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BackgroundSince January 2020, COVID-19 has affected more than 100 million people in the U.S. Previous studies on racial and ethnic disparities related to characteristics and outcomes of COVID-19 patients have been insightful. However, appropriate epidemiologic age-standardization of the disease burden and disparities for hospitalization data are lacking.ObjectiveTo identify and describe racial and ethnic disparities for primary COVID-19 hospitalizations in the U.S. in 2020.MethodsIn this nationally representative observational study, we use the National Inpatient Sample to quantify racial and ethnic disparities in COVID-19 hospitalizations. Descriptive statistics for patient characteristics, common comorbidities, age-standardized hospitalization rates, inpatient complications, and mortality among COVID-19 hospitalizations were contrasted by race and ethnicity.ResultsThere were 1,058,815 primary COVID-19 hospitalizations in 2020. Of those, 47.2% were female, with median age of 66 (IQR, 54, 77). Overall inpatient mortality rate was 11.1%. When compared to White patients, Black, Hispanic, and Native American patients had higher age-standardized hospitalization rate ratios of 2.42 (95% CI 2.40-2.43), 2.26 (2.25-2.28), and 2.51 (2.46-2.56), respectively. Non-White patients had increased age-adjusted rates for procedures and complications. Factors associated with inpatient mortality include age, male sex, Hispanic or Native American race or ethnicity, lower income, Medicaid, heart failure, arrhythmias, coagulopathy, and chronic liver disease.ConclusionsMarginalized populations in the U.S. had over twice the COVID-19 hospitalization rate relative to White patients. Age-adjusted mortality rates were highest for Black, Hispanic, and Native American patients. Careful consideration for vulnerable populations is encouraged during highly communicable respiratory pandemics.

This document describes performance measures for heart failure that are appropriate for public reporting or pay-for-performance programs and is meant to serve as a focused update of the "2020 ACC/AHA Clinical Performance and Quality Measures for Adults With Heart Failure: A Report of the American College of Cardiology/American Heart Association Task Force on Performance Measures." The new performance measures are taken from the "2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines" and are selected from the strongest recommendations (Class 1 or Class 3). In contrast, quality measures may not have as much evidence base and generally comprise metrics that might be useful for clinicians and health care organizations for quality improvement but are not yet appropriate for public reporting or pay-for-performance programs. New performance measures include optimal blood pressure control in patients with heart failure with preserved ejection fraction, the use of sodium-glucose cotransporter-2 inhibitors for patients with heart failure with reduced ejection fraction, and the use of guideline-directed medical therapy in hospitalized patients. New quality measures include the use of sodium-glucose cotransporter-2 inhibitors in patients with heart failure with mildly reduced and preserved ejection fraction, the optimization of guideline-directed medical therapy prior to intervention for chronic secondary severe mitral regurgitation, continuation of guideline-directed medical therapy for patients with heart failure with improved ejection fraction, identifying both known risks for cardiovascular disease and social determinants of health, patient-centered counseling regarding contraception and pregnancy risks for individuals with cardiomyopathy, and the need for a monoclonal protein screen to exclude light chain amyloidosis when interpreting a bone scintigraphy scan assessing for transthyretin cardiac amyloidosis.

BackgroundVentricular ablation may be clinically indicated for patients with recurrent ventricular tachycardia (VT) and has been shown to decrease risk of recurrence and overall morbidity. However, the existence of disparities among patients receiving ventricular ablation has not been well characterized.ObjectivesIn this study, we examined patients hospitalized with VT to determine whether disparities exist among those receiving ablations.MethodsWe used the National Inpatient Sample to assess patients hospitalized with a primary diagnosis of VT in 2019 who did and did not receive catheter ablations. Multiple logistic regression was used to calculate risk factors for VT ablation based on age, sex, race/ethnicity, socioeconomic status, and hospital characteristics.ResultsAfter adjusting for baseline characteristics and comorbidities, female and Black patients hospitalized with VT had significantly lower odds of receiving ablations compared with male and White patients (OR: 0.835; 95% CI: 0.699-0.997; P = 0.047; and OR: 0.617; 95% CI: 0.457-0.832; P = 0.002, respectively). Additionally, patients at rural or nonteaching hospitals were significantly less likely to receive ablations compared with those at urban, teaching hospitals. No significant differences were noted based on income or insurance status in the adjusted models.ConclusionsWe identified significant disparities in the delivery of ventricular ablations among patients hospitalized with VT. Overall, patients who were female or Black as well as those who were hospitalized at rural or nonteaching hospitals were significantly less likely to receive VT ablations during hospitalization.

BackgroundHow housing insecurity might affect patients with heart failure (HF) is not well characterized. Housing insecurity increases risks related to both communicable and non-communicable diseases. For patients with HF, housing insecurity likely increases the risk for worse outcomes and rehospitalizations.Methods and resultsWe analyzed U.S. HF hospitalizations using the 2020 National Inpatient Sample (NIS) and Nationwide Readmissions Database (NRD) to evaluate the impacts of housing insecurity on HF outcomes and hospital utilization. Individuals were identified as having housing insecurity using diagnostic ICD-10 codes. Demographics and comorbidities were compared between HF patients with and without housing insecurity. An adjusted logistic regression was performed to evaluate the relationships between housing insecurity and socioeconomic status on in-hospital mortality. Using a Cox proportional hazards model, HF patients with and without housing insecurity were evaluated for the risk of all-cause and HF-specific readmissions over time. Of the 1,003,270 hospitalizations for HF in the U.S. in 2020, 16,150 were identified as having housing insecurity (1.6%) and 987,120 were identified as having no housing insecurity (98.4%). The median age of patients with housing insecurity hospitalized for HF was 57, as compared to 73 in the population with no housing insecurity. A higher proportion of patients in the housing insecurity group were Black (35% vs 20.1%) or Hispanic (11.1% vs 7.3%). Patients with housing insecurity were more likely to carry a diagnosis of alcohol use disorder (15.2% vs 3.3%) or substance use disorder (70.2% vs 17.8%), but were less likely to use tobacco (18.3% vs 28.7%). Patients with housing insecurity were over 4.5 times more likely to have Medicaid (52.4% vs 11.3%). Median length of stay did not differ between patients with housing insecurity versus those without. Patients with housing insecurity were more likely to discharge Against Medical Advice (11.4% vs 2.03%). After adjusting for patient characteristics, housing insecurity was associated with lower in-hospital mortality (OR 0.60, 95% CI 0.39 - 0.92). Housing insecurity was associated with a higher risk of all-cause readmissions at 180 days (HR 1.13, 95% CI 1.12 - 1.14). However, there was no significant difference in the risk of HF-specific readmissions at 180 days (HR 1.07, 95% CI 0.998 - 1.14) CONCLUSIONS: Patients with HF and housing insecurity have distinct demographic characteristics. They are also more likely to be readmitted after their initial hospitalization when compared to those without housing insecurity. Identifying and addressing specific comorbid conditions for patients with housing insecurity who are hospitalized for HF may allow clinicians to provide more focused care, with the goal of preventing morbidity, mortality, and unnecessary readmissions.

BackgroundThe optimal timing of noncardiac surgery (NCS) following transcatheter aortic valve replacement (TAVR) for aortic stenosis has not been elucidated by current national guidelines.ObjectivesThe aim of this study was to evaluate the effect of the time interval between TAVR and NCS (Δt) on the perioperative risk of major adverse events (MAEs).MethodsAll adult admissions for isolated TAVR for aortic stenosis were identified in the 2016 to 2020 Nationwide Readmissions Database. Patients who received NCS on subsequent admission were included for analysis and grouped by Δt as follows: ≤30, 31 to 60, 61 to 90, and >90 days. Multivariable regression models were constructed to examine the association of Δt with ensuing outcomes.ResultsOf 3,098 patients (median age = 79 years, 41.6% female), 19.1% underwent NCS at ≤30 days, 22.9% at 31 to 60 days, 16.7% at 61 to 90 days, and 41.3% at >90 days. After adjustment, the odds of MAEs were similar for operations performed at ≤30 days (adjusted OR [AOR]: 1.05; 95% confidence interval [CI]: 0.74-1.50), 31 to 60 days (AOR: 0.97; 95% CI: 0.71-1.31), and 61 to 90 days (AOR: 0.95; 95% CI: 0.67-1.34), with those at >90 days as reference. When examining the average marginal effect of the interval to surgery, risk-adjusted MAE rates were statistically similar across Δt groups for elective status and NCS risk category combinations.ConclusionsNCS within 30, 31 to 60, or 61 to 90 days after TAVR was not associated with increased odds of MAEs compared with operations after 90 days irrespective of NCS risk category or elective status. Our findings suggest that the interval between NCS and TAVR may not be an accurate predictor of MAE risk in this population.

Mean cardiovascular health has improved over the past several decades in the United States, but it is unclear whether the benefit is shared equitably. This study examined 30-year trends in cardiovascular health using a suite of income equity metrics to provide a comprehensive picture of cardiovascular income equity. The study evaluated data from the 1988-2018 National Health and Nutrition Examination Survey. Survey groupings were stratified by poverty-to-income ratio (PIR) category, and the mean predicted 10-year risk of a major cardiovascular event or death based on the pooled cohort equations (PCE) was calculated (10-year PCE risk). Equity metrics including the relative and absolute concentration indices and the achievement index-metrics that assess both the prevalence and the distribution of a health measure across different socioeconomic categories-were calculated. A total of 26 633 participants aged 40 to 75 years were included (mean age, 53.0-55.5 years; women, 51.9%-53.0%). From 1988-1994 to 2015-2018, the mean 10-year PCE risk improved from 7.8% to 6.4% (P

Heart failure (HF) is a common disease with increasing prevalence around the world. There is high morbidity and mortality associated with poorly controlled HF along with increasing costs and strain on healthcare systems due to a high rate of rehospitalization and resource utilization. Despite the establishment of clear evidence-based guideline directed medical therapies (GDMT) proven to improve HF morbidity and mortality, there remains significant clinical inertia to optimizing HF patients on GDMT. Only a minority of HF patients are prescribed on all four classes of GDMT. To bridge the gap between the vulnerable population of HF patients and lifesaving GDMT, HF implementation is of increasing importance. HF implementation involves strategies and techniques to improve GDMT optimization along with other modalities to improve HF management. HF implementation meets patients where they are, including at the time of acute decompensation in the inpatient setting, at the vulnerable discharge stage, and at the chronic management stage in the outpatient setting. Inpatient HF implementation strategies include protocolized rapid titration of GDMT, site-level audit-and-feedback, virtual GDMT optimization teams, and electronic health record notifications and alerts. Discharge HF implementation strategies include education at patient and provider levels, discharge summaries, and HF transitional programs. Outpatient HF implementation strategies include digital innovations such as electronic health record utilization and mobile applications, population level strategies such as registries and clinical dashboards), changes in HF team structure and member roles, remote monitoring with implanted devices and telemonitoring, and hospital at home care model. With a growing population of HF patients, there is an increasing need for novel and creative HF implementation and monitoring methods.

Background: The STRONG-HF trial demonstrated substantial reductions in the composite of mortality and morbidity over 6 months among hospitalized heart failure patients who were randomized to intensive guideline-directed medical therapy (GDMT) optimization compared to usual care. Whether an intensive GDMT optimization program would be cost-effective for patients with heart failure with reduced ejection fraction (HFrEF) is unknown. Methods: Using a 2-state Markov model we evaluated the effect of an intensive GDMT optimization program on hospitalized patients with HFrEF. Two population models were created to simulate this intervention, a "Clinical Trial" model, based off the participants in the STRONG-HF trial and a "Real-World" model, based off the Get With The Guidelines-HF Registry of patients admitted with worsening HF. We then modeled the effect of a 6-month intensive triple therapy GDMT optimization program comprised of cardiologists, clinical pharmacists, and registered nurses. Hazard ratios from the intervention arm of the STRONG-HF trial were applied to both populations models to simulate clinical and financial outcomes of an intensive GDMT optimization program from a United States healthcare sector perspective with a lifetime time horizon. Optimal quadruple GDMT use was also modeled. Results: An intensive GDMT optimization program was extremely cost-effective with incremental cost-effectiveness ratios

To evaluate the impact of age and COVID-19 variant time period on morbidity and mortality among those hospitalized with COVID-19.Patients from the American Heart Association's Get With The Guidelines COVID-19 cardiovascular disease registry (January 20, 2020-February 14, 2022) were divided into groups based on whether they presented during periods of wild type/alpha, delta, or omicron predominance. They were further subdivided by age (young: 18-40 years; older: more than 40 years), and characteristics and outcomes were compared.The cohort consisted of 45,421 hospitalized COVID-19 patients (wild type/alpha period: 41,426, delta period: 3349, and omicron period: 646). Among young patients (18-40 years), presentation during delta was associated with increased odds of severe COVID-19 (OR, 1.6; 95% CI, 1.3-2.1), major adverse cardiovascular events (MACE) (OR, 1.8; 95% CI, 1.3-2.5), and in-hospital mortality (OR, 2.2; 95% CI, 1.5-3.3) when compared with presentation during wild type/alpha. Among older patients (more than 40 years), presentation during delta was associated with increased odds of severe COVID-19 (OR, 1.2; 95% CI, 1.1-1.3), MACE (OR, 1.5; 95% CI, 1.4-1.7), and in-hospital mortality (OR, 1.4; 95% CI, 1.3-1.6) when compared with wild type/alpha. Among older patients (more than 40 years), presentation during omicron associated with decreased odds of severe COVID-19 (OR, 0.7; 95% CI, 0.5-0.9) and in-hospital mortality (OR, 0.6; 95% CI, 0.5-0.9) when compared with wild type/alpha.Among hospitalized adults with COVID-19, presentation during a time of delta predominance was associated with increased odds of severe COVID-19, MACE, and in-hospital mortality compared with presentation during wild type/alpha. Among older patients (aged more than 40 years), presentation during omicron was associated with decreased odds of severe COVID-19 and in-hospital mortality compared with wild type/alpha.

Asian American/Pacific Islanders (AAPIs) and Hispanics are growing minority United States populations, but are poorly represented in the cardiovascular literature. This study examines guideline adherence and outcomes in AAPIs and Hispanics compared with non-Hispanic Whites (NHWs) in a quaternary care center after inpatient percutaneous coronary intervention (PCI). The primary end points were inpatient post-PCI bleed, heart failure, cardiogenic shock, and all-cause mortality, whereas the secondary end point was the prescription rate of post-PCI guideline-directed medical therapy including aspirin, statins, P2Y12 receptor blockers, and cardiopulmonary rehabilitation. Intergroup differences were assessed through analysis of variance or two-way chi-square tests, and the association of race with binary outcomes was examined through logistic regression with NHW as the reference group. Compared with NHW, AAPIs, and Hispanics had higher odds of diabetes mellitus, and AAPIs had higher odds of hypertension and being on dialysis. Hispanics had higher odds of post-PCI mortality versus NHW, both in acute coronary syndrome (odds ratio [OR] 2.04, p = 0.03) and elective PCI (OR 2.51, p = 0.04). AAPI also trended toward higher mortality than NHW in both categories. AAPIs were found to have higher odds of statin prescription (OR 1.91, p = 0.04). Hispanics had lower odds of ticagrelor prescription versus NHW (OR 0.65, p = 0.04), and AAPIs trended toward such. No differences were found for cardiopulmonary rehabilitation prescriptions in groups. This study suggests that despite quality improvement efforts, disparities remain in postprocedural outcomes in minority groups in comparison with NHW.

BackgroundIn 2020, the Veterans' Affairs (VA) healthcare system deployed a heart failure (HF) dashboard for use nationally. The initial version was notably imprecise and unreliable for the identification of HF subtypes. We describe the development and subsequent optimization of the VA national HF dashboard.Materials and methodsThis study describes the stepwise process for improving the accuracy of the VA national HF dashboard, including defining the initial dashboard, improvement of case definitions, utilization of natural language processing for patient identification, and incorporation of an imaging quality hierarchy model. Optimization further included evaluating whether to require concurrent ICD-codes for inclusion in the dashboard and assessing various imaging modalities for patient characterization.ResultsThrough multiple rounds of optimization, the dashboard accuracy (defined as the proportion of true results to the total population) was improved from 54.1% to 89.2% for the identification of HF with reduced ejection fraction (HFrEF) and from 53.9% to 88.0% for the identification of HF with preserved ejection fraction (HFpEF). To align with current guidelines, HF with mildly reduced ejection fraction (HFmrEF) was added to the dashboard output with 88.0% accuracy.ConclusionsThe inclusion of an imaging quality hierarchy model and natural language processing algorithm improved the accuracy of the VA national HF dashboard. The revised dashboard informatics algorithm has higher utilization rates and improved reliability for population health management.

BackgroundThe burden of heart failure is growing. Guideline-directed medical therapies (GDMT) reduce adverse outcomes in heart failure with reduced ejection fraction (HFrEF). Whether there is geographic variation in HFrEF quality of care is not well described.ObjectivesThis study evaluated variation nationally for prescription of GDMT within the Veterans Health Administration.MethodsA cohort of Veterans with HFrEF had their address linked to hospital referral regions (HRRs). GDMT prescription was defined using pharmacy data between July 1, 2020, and July 1, 2021. Within HRRs, we calculated the percentage of Veterans prescribed GDMT and a composite GDMT z-score. National choropleth maps were created to evaluate prescription variation. Associations between GDMT performance and demographic characteristics were evaluated using linear regression.ResultsMaps demonstrated significant variation in the HRR composite score and GDMT prescriptions. Within HRRs, the prescription of beta-blockers to Veterans was highest with a median of 80% (IQR: 77.3%-82.2%) followed by angiotensin-converting enzyme inhibitor/angiotensin receptor blocker/angiotensin receptor-neprilysin inhibitors (69.3%; IQR: 66.4%-72.1%), sodium-glucose cotransporter 2 inhibitors (10.3%; IQR: 7.7%-12.8%), mineralocorticoid receptor antagonists (29.2%; IQR: 25.8%-33.9%), and angiotensin receptor-neprilysin inhibitors (12.2%; IQR: 8.6%-15.3%). HRR composite GDMT z-scores were inversely associated with the HRR median Gini coefficient (R = -0.13; P = 0.0218) and the percentage of low-income residents (R = -0.117; P = 0.0413).ConclusionsWide geographic differences exist for HFrEF care. Targeted strategies may be required to increase GDMT prescription for Veterans in lower-performing regions, including those affected by income inequality and poverty.

BackgroundHeart failure is a prevailing diagnosis of hospitalization and readmission within 6 months, and nearly a quarter of these patients die within a year. Guideline-directed medication therapies reduce risk of mortality by 73% over 2 years; however, the implementation of these therapies to their target dose in clinical practice continues to be challenging. In 2020, the Veterans Affairs (VA) Health Care System developed a HF dashboard to monitor and improve outpatient HF management. The DASH-HF (Dashboard Activated Services and Telehealth for Heart Failure) study is a randomized, pragmatic clinical trial to evaluate proactive dashboard-directed telehealth clinics to improve the use and dosing of guideline-directed medication therapy for patients with heart failure with reduced ejection fraction not on optimal guideline-directed medication therapy within the VA.MethodsThree hundred veterans with heart failure with reduced ejection fraction met inclusion criteria with an optimization potential score (OPS) of 5 or less out of 10, representing nonoptimal guideline-directed medication therapy. The primary outcome was a composite score of guideline-directed medical therapy, the OPS, 6 months after the end of the intervention. Secondary outcomes included active prescriptions for each individual guideline-directed medical therapy class, HF-related hospitalizations, deaths, and clinician time per patient during the intervention clinics.ResultsThere was no significant difference between the intervention arm and usual care group in the primary outcome (OPS, 2.9; SD=2.1 versus OPS, 2.6, SD=2.1); adjusted mean difference 0.3 (95% CI, -0.1 to 0.7) or in the prespecified secondary outcomes for hospitalization and all-cause mortality for the intervention of proactive dashboard-based clinics.ConclusionsA dashboard-based clinic intervention did not improve the OPS or secondary outcomes of hospitalization and all-cause mortality. There remains a larger opportunity to better target patients and provide more intensive follow-up to further evaluate the utility of proactive dashboard-based clinics for HF management and quality improvement.RegistrationURL: https://www.Clinicaltrialsgov; Unique identifier: NCT05001165.

Heart failure remains a huge societal concern despite medical advancement, with an annual direct cost of over $30 billion. While guideline-directed medical therapy (GDMT) is proven to reduce morbidity and mortality, many eligible patients with heart failure with reduced ejection fraction (HFrEF) are not receiving one or more of the recommended medications, often due to suboptimal initiation and titration in the outpatient setting. Hospitalization serves as a key point to initiate and titrate GDMT. Four evidence-based therapies have clinical benefit within 30 days of initiation and form a crucial foundation for HFrEF therapy: renin-angiotensin-aldosterone system inhibitors with or without a neprilysin inhibitor, β-blockers, mineralocorticoid-receptor-antagonists, and sodium-glucose cotransporter-2 inhibitors. The authors present a practical guide for the implementation of these four pillars of GDMT during a hospitalization for acute heart failure.

BackgroundHeart failure with reduced ejection fraction (HFrEF) is one of the most costly and deadly chronic disease states. The cost effectiveness of a comprehensive quadruple therapy regimen for HFrEF has not been studied.ObjectivesThe authors sought to determine the cost-effectiveness of quadruple therapy comprised of beta-blockers, mineralocorticoid receptor antagonists, angiotensin receptor-neprilysin inhibitors, and sodium glucose cotransporter-2 inhibitors vs regimens composed of only beta-blockers, angiotensin-converting enzyme inhibitors, and mineralocorticoid receptor antagonists (triple therapy), and angiotensin-converting enzyme inhibitors and beta-blockers (double therapy).MethodsUsing a 2-state Markov model, the authors performed a cost-effectiveness study using simulated populations of 1,000 patients with HFrEF based on the participants in the PARADIGM-HF (Prospective comparison of ARNI with ACEI to Determine Impact on Global Mortality and morbidity in Heart Failure) trial and compared them by treatment strategy (quadruple therapy vs triple and double therapy) from a United States health care system perspective. The authors also performed 10,000 probabilistic simulations.ResultsTreatment with quadruple therapy resulted in an increase of 1.73 and 2.87 life-years compared with triple therapy and double therapy, respectively, and an increase in quality-adjusted life-years of 1.12 and 1.85 years, respectively. The incremental cost-effectiveness ratios of quadruple therapy vs triple therapy and double therapy were $81,000 and $51,081, respectively. In 91.7% and 99.9% of probabilistic simulations quadruple therapy had an incremental cost-effectiveness ratio of

BackgroundThe sex differences in use, safety outcomes, and health-care resource use of patients with pulmonary embolism (PE) undergoing percutaneous pulmonary artery thrombectomy are not well characterized.Research questionWhat are the sex differences in outcomes for patients diagnosed with PE who undergo percutaneous pulmonary artery thrombectomy?Study design and methodsThis retrospective cross-sectional study used national inpatient claims data to identify patients in the United States with a discharge diagnosis of PE who underwent percutaneous thrombectomy between January 2016 and December 2018. We evaluated the demographics, comorbidities, safety outcomes (in-hospital mortality), and health-care resource use (discharge to home, length of stay, and hospital charges) of patients with PE undergoing percutaneous thrombectomy.ResultsAmong 1,128,904 patients with a diagnosis of PE between 2016 and 2018, 5,160 patients (0.5%) underwent percutaneous pulmonary artery thrombectomy. When compared with male patients, female patients showed higher procedural bleeding (16.9% vs 11.2%; P < .05), required more blood transfusions (11.9% vs 5.7%; P < .05), and experienced more vascular complications (5.0% vs 1.5%; P < .05). Women experienced higher in-hospital mortality (16.9% vs 9.3%; adjusted OR, 1.9; 95% CI, 1.2-3.0; P = .003) when compared with men. Although length of stay and hospital charges were similar to those of men, women were less likely to be discharged home after surviving hospitalization (47.9% vs 60.3%; adjusted OR, 0.7; 95% CI, 0.50-0.99; P = .04).InterpretationIn this large nationwide cohort, women with PE who underwent percutaneous thrombectomy showed higher morbidity and in-hospital mortality compared with men.

Introduction: In patients with heart failure with reduced ejection fraction (HFrEF), use of guideline directed medical therapies (GDMT) reduces mortality. Whether there is geographic variation in GDMT prescribing is not well-characterized. Hypothesis: We assessed the hypothesis that there is wide geographic variation nationally within the Veterans Affairs (VA) healthcare system for the receipt of GDMT. Methods: We linked the primary residence address of a cohort of Veterans with HFrEF receiving care at VA facilities (n=178,856) to hospital referral regions (HRRs). Using VA and non-VA pharmacy data between July 1, 2020 and July 1, 2021, we defined receipt of GDMT. For each HRR, we calculated the percentage of eligible Veterans that were prescribed each class of GDMT and a composite GDMT z-score. Lastly, we constructed national choropleth maps to depict HRR geographic variation in composite z-scores and prescription of each class of GDMT. Results: There was significant variation in individual GDMT class prescription and composite score across HRRs as shown in choropleth maps ( Figure) . Within HRRs, beta-blocker prescription was highest, with a median 80% of Veterans (interquartile range [IQR] 77.3% to 82.2%), afterload-reducing agents including angiotensin converting enzyme inhibitor / angiotensin receptor blocker / angiotensin receptor-neprilysin inhibitors (ARNI) 69.3% (IQR 66.4% to 72.1%), mineralocorticoid receptor antagonists (MRA) 29.2% (IQR 25.8% to 33.9%), sodium-glucose cotransporter 2 inhibitors (SGLT2I) 10.3% (IQR 7.7% to 12.8%), and ARNI 12.2% (IQR 8.6% to 15.3%). HRRs with the highest and lowest composite scores were often found in the same U.S. Census Regions. Conclusions: In conclusion, wide geographic disparities are present for GDMT prescribing to Veterans across HRRs. Veteran receipt of ARNI, SGLT2I, and MRA is low nationwide. Targeted approaches may be necessary to improve GDMT prescription for Veterans in lower performing HRRs.

Introduction: Asian-American/Pacific Islanders (AAPIs) and Hispanics are two of the most rapidly growing minorities, but both are poorly represented in the cardiovascular literature. In light of national quality improvement efforts to ensure adherence to cardiovascular therapy guidelines, this study examines guideline adherence and outcomes in AAPIs and Hispanics compared to non-Hispanic Whites (NHW) in a quaternary care center after percutaneous coronary intervention (PCI). Methods: 1,896 AAPI, Hispanics, and NHW adults from February 28, 2012 to December 30, 2020 who underwent emergent or elective PCI were included. The primary endpoint was the prescription of post-PCI guideline-directed medical therapy including aspirin, statins, P2Y12 receptor blockers, and cardiopulmonary rehabilitation. Secondary endpoints included comorbidity burden, post-PCI morbidity and mortality, and prior PCI. Analyses were adjusted for age, sex, and insurance type. Results: Hispanics had the lowest median age and the highest rates of government insurance. Hispanics had lower odds of either ACE inhibitor or ARB prescription versus NHW (OR = 0.75, p = 0.03). Odds of ticagrelor prescriptions were lower for both Hispanics (OR = 0.56, p = 0.01) and AAPIs (OR = 0.62, p = 0.02) versus NHW. However, odds of clopidogrel prescriptions were higher for Hispanics than NHW (OR = 1.57, p = 0.01), while AAPIs trended towards the same (OR = 1.42, p = 0.05). No differences were found for statin or cardiopulmonary rehabilitation prescriptions. AAPIs and Hispanics had significantly higher risks of diabetes (OR = 2.28 and 1.8 respectively, p < 0.01) and of being on dialysis (OR = 2.25 and 2.52 respectively, p < 0.01) than NHW. AAPIs also had higher odds of hypertension than NHW (OR = 1.51, p = 0.01). Hispanics had significantly higher risk of post-PCI mortality versus NHW (OR = 2.12, p < 0.01). Conclusions: AAPIs and Hispanics had lower odds of ticagrelor prescription than NHW, and Hispanics had higher odds of clopidogrel prescription. Hispanics also had higher odds of mortality post-PCI. Further, AAPIs and Hispanics had higher comorbidity burdens. This study suggests that despite quality improvement efforts, work remains to be done to narrow health disparities.

Introduction: The COVID-19 pandemic has caused significant cardiovascular (CV) morbidity and mortality. Using a national registry, we evaluate the impact of age and variant on CV outcomes across the three main coronavirus waves. Methods: Using the AHA’s COVID-19 CV Disease Registry, we divided patients hospitalized with COVID-19 into three groups based on dominant variant at the time of admission (Alpha, Delta, Omicron). We further stratified patients based on age (young: 18-40, older: >40 years). Using adjusted logistic regression, we compared rates of major adverse cardiovascular events (MACE: new onset heart failure, myocardial infarction, stroke, or death) and in-patient mortality between the groups. Results: There were 41,426 patients in the alpha wave (young: 5,585, older: 35,841), 3,349 patients in the delta wave (young: 690, older: 2,659), and 646 patients in the omicron wave (young: 213, older: 433). The cohort’s median (25 th -75 th %ile) age was 63 (50-75) years. 46.8% of the patients were female. Rates of MACE in the Alpha, Delta, and Omicron waves were 20.8%, 23.6%, and 15.5%. Rates of death were 14.0%, 14.8% and 6.0%, respectively. Compared to alpha, patients presenting during delta had increased odds of MACE and death (OR: 1.57 [1.42-1.73] and OR: 1.49 [1.34-1.66]). Patients presenting during omicron had decreased odds of death (OR: 0.6 [0.43-0.84]) and similar odds of MACE compared to alpha. When stratifying by age, both young and older patients presenting during delta had increased odds of MACE and death when compared to alpha (Fig 1A). When compared to young patients, older patients had increased odds of MACE in all three waves (Fig 1B). Conclusions: Patients had increased odds of MACE and death during delta compared to alpha. Compared to young patients, older patients had increased odds of MACE across all three waves. These findings help elucidate the differential impact of age and variant on cardiovascular outcomes among those hospitalized with COVID-19.

BackgroundThe United States lacks a timely and accurate nationwide surveillance system for acute ischemic stroke (AIS). We use the Get With The Guidelines-Stroke registry to apply poststratification survey weights to generate national assessment of AIS epidemiology, hospital care quality, and in-hospital outcomes.MethodsClinical data from the Get With The Guidelines-Stroke registry were weighted using a Bayesian interpolation method anchored to observations from the national inpatient sample. To generate a US stroke forecast for 2019, we linearized time trend estimates from the national inpatient sample to project anticipated AIS hospital volume, distribution, and race/ethnicity characteristics for the year 2019. Primary measures of AIS epidemiology and clinical care included patient and hospital characteristics, stroke severity, vital and laboratory measures, treatment interventions, performance measures, disposition, and clinical outcomes at discharge.ResultsWe estimate 552 476 patients with AIS were admitted in 2019 to US hospitals. Median age was 71 (interquartile range, 60-81), 48.8% female. Atrial fibrillation was diagnosed in 22.6%, 30.2% had prior stroke/transient ischemic attack, and 36.4% had diabetes. At baseline, 46.4% of patients with AIS were taking antiplatelet agents, 19.2% anticoagulants, and 46.3% cholesterol-reducers. Mortality was 4.4%, and only 52.3% were able to ambulate independently at discharge. Performance nationally on AIS achievement measures were generally higher than 95% for all measures but the use of thrombolytics within 3 hours of early stroke presentations (81.9%). Additional quality measures had lower rates of receipt: dysphagia screening (84.9%), early thrombolytics by 4.5 hours (79.7%), and statin therapy (80.6%).ConclusionsWe provide timely, reliable, and actionable US national AIS surveillance using Bayesian interpolation poststratification weights. These data may facilitate more targeted quality improvement efforts, resource allocation, and national policies to improve AIS care and outcomes.

Sodium-glucose cotransporter-2 inhibitors (SGLT2i) are a recent addition to the pillars of medical therapy for heart failure (HF) with reduced ejection fraction, all of which improve quality of life, morbidity, and mortality. These benefits are evident within the first 30 days of initiation. This review discusses the rationale for SGLT2i initiation in simultaneous or in rapid sequence with other guideline-directed medical therapy (GDMT). We also discuss SGLT2i use and early benefits in HF patients with an ejection fraction greater than 40%.

BackgroundGaps in the receipt and dosing of guideline-directed medical therapy (GDMT) persist for patients with heart failure with reduced ejection fraction (HFrEF) [1]. In 2020, the Veterans Affairs (VA) developed a heart failure (HF) specific population dashboard to monitor care quality and performance on standard HFrEF performance measures [2].MethodsThe Dashboard Activated Services and Telehealth for HF (DASH-HF) study is a pragmatic randomized quality improvement study designed to evaluate the utility of proactive population management clinics using the VA's HF dashboard to optimize GDMT for patients with HFrEF. Panel management telemedicine clinics incorporated multidisciplinary clinicians to perform chart review and impromptu telephone encounters to evaluate current HFrEF management and opportunities to optimize GDMT. The study will evaluate the efficacy of proactive panel management to usual care at 6 months as quantified by the GDMT optimization potential score. Secondary outcomes include hospitalizations, mortality, and clinician time per intervention. The study completed enrollment and randomization of 300 participants. The intervention was performed from September to December 2021.ConclusionDASH-HF will contribute to the literature by evaluating use of the existing VA dashboard to identify HF patients with the lowest adherence to GDMT and proactively target this group for the intervention.Registrationhttps://clinicaltrials.gov/. Unique identifier: NCT05001165.

BackgroundWith rising United States health care expenditure, estimating current spending for patients with heart failure (HF) informs the value of preventative health interventions.ObjectivesThe purpose of this study was to estimate current health care expenditure growth for patients with HF in the United States.MethodsThe authors pooled MEPS (Medical Expenditure Panel Survey) data from 2009-2018 to calculate total HF-related expenditure across clinical settings in the United States. A 2-part model adjusted for demographics, comorbidities, and year was used to estimate annual mean and incremental expenditures associated with HF.ResultsIn the United States, an average of $28,950 (2018 inflation-adjusted dollars) is spent per year for health care-related expenditure for individuals with HF compared with $5,727 for individuals without HF. After adjusting for demographics and comorbidities, a diagnosis of HF was associated with $3,594 in annual incremental expenditure compared with those without HF. HF-related expenditure increased from $26,864 annual per person in 2009-2010 to $32,955 in 2017-2018, representing a 23% rise over 10 years. In comparison, expenditure on myocardial infarction, type 2 diabetes mellitus, and cancer grew by 16%, 28%, and 16%, respectively. Most of the cost was related to hospitalization: $12,569 per year. Outpatient office-based care and prescription medications saw the greatest growth in cost over the period, 41% and 24%, respectively. Estimated incremental national expenditure for HF per year was $22.3 billion; total annual expenditure for adults with HF was $179.5 billion.ConclusionsHF is a costly condition for which expenditure is growing faster than that of other chronic conditions.

BackgroundCOVID-19 rapidly accelerated the implementation of telemedicine in U.S. Department of Veterans Affairs (VA) specialty care clinics. This mixed-methods study was conducted at a VA medical center to understand the use of telemedicine, and the barriers and facilitators to its implementation, in cardiology outpatient clinics.MethodsQuantitative analyses modeled monthly trends of telemedicine use over 24-months (March 2019-March 2021) with segmented logistic regression and adjusted for socio-demographic predictors of patient-level telemedicine use. Qualitative interviews were conducted (July-October 2020) with eight cardiology clinicians.ResultsAt the onset of COVID-19, likelihood of telemedicine use was ∼12 times higher than it was pre-COVID-19 (p

ObjectiveTo evaluate the adoption and discontinuation of four broadly used non-pharmaceutical interventions on shifts in the covid-19 burden among US states.DesignRetrospective, observational cohort study.SettingUS state data on covid-19 between 19 January 2020 and 7 March 2021.ParticipantsUS population with a diagnosis of covid-19.Main outcome measuresEmpirically derived breakpoints in case and mortality velocities (ie, rate of change) were used to identify periods of stable, decreasing, or increasing covid-19 burden. Associations between adoption of non-pharmaceutical interventions and subsequent decreases in case or death rates were estimated by use of generalised linear models accounting for weekly variability across US states. State level case and mortality counts per day were obtained from the Covid-19 Tracking Project. State level policies on non-pharmaceutical interventions included stay-at-home orders, indoor public gathering bans (mild >10 or severe ≤10 people), indoor restaurant dining bans, and public mask mandates. National policies were not included in statistical models.Results28 602 830 cases and 511 899 deaths were recorded during the study. Odds of a reduction in covid-19 case velocity increased for stay-at-home orders (odds ratio 2.02, 95% confidence interval 1.63 to 2.52), indoor dining bans (1.62, 1.25 to 2.10), public mask mandates (2.18, 1.47 to 3.23), and severe indoor public gathering bans (1.68, 1.31 to 2.16) in univariate analysis. In mutually adjusted models, odds remained elevated for orders to stay at home (adjusted odds ratio 1.47, 95% confidence interval 1.04 to 2.07) and public mask mandates (2.27, 1.51 to 3.41). Stay-at-home orders (odds ratio 2.00, 95% confidence interval 1.53 to 2.62; adjusted odds ratio 1.89, 95% confidence interval 1.25 to 2.87) was also associated with a greater likelihood of decrease in death velocity in unadjusted and adjusted models.ConclusionsState level non-pharmaceutical interventions used in the US during the covid-19 pandemic, in particular stay-at-home orders, were associated with a decreased covid-19 burden.

BackgroundTelemedicine and telemonitoring have become invaluable tools in managing chronic diseases, such as heart failure (HF). With the recent pandemic, telemedicine has become the preferred method of providing consultative care.Local problemThis rapid paradigm shift from face-to-face (F2F) consultations to telemedicine required a collaborative approach for successful implementation while maintaining quality of care. The processes for conducting a telemedicine visit for HF patient are not well defined or outlined.MethodUsing a collaborative practice model and nurse practitioner led program, technology was leveraged to manage the high-risk HF population using virtual care (consultation via phone or video-to-home) with two aims: first to provide ongoing HF care using available telemedicine technologies or F2F care when necessary and, second, to evaluate and direct those needing urgent/emergent level of care to emergency department (ED).InterventionThe process was converted into an intuitive algorithm that describes essential elements and team roles necessary for execution of a successful HF consultation.ResultsFollowing the algorithm, nurse practitioners conducted 132 visits, yielding 100% success in the conversion of F2F appointments to telemedicine, with 3 patients referred to ED for care. The information obtained through telemedicine consultation accurately informed decision for ED evaluation with resultant admission.ConclusionCollaborative team-based approach delineated in the algorithm facilitated successful virtual consultations for HF patients and accurately informed decisions for higher level of care.

BackgroundLack of consensus remains about factors that may be associated with high resource use (HRU) in adult cardiac surgical patients. This study aimed to identify patient-related, hospital, and perioperative characteristics associated with HRU admissions involving elective cardiac operations.MethodsData from the National Inpatient Sample was used to identify patients who underwent coronary artery bypass graft, valve replacement, and valve repair operations between 2005 and 2016. Admissions with HRU were defined as those in the highest decile for total hospital costs. Multivariable regressions were used to identify factors associated with HRU.ResultsAn estimated 1,750,253 hospitalizations coded for elective cardiac operations. The median hospitalization cost was $34,700 (interquartile range, $26,800- to $47,100), with the HRU (N = 175,025) cutoff at $66,029. Although HRU patients comprised 10% of admissions, they accounted for 25% of cumulative costs. On multivariable regression, patient-related characteristics predictive of HRU included female sex, older age, higher comorbidity burden, non-White race, and highest income quartile. Hospital factors associated with HRU were low-volume hospitals for both coronary artery bypass graft and valvular operations. Among postoperative outcomes, mortality, infectious complications, extracorporeal membrane oxygenation use, and hospitalization for more than 8 days were associated with greater odds of HRU.ConclusionsIn this nationwide study of elective cardiac surgical patients, several important patient-related and hospital factors, including patients' race, comorbidities, postoperative infectious complications, and low hospital operative volume were identified as predictors of HRU. These highly predictive factors may be used for benchmarking purposes and improvement in surgical planning.

BackgroundAcute myocardial infarction (AMI) complicated by cardiogenic shock (CS) is associated with significant morbidity and mortality.MethodsWe provide an overview of previously conducted studies on the use of mechanical circulatory support (MCS) devices in the treatment of AMI-CS and difficulties which may be encountered in conducting such trials in the United States.ResultsWell powered randomized control trials are difficult to conduct in a critically ill patient population due to physician preferences, perceived lack of equipoise and challenges obtaining informed consent.ConclusionsWith growth in utilization of MCS devices in patients with AMI-CS, efforts to perform well-powered, randomized control trials must be undertaken.

BACKGROUND: Non-pharmaceutical interventions (NPIs) are mitigation strategies used to reduce the spread of transmissible diseases. The relative effectiveness of specific NPIs remains uncertain. METHODS: We used state-level Coronavirus disease 2019 (COVID-19) case and mortality data between January 19, 2020 and March 7, 2021 to model NPI policy effectiveness. Empirically derived breakpoints in case and mortality velocities were used to identify periods of stable, decreasing, or increasing COVID-19 burden. The associations between NPI adoption and subsequent decreases in case or death velocities were estimated using generalized linear models accounting for weekly variability shared across states. State-level NPI policies included: stay at home order, indoor public gathering ban (mild >10 or severe ≤10), indoor restaurant dining ban, and public mask mandate. RESULTS: 28,602,830 cases and 511,899 deaths were recorded. The odds of a decrease in COVID-19 case velocity were significantly elevated for stay at home (OR 2.02, 95% CI 1.63-2.52), indoor dining ban (OR 1.62, 95% CI 1.25-2.10), public mask mandate (OR 2.18, 95% CI 1.47-3.23), and severe gathering ban (OR 1.68, 95% CI 1.31-2.16). In mutually adjusted models, odds remained elevated for stay at home (AOR 1.47, 95% CI 1.04-2.07) and public mask mandate (AOR = 2.27, 95% CI 1.51-3.41). Stay at home (OR 2.00, 95% CI 1.53-2.62; AOR 1.89, 95% CI 1.25-2.87) was also associated with greater likelihood of decrease in death velocity in unadjusted and adjusted models. CONCLUSIONS: NPIs employed in the U.S. during the COVID-19 pandemic, most significantly stay at home orders, were associated with decreased COVID-19 burden.

BackgroundAt the onset of the COVID-19 pandemic, there was a rapid increase in the use of telehealth services at the US Department of Veterans Affairs (VA), which was accelerated by state and local policies mandating stay-at-home orders and restricting nonurgent in-person appointments. Even though the VA was an early adopter of telehealth in the late 1990s, the vast majority of VA outpatient care continued to be face-to-face visits through February 2020.ObjectiveWe compared telehealth service use at a VA Medical Center, Greater Los Angeles across 3 clinics (primary care [PC], cardiology, and home-based primary care [HBPC]) 12 months before and 12 months after the onset of COVID-19 (March 2020).MethodsWe used a parallel mixed methods approach including simultaneous quantitative and qualitative approaches. The distribution of monthly outpatient and telehealth visits, as well as telephone and VA Video Connect encounters were examined for each clinic. Semistructured telephone interviews were conducted with 34 staff involved in telehealth services within PC, cardiology, and HBPC during COVID-19. All audiotaped interviews were transcribed and analyzed by identifying key themes.ResultsPrior to COVID-19, telehealth use was minimal at all 3 clinics, but at the onset of COVID-19, telehealth use increased substantially at all 3 clinics. Telephone was the main modality of patient choice. Compared with PC and cardiology, video-based care had the greatest increase in HBPC. Several important barriers (multiple steps for videoconferencing, creation of new scheduling grids, and limited access to the internet and internet-connected devices) and facilitators (flexibility in using different video-capable platforms, technical support for patients, identification of staff telehealth champions, and development of workflows to help incorporate telehealth into treatment plans) were noted.ConclusionsTechnological issues must be addressed at the forefront of telehealth evolution to achieve access for all patient populations with different socioeconomic backgrounds, living situations and locations, and health conditions. The unprecedented expansion of telehealth during COVID-19 provides opportunities to create lasting telehealth solutions to improve access to care beyond the pandemic.

ImportancePrevious studies have described the secular trends of overall heart failure (HF) hospitalizations, but the literature describing the national trends of unique index hospitalizations and readmission visits for the primary management of HF is lacking.ObjectivesTo examine contemporary overall and sex-specific trends of unique primary HF (grouped by number of visits for the same patient in a given year) and 30-day readmission visits in a large national US administrative database from 2010 to 2017.Design, setting, and participantsThis cohort study used data from all adult hospitalizations in the Nationwide Readmission Database from January 1, 2010, to December 31, 2017, with a primary diagnosis of HF. Data analyses were conducted from March to November 2020.ExposuresAdmission for a primary diagnosis of HF at discharge.Main outcomes and measuresUnique and overall hospitalizations with a primary diagnosis of HF and postdischarge readmissions. Unique primary HF hospitalizations were grouped by number of visits for the same patient in a given year.ResultsThere were 8 273 270 primary HF hospitalizations with a single primary HF admission present in 5 092 626 unique patients, and 1 269 109 had 2 or more HF hospitalizations. The mean age was 72.1 (95% CI, 72.0-72.3) years, and 48.9% (95% CI, 48.7-49.0) were women. The primary HF hospitalization rates per 1000 US adults declined from 4.4 in 2010 to 4.1 in 2013 and then increased from 4.2 in 2014 to 4.9 in 2017. The rates per 1000 US adults for postdischarge HF readmissions (1.0 in 2010 to 0.9 in 2014 to 1.1 in 2017) and all-cause 30-day readmissions (0.8 in 2010 to 0.7 in 2014 to 0.9 in 2017) had similar trends.Conclusions and relevanceIn this analysis of a nationally representative administrative data set, for primary HF admissions, crude rates of overall and unique patient hospitalizations declined from 2010 to 2014 followed by an increase from 2014 to 2017. Additionally, readmission visits after index HF hospitalizations followed a similar trend. Future studies are needed to verify these findings to improve policies for HF management.

ImportanceThe Centers for Medicare & Medicaid Services uses a new peer group-based payment system to compare hospital performance as part of its Hospital Readmissions Reduction Program, which classifies hospitals into quintiles based on their share of dual-eligible beneficiaries for Medicare and Medicaid. However, little is known about the association of a hospital's share of dual-eligible beneficiaries with the quality of care and outcomes for patients with heart failure (HF).ObjectiveTo evaluate the association between a hospital's proportion of patients with dual eligibility for Medicare and Medicaid and HF quality of care and outcomes.Design, setting, and participantsThis retrospective cohort study evaluated 436 196 patients hospitalized for HF using the Get With The Guidelines-Heart Failure registry from January 1, 2010, to December 31, 2017. The analysis included patients 65 years or older with available data on dual-eligibility status. Hospitals were divided into quintiles based on their share of dual-eligible patients. Quality and outcomes were analyzed using unadjusted and adjusted multivariable logistic regression models. Data analysis was performed from April 1, 2020, to January 1, 2021.Main outcomes and measuresThe primary outcome was 30-day all-cause readmission. The secondary outcomes included in-hospital mortality, 30-day HF readmissions, 30-day all-cause mortality, and HF process of care measures.ResultsA total of 436 196 hospitalized HF patients 65 years or older from 535 hospital sites were identified, with 258 995 hospitalized patients (median age, 81 years; interquartile range, 74-87 years) at 455 sites meeting the study criteria and included in the primary analysis. A total of 258 995 HF hospitalizations from 455 sites were included in the primary analysis of the study. Hospitals in the highest dual-eligibility quintile (quintile 5) tended to care for patients who were younger, were more likely to be female, belonged to racial minority groups, or were located in rural areas compared with quintile 1 sites. After multivariable adjustment, hospitals with the highest quintile of dual eligibility were associated with lower rates of key process measures, including evidence-based β-blocker prescription, measure of left ventricular function, and anticoagulation for atrial fibrillation or atrial flutter. Differences in clinical outcomes were seen with higher 30-day all-cause (adjusted odds ratio, 1.24; 95% CI, 1.14-1.35) and HF (adjusted odds ratio, 1.14; 95% CI, 1.03-1.27) readmissions in higher dual-eligible quintile 5 sites compared with quintile 1 sites. Risk-adjusted in-hospital and 30-day mortality did not significantly differ in quintile 1 vs quintile 5 hospitals.Conclusions and relevanceIn this cohort study, hospitals with a higher share of dual-eligible patients provided care with lower rates of some of the key HF quality of care process measures and with higher 30-day all-cause or HF readmissions compared with lower dual-eligibility quintile hospitals.

Abstract Background: The U.S. lacks a stroke surveillance system. This study develops a method to transform an existing registry into a nationally representative database to evaluate acute ischemic stroke care quality.Methods: Two statistical approaches were used to develop post-stratification weights for the Get With The Guidelines-Stroke registry by anchoring population estimates to the National Inpatient Sample. Post-stratification survey weights were estimated using a raking procedure and Bayesian interpolation methods. Weighting methods were adjusted to limit the dispersion of weights and make reasonable epidemiologic estimates of patient characteristics, quality of hospital care, and clinical outcomes. Standardized differences in national estimates were reported between the two post-stratification methods for anchored and non-anchored patient characteristics to evaluate estimation quality. Primary measures evaluated were patient and hospital characteristics, stroke severity, vital and laboratory measures, disposition, and clinical outcomes at discharge. Results: A total of 1,388,296 acute ischemic strokes occurred between 2012 and 2014. Raking and Bayesian estimates of clinical data not recorded in administrative databases were estimated within 5% to 10% of the margins of expected values. Median weights for the raking method were 1.386 and the weights at the 99th percentile were 6.881 with a maximum weight of 30.775. Median Bayesian weights were 1.329 and the 99th percentile weights were 11.201 with a maximum weight of 515.689. Conclusions: Leveraging existing databases with patient registries to develop post-stratification weights is a reliable approach to estimate acute ischemic stroke epidemiology and monitoring for stroke quality of care nationally. These methods may be applied to other diseases or settings to better monitor population health.