC). Secondary outcomes included a blood transfusion, AKI, Pneumonia, Sepsis and GI bleed. Results: Out of 1,276,429 adult patients admitted with HF, 70,755 (5.5%) were found to have a diagnosis of thrombocytopenia. The mean age was 72 years for the thrombocytopenia group vs 71 years for the other group. On a multivariate regression analysis after adjusting for confounders, HF patients with thrombocytopenia had double the odds of inpatient mortality (aOR 2.0 , 95% CI 1.84-52.16, p&lt;0.01) and LOS (aOR 2.38 , 95% CI 2.19-2.58 p&lt;0.01) compared to the other group .THC was also increased by 43,376$ ( 95%CI 38,842-47,910 ,p&lt;0.01). Among the secondary outcomes, the rate of blood transfusion (6.4% vs 2.1%, aOR 2.19, 95% CI 2.02-2.38, p&lt;0.01), AKI (37.4% vs 25.0%, aOR 1.5, 95% CI 1.44-1.56, p&lt;0.01), Pneumonia (16% vs 13%, aOR 1.18, 95% CI 1.12-1.25, p&lt;0.01),Sepsis (3.08% vs 1.13, aOR 2.5 ,95% CI 2.22-2.78, p&lt;0.01) and GI Bleed (0.9 %vs 0.4 %, aOR 1.68, 95% CI 1.38-2.05, p&lt;0.01) was also significantly elevated in the thrombocytopenia group. Conclusion: HF patients with thrombocytopenia had worse clinical outcomes compared to those without. Very few studies have explored this impact of thrombocytopenia on HF and concluded with similar outcomes, probably related to abnormal platelet activity in this population and its consequence on cardiac function. This finding highlights the need for future studies to elucidate the pathophysiology and include platelet level in prognostic tools.

Association Between Frailty, 30-day Unplanned Readmission and Mortality After Hospitalization for Heart Failure: Results From the Nationwide Readmissions Database.

Objectives: This study examined how frailty in traditional risk-adjusted models could improve the predictability of unplanned 30-day readmission and mortality among heart failure patients. Methods: This study was a retrospective analysis of Nationwide Readmissions Database data collected during the years 2010-2018. All patients ≥65years who had a principal diagnosis of heart failure were included in the analysis. The Johns Hopkins Adjusted Clinical Groups frailty-defining diagnosis indicator was used to identify frail patients. Results: There was a total of 819,854 patients admitted for heart failure during the study period. Among them, 63,302 (7.7%) were frail. In the regression analysis, the risk of all-cause 30-day readmission (OR, 1.18; 95% CI, 1.14-1.22) and in-hospital mortality (OR, 1.52; 95% CI, 1.40-1.66) were higher in patients with frailty. Discussion: Inclusion of frailty in comorbidity-based risk-prediction models significantly improved the predictability of unplanned 30-day readmission and in-hospital mortality.

The affordable care act and do-not-resuscitate orders: Differences by race and ethnicity

BackgroundThe Affordable Care Act (ACA) created new payment rules that provided reimbursement for physicians to engage in advance care planning (ACP) conversations with patients. This reimbursement policy has the potential to increase ACP participation, including among racial and ethnic minority groups that have had lower ACP participation. ObjectivesTo examine whether the ACP payment rules were associated with an increase in use of do-not-resuscitate (DNR) orders, particularly among racial and ethnic minority groups, among patients diagnosed with heart failure (HF) in California. MethodsThe California Office of Statewide Health Planning and Development (OSHPD) Patient Discharge Data Set was used to identify a cohort of elderly patients with a principal diagnosis of HF. This study included 432,520 hospital admissions of patients over the age of 65 with a primary diagnosis of HF between 2012 and 2018. DNR status was identified using International Classification of Diseases, Clinical Modification Ninth and Tenth Revision, codes. ResultsThere was a small increase in the utilization of DNR orders overall after the ACA reimbursement policy, but the change was not significantly different for all racial and ethnic groups when compared to white non-Hispanic patients. ConclusionsACP payment rules provided in the ACA were associated with increased utilization of DNR, but the effect was not significantly different for racial and ethnic minorities hospitalized with HF in CA. Additional efforts are needed to increase ACP participation among racial and ethnic minorities.

The effect of the COVID-19 pandemic on heart failure unplanned admission: a single center study

BackgroundAcute heart failure (AHF) is a leading cause of admissions among adults. The COVID-19 pandemic has placed a high burden on healthcare systems globally. Many countries announced lockdowns which restricted residents' movement. There is a reported reduction in AHF admissions during the pandemic in several countries, potentially leading to adverse outcomes such as increased morbidity and mortality. To date, little is known on whether similar trends are observed in Southeast Asian (SEA) countries.PurposeWe aim to evaluate whether AHF admissions have been affected by the pandemic and the lockdown restrictions in a multi-ethnic, urban SEA country. We hypothesized that the pandemic and lockdown restrictions (called a “circuit breaker (CB)”) will influence heart failure (HF) admission rates.MethodsWe conducted a retrospective analysis of patients who were admitted with a principal diagnosis of HF to a tertiary hospital in a SEA country. The study period was from the first confirmed case of COVID-19 (January 23, 2020) to July 31, 2020 (n=378). This was further divided into 3 sub-periods for inter-year and intra-year subgroup analysis. Pre-CB: January 23, 2020 to April 6, 2020, CB: April 7, 2020 to June 1, 2020, and Post-CB reopening (Phase 1 & 2): June 2, 2020 to July 31, 2020. The control period was the same timeframe in the preceding year (January 23, 2019 to July 31, 2019) (n=398) and was similarly divided into 3 subgroups. The primary outcome was the overall HF admission rate. Where appropriate, Poisson regression or Negative Binomial regression was utilised to compare the incidence rate ratios of the HF admissions between the periods. Mann-Whitney test or student's t-test was used to compare the length of stay (LOS) and Charlson Comorbidity Index (CCI) scores.ResultsDetails on the study cohort can be found in Table 1. The study period's overall mean admission rate was 2.08 per day, which was not significantly different from the control (2.00 per day). Subgroup analysis showed that the CB admission rates were significantly lower compared to (i) the control (1.39 per day vs. 2.02 per day) and (ii) pre-CB period in the same year (1.39 per day vs. 2.44 per day) (Fig. 1). Phase 1 & 2 admission rates were significantly higher compared to the control (2.28 per day vs. 1.68 per day), and CB admission rates (2.28 per day vs. 1.39 per day). There were no inter-year or intra-year differences for LOS. There was a significant inter-year difference in CCI scores during the CB period (CB: 2.88 vs. control: 1.97).ConclusionsOur study showed significant decreases in AHF admissions during the CB period, and a significant increase in AHF admissions from CB to Post-CB reopening. These suggest that the lockdown restrictions had an influence on patients' health seeking behaviour. We also recognise the need to raise public awareness to encourage HF patients to seek timely treatment, prevent complications and adverse events.Funding AcknowledgementType of funding sources: None. Table 1. Study cohorts demographicsFigure 1. Weekly HF admissions to hospital in 2020

Thirteen-year trends in hospitalization and outcomes of patients with heart failure in Spain.

Heart failure is one of the most pressing current public health concerns. However, in Spain there is a lack of population data. We aimed to examine thirteen-year nationwide trends in heart failure hospitalization, in-hospital mortality and 30-day readmission rates in Spain. We conducted a retrospective observational study of patients discharged with the principal diagnosis of heart failure from The National Health System' acute hospitals during 2003-2015. The source of the data was the Minimum Basic Data Set. Temporal trends were modelled using Poisson regression analysis. The risk-standardized in-hospital mortality ratio was calculated usinga multilevelrisk adjustmentlogistic regressionmodel. A total of 1254830 episodes of heart failure were selected. Throughout 2003-2015, the number of hospital discharges with principal diagnosis of heart failure increased by 61%. Discharge rates weighted by age and sex increased during the period [incidence rate ratio (IRR): 1.03; 95% confidence interval (95% CI): 1.03-1.03; P<.001)], although this increase was motivated by the increase in older age groups (≥75years old). The crude mortality rate diminished (IRR: 0.99; 95% CI: 0.98-1, P<.001), but 30-day readmission rate increased (IRR: 1.05; 95% CI: 1.04-1.06; P<.001). The risk-standardized in-hospital mortality ratio did not change throughout the study period (IRR: 0.997; 95% CI: 0.992-1; P=.32). From 2003 to 2015, heart failure admission rates increased significantly in Spain as a consequence of the sustained increase of hospitalization in the population ≥75years. 30-day readmission rates increased, but the risk-standardized in-hospital mortality ratio did not significantly change for the same period.

Impact of Global Budget Payments on Cardiovascular Care in Maryland: An Interrupted Time Series Analysis.

Background Global budget payments (GBP) are considered effective in containing health care expenditures; however, information on their impact on quality of cardiovascular care is limited. We aimed to evaluate the effects of GBP on utilization, outcomes, and costs for 3 major cardiovascular conditions. Methods We analyzed claims data of hospital admissions in Maryland from fiscal year 2013 to 2018. Using segmented regression, we evaluated temporal trends in hospitalizations, length of stay, percutaneous coronary intervention and coronary artery bypass grafting volumes, case mix-adjusted 30-day readmission rates, risk-standardized mortality rates, and hospitalization charges in patients with principal diagnosis of heart failure, acute ischemic stroke, and acute myocardial infarction (AMI) in relation to GBP implementation. Trends in global cardiovascular procedure charges/volumes were also studied. Results Hospitalization rates for congestive heart failure and AMI remained unaffected by GBP, while the gradient of ischemic stroke admissions decreased (Ptrend <0.0001). Length of stay slightly increased for patients with congestive heart failure (Ptrend=0.03). Inpatient coronary artery bypass grafting surgeries decreased (Ptrend <0.0001). We observed a significant decrease in casemix-adjusted 30-day readmission rate in the AMI cohort beyond the prepolicy trend (Ptrend=0.0069). There were no significant changes in mortality for any of the 3 conditions. Hospitalization charges increased for ischemic stroke (Ptrend <0.0001), remained constant for congestive heart failure (Ptrend=0.1), and decreased for AMI (Ptrend=0.0005). We observed a significant increase in electrocardiography rate charges (Ptrend <0.0001), coincidentally with a reduction in volumes (Ptrend=0.0003). Conclusions Introducing GBP in Maryland had no perceivable adverse effects on inpatient outcomes and quality indicators for 3 major cardiovascular conditions. Savings were observed in the AMI cohort, possibly due to reduced unnecessary readmissions, efficiency improvements, or shifts to outpatient care. Reduced cardiovascular procedure volumes were counterbalanced by a proportional rise in charges. State-level adoption of GBP with pay-for-performance incentives may be effective for cost containment without adversely impacting quality of cardiovascular care.

Association Between Use of EHR-Generated Dashboards and Hospital Outcomes in 30-Day Heart Failure Readmissions.

This study examined whether usage of clinical data from the electronic health record (EHR) to create organizational- and unit-level performance dashboards and assess adherence to clinical practice guidelines is associated with hospital outcomes in risk-adjusted 30-day readmissions for patients with a principal diagnosis of heart failure (HF). It further assesses the association between the metrics of hospital financial health and the usage of those EHR-generated tools.A cross-sectional study design was used. The study used data from the 2016 American Hospital Association Annual Survey Information Technology Supplement, the Pennsylvania Health Care Cost Containment Council's (PHC4's) 2017 Hospital Performance Report, and the PHC4 General Acute Care Hospitals Financial Analysis Report for fiscal year 2017. Contingency tables, likelihood-ratio chi-square tests, and logistic regression were applied for data analysis.Usage of the EHR to assess adherence to clinical practice guidelines and create EHR-generated unit-level performance dashboards, rather than organizational performance dashboards, was more strongly associated with the hospitals' rating in risk-adjusted 30-day readmissions for HF patients. An increase in hospitals' operating margin was associated with greater odds of the usage of the discussed EHR tools, after controlling for hospital control/ownership and the total number of beds.Usage of some EHR-generated analytical tools may be more strongly associated with lower-than-expected 30-day hospital readmissions in HF patients than with other tools. Better hospital financial health is linked with greater uptake of the discussed analytical tools. Further research could help to determine which EHR-generated tools are more effective in improving hospital outcomes in HF.

The Decrease in Hospitalizations For Heart Failure During the Covid-19 Pandemic: A Community and Academic Hospital Comparison Study

IntroductionDuring the novel coronavirus (COVID-19) pandemic, the incidence of cardiovascular hospitalizations has been observed to decrease. The patient behavior, clinician behavior and pathophysiological contributors are currently unclear. We sought to determine if the pattern of heart failure (HF) hospitalizations was the same between 1 Academic Hospital with Advanced HF and Transplant services and 2 Community Hospitals, within a single health system in Massachusetts (MA).MethodsThe 3 hospitals, Academic/Advanced HF Hospital A, Community Hospital B and Community Hospital C, are all located within 30-mile radius and share many clinical protocols, although HF hospitalizations at Academic/Advanced HF Hospital A include advanced HF therapy referrals and patients listed for heart transplantation. We retrospectively reviewed the weekly adult hospitalizations for HF, defined as patients ≥18 years discharged with a principal diagnosis of HF per ICD-10 coding (I110, I130, I132, I50 subsets) across the 3 hospitals, between January 1 and April 26 in 2019 and 2020. The weekly hospitalization volumes for 2019 and 2020 were displayed as a bar graph, alongside the total MA COVID-19 diagnosis and key dates in the pandemic response, for each hospital.ResultsThe volume of weekly hospitalizations for HF in March and April 2020 were lower at all 3 hospitals, as compared to 2019 (Figure 1). At Academic/Advanced HF Hospital A, the reduction in weekly HF hospitalizations began in mid-February, prior to the MA ‘state of emergency’ declaration effective March 11 and the ‘stay at home’ order effective March 24, 2020. Conversely, at Community Hospitals B and C the reduction in hospitalizations for HF (compared to 2019) occurred closer to the ‘stay at home’ order. The date on which each hospital formally ramped down non-urgent outpatient visits and procedures occurred first for Academic/Advanced HF Hospital A, but HF hospitalization volume reduction still appeared to precede this announcement.ConclusionThe decrease in hospitalizations for HF during the COVID-19 pandemic began in an Academic/Advanced HF Hospital before the MA ‘state of emergency’ and ‘stay at home’ orders, but around the time of the ‘state of emergency’ order in 2 affiliated Community Hospitals. This observation suggests that the factors driving HF volume during a pandemic may differ across patient populations and hospitals, even within the same region.

Abstract 204: Impact of Global Budgets on Hospital Cardiovascular Care in Maryland

Background: Global budgets (GB), an innovative method of hospital payment, have been considered effective in containing expenditures. In January 2014, the state of Maryland introduced Global Budget Revenues (GBR), transitioning from per case to capitated, population-based payments (PBP). Under this model, hospitals are provided yearly funds, thus being financially incentivized to improve efficiency of services. Prices are set by the Health Services Cost Review Commission (HSCRC), which collects data and monitors hospitals’ quality of care. Potential adverse incentives of GB would include underprovision of necessary services or avoiding sicker, high cost patients (cream skimming). This study aimed to evaluate the effects of GBR on the care of hospitalized patients with important CV conditions. Methods: We analyzed HSCRC inpatient claim databases containing anonymized information on statewide hospital admissions between fiscal years 2013 and 2018. Using ICD codes, we identified patients with a principal diagnosis of heart failure (CHF), acute myocardial infarction (AMI), and acute ischemic stroke (AIS) from a pool of 1,959,237 inpatient admissions. Outcome measures were: hospitalizations, length of stay (LOS), inpatient PCI and CABG procedure rates, casemix adjusted 30-day readmission rates (CARR), risk standardized in-hospital mortality, and hospitalization charges. Trends in outcome measures before and after GBR implementation were compared using segmented regression analysis, with p values indicating trend change. Results: With introduction of GBR, CHF and AMI hospitalization trends did not change significantly, whereas AIS admissions stabilized downward (p&lt;0.0001). There was an increase in mean LOS for CHF (p=0.059). CARR followed pre-policy declining trends, with more consistent improvements noted for the AMI cohort (p=0.005). In-hospital mortality continued to decrease, although at slower rates for CHF and AMI cohorts (p=0.03; p=0.019). CABG procedure rates declined significantly (p&lt;0.0001). Mean hospitalization charges increased for all three CV conditions, faster for CHF (p=0.03) and AIS (p&lt;0.0001), slower for AMI (p=0.0003). Conclusions: Adoption of GBR in Maryland had no harmful effects on in-hospital outcomes and quality measures. There was a modest improvement in potentially avoidable hospitalizations and mildly reduced utilization offset by significant rise in charges. Some observations could result from care shifts to the outpatient setting. Quality of CV care was not affected by GBR suggesting that efficiency improvements might have occurred in other areas of the healthcare system. Additionally, combining GB with pay for performance programs and assiduous quality monitoring might have mitigated adverse incentives. As GBR transitions to Maryland Total Cost of Care, long-term effects of PBP on CV outcomes will require further investigation.

Relation of a Simple Cardiac Co-Morbidity Count and Cardiovascular Readmission After a Heart Failure Hospitalization

Although several risk calculators are available to determine risk for readmission following a heart failure (HF) hospitalization, none provide information on cause-specific readmission. Understanding risk for cause-specific readmission could aid in developing a targeted approach to reducing readmissions. We sought to determine if a simple cardiac co-morbidity count could identify individuals at high risk for a cardiovascular (CV) readmission following a HF hospitalization. Using the Nationwide Readmissions Database, we examined nonfatal hospital discharges with a principal diagnosis of HF. We calculated a 0 to 3 cardiac co-morbidity count based on the presence of coronary artery disease, atrial arrhythmia, and/or ventricular arrhythmia. We used a multinomial logistic regression to determine if the cardiac co-morbidity count was independently associated with CV readmission or non-CV readmission, adjusting for patient- and hospital-level confounders. In 380,075 discharges, 28% had a co-morbidity count of 0, 47% had a count of 1, 23% had a count of 2, and 2% had a count of 3. In a fully adjusted model, cardiac co-morbidity count was independently associated with CV readmission: compared with individuals with a count of 0, the relative risk for those with a count of 1 was 1.27 (95% confidence interval [CI]: 1.23 to 1.31); for those with a count of 2 was 1.40 (95% CI: 1.35 to 1.46); and for those with a count of 3 was 1.36 (95% CI: 1.23 to 1.51). Cardiac co-morbidity count was not independently associated with non-CV readmission. In conclusion, we found that a simple cardiac co-morbidity count was independently associated with increased risk of CV but not non-CV readmission.

Abstract P321: Assembly and Validation of a Heart Failure Free Cohort From the Reasons for Geographic and Racial Differences in Stroke Study

Introduction: Studies of incident heart failure (HF) have provided insights into key risk factors for the disease but have been limited to select populations that often lack geographic, racial, and gender diversity. There is a need to assemble a HF-free cohort using a contemporary, geographically diverse sample. Aim: To develop and validate a strategy for assembling a HF-free cohort from the REasons for Geographic And Racial Differences in Stroke (REGARDS) study. Methods: To assemble a HF-free cohort, we identified and excluded REGARDS participants who were taking HF-specific medications at baseline including: digoxin without atrial fibrillation, angiotensin converting enzyme inhibitor/angiotensin receptor blocker plus beta-blocker in the absence of hypertension, carvedilol, spironolactone, loop diuretic or a combination of hydralazine and nitrates. We then examined the subgroup of REGARDS participants with at least 6 months of Medicare claims at the time of the baseline assessment; we evaluated diagnostic performance (negative predictive value, positive predictive value, sensitivity and specificity) using three Medicare claims-based definitions of HF as the referent standard: Hospitalization for HF, Principal Diagnosis of HF, and Any Diagnosis of HF. Results: Among 28,884 eligible participants, 3,125 used HF-specific medications at baseline, leaving 25,759 (89%) participants in the proposed HF-free cohort. Participants in the HF-free cohort had a lower prevalence of coronary disease, atrial fibrillation, and diabetes compared to excluded participants. Depending on the Medicare definition used as the referent, the percent of the HF-free cohort without evidence of HF based on Medicare claims (the negative predictive value) ranged from 95.0-99.2% (Table 1). Negative predictive value was stable across age, sex, and race strata. Conclusions: This medication-based strategy to assembling a HF-free cohort in REGARDS can serve as a basis for future studies to examine incident HF in REGARDS and similar studies.

The association of hospital teaching intensity with 30-day postdischarge heart failure readmission and mortality rates.

To investigate risk-adjusted, 30-day postdischarge heart failure mortality and readmission rates stratified by hospital teaching intensity. A total of 709221 Medicare fee-for-service beneficiaries discharged from 3135 US hospitals between 1/1/2013 and 11/30/2014 with a principal diagnosis of heart failure. Hospitals were classified as Council of Teaching Hospitals and Health Systems (COTH) major teaching hospitals, non-COTH teaching hospitals, and nonteaching hospitals. Hospital teaching status was linked with MedPAR patient data and FY2016 Hospital Readmission Reduction Program penalties. Index hospitalization survival probabilities were estimated with hierarchical logistic regression and used to stratify index hospitalization survivors into severity deciles. Decile-specific models were estimated for 30-day postdischarge readmission and mortality. Thirty-day postdischarge outcomes were estimated by teaching intensity and penalty categories. Averaged across deciles, adjusted 30-day COTH hospital readmission rates were, on a relative scale ([COTH minus nonteaching]÷nonteaching), 1.63 percent higher (95% CI: 0.89 percent, 2.25 percent) than at nonteaching hospitals, but their average adjusted 30-day postdischarge mortality rates were 11.55 percent lower (95% CI: -13.78 percent, -9.37 percent). Penalized COTH hospitals had the highest readmission rates of all categories (23.99 percent [95% CI: 23.50 percent, 24.49 percent]) but the lowest 30-day postdischarge mortality (8.30 percent [95% CI: 7.99 percent, 8.57 percent] vs 9.84 percent [95% CI: 9.69 percent, 9.99 percent] for nonpenalized, nonteaching hospitals). Heart failure readmission penalties disproportionately impact major teaching hospitals and inadequately credit their better postdischarge survival.