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Background: The American Heart Association's Get With The Guidelines (GWTG) has emerged as a vital resource in advancing the standards and practices of inpatient care across stroke, heart failure, coronary artery disease, atrial fibrillation, and resuscitation focus areas. The GWTG registry data have also created new opportunities for secondary use of real-world clinical data in biomedical research. Our goal was to implement a scalable database with an integrated user interface (UI) to improve GWTG data management and accessibility., Methods: The curation of registry data begins by going through a data processing and quality control pipeline programmed in Python. This pipeline includes data cleaning and record exclusion, variable derivation and unit harmonization, limited data set preparation, and documentation generation of the registry data. The database was built using PostgreSQL, and integrations between the database and the UI were built using the Django Web Framework in Python. Smaller subsets of data were created using SQLite database files for distribution purposes. Use cases of these tools are provided in the article., Results: We implemented an automated data curation pipeline, centralized database, and UI application for the American Heart Association GWTG registry data. The database and the UI are accessible through a Precision Medicine Platform workspace. As of March 2024, the database contains over 13.2 million cleaned GWTG patient records. The SQLite subsets benefit researchers by optimizing data extraction and manipulation using Structured Query Language. The UI improves accessibility for nontechnical researchers by presenting data in a user-friendly tabular format with intuitive filtering options., Conclusions: With the implementation of the GWTG database and UI application, we addressed data management and accessibility concerns despite its growing scale. We have launched tools to provide streamlined access and accessibility of GWTG registry data to all researchers, regardless of familiarity or experience in coding., Competing Interests: None.

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.

The US health care industry has broadly adopted performance and quality measures that are extracted from electronic health records and connected to payment incentives that hope to improve declining life expectancy and health status and reduce costs. While the development of a quality measurement infrastructure based on electronic health record data was an important first step in addressing US health outcomes, these metrics, reflecting the average performance across diverse populations, do not adequately adjust for population demographic differences, social determinants of health, or ecosystem vulnerability. Like society as a whole, health care must confront the powerful impact that social determinants of health, race, ethnicity, and other demographic variations have on key health care performance indicators and quality metrics. Tools that are currently available to capture and report the health status of Americans lack the granularity, complexity, and standardization needed to improve health and address disparities at the local level. In this article, we discuss the current and future state of electronic clinical quality measures through a lens of equity., Competing Interests: Disclosures Dr Shah receives consulting earnings from Novartis Pharmaceuticals, Amgen, Amarin, and Merck and research support from National Institutes of Health, Amgen, Novartis Pharmaceuticals, and Janssen. Dr Sitapati is an internal advisor for the U.S. Food and Drug Administration and acts as an unpaid consultant to nonprofit organizations the College of Healthcare Information Management Executives and the Kelee Foundation. The other authors report no conflicts.

Background Identifying actionable resuscitation practices that vary across hospitals could improve adherence to process measures or outcomes after in-hospital cardiac arrest (IHCA). We sought to examine whether hospital debriefing frequency after IHCA varies across hospitals and whether hospitals which routinely perform debriefing have higher rates of process-of-care compliance or survival. Methods We conducted a nationwide survey of hospital resuscitation practices in April of 2018, which were then linked to data from the Get With The Guidelines-Resuscitation national registry for IHCA. Hospitals were categorized according to their reported frequency of debriefing immediately after IHCA; rarely (0%-20% of all IHCA cases), occasionally (21%-80%), and frequently (81%-100%). Hospital-level rates of timely defibrillation (≤2 minutes), epinephrine administration (≤5 minutes), survival to discharge, return of spontaneous circulation, and neurologically intact survival were comparted for patients with IHCA from 2015 to 2017. Results Overall, there were 193 hospitals comprising 44 477 IHCA events. Mean patient age was 65±16, 41% were females, and 68% were of White race. Across hospitals, 84 (43.5%) rarely performed debriefings immediately after an IHCA, 82 (42.5%) performed debriefing sessions occasionally, and 27 (14.0%) performed debriefing frequently. There was no association between higher reported debriefing frequency and hospital rates of timely defibrillation and epinephrine administration. Mean hospital rates of risk-standardized survival to discharge were similar across debriefing frequency groups (rarely 25.6%; occasionally 26.0%; frequently 25.2%, P =0.72), as were hospital rates of risk-adjusted return of spontaneous circulation (rarely 72.2%; occasionally 73.0%; frequently 70.0%, P =0.06) and neurologically intact survival (rarely 21.9%, occasionally 22.2%, frequently 21.1%, P =0.75). Conclusions In a large contemporary nationwide quality improvement registry, hospitals varied widely in how often they conducted debriefings immediately after IHCA. However, hospital debriefing frequency was not associated with better adherence to timely delivery of epinephrine or defibrillation or higher rates of IHCA survival.

Background: Transcatheter aortic valve replacement (TAVR) is widely used; however, its appropriateness is unknown. We sought to investigate the appropriateness of TAVR., Methods and Results: We assigned appropriateness ratings to patients undergoing TAVR for severe aortic stenosis between October 2013 and May 2017 at 14 Japanese hospitals participating in the optimized transcatheter valvular intervention-transcatheter aortic valve implantation registry according to the US appropriate use criteria for treating severe aortic stenosis. To account for the influence of uncaptured variables on appropriate use criteria ratings, we initially assigned them to a best-case scenario where they were assumed to classify a case to the most appropriate clinical scenario and then to a worst-case scenario where assumed least appropriate. Overall proportion of TAVRs classified as appropriate, maybe appropriate, or rarely appropriate was assessed. In addition, extent of hospital-level variation in rarely appropriate procedures was evaluated. Of 2036 TAVRs (median age [25th, 75th]: 85.0 years [81.0-88.0]; 70.5% female the Society of Thoracic Surgeons Predicted Risk of Mortality score: 6.2% [4.4-8.9]), in the best-case scenario, 177 (8.7%) were not successfully mapped, and 1580 (77.6%) were classified as appropriate, 180 (8.8%) as maybe appropriate, 99 (4.9%) as rarely appropriate, respectively. In the worst-case scenario, the rate of rarely appropriate increased to 6.8%. The majority of rarely appropriate TAVRs was performed in patients with moderate to severe dementia (defined as mini-mental status examination of ≤17), bicuspid aortic valve, or anticipated life expectancy <1 year. There was substantial variation in the proportion of rarely appropriate TAVR across hospitals (median rate of rarely appropriate: 4.9% [3.8-6.6] in the best-case scenario, P <0.001; 6.5% [5.6-8.6] in the worst-case scenario, P <0.001)., Conclusions: In clinical practice, the proportion of rarely appropriate TAVRs ranged from 4.9% to 6.8% with substantial institutional variation. Our study elucidates common clinical scenarios deemed rarely appropriate and clarifies the potential targets of quality improvement. Registration: URL: https://www.umin.ac.jp/ctr/index.htm. Unique identifier: UMIN000020423.

Background: Medicare patients with coronary artery disease (CAD) have been a significant focus of value-based payment programs for outpatient practices. Physicians and policymakers, however, have voiced concern that value-based payment programs may penalize practices that serve vulnerable populations. This study evaluated whether outpatient practices that serve socioeconomically disadvantaged populations have worse CAD outcomes, and if this reflects the delivery of lower-quality care or rather, patient and community factors beyond the care provided by physician practices., Methods and Results: Retrospective cohort study of Medicare fee-for-service patients ≥65 years with CAD at outpatient practices participating in the the Practice Innovation and Clinical Excellence registry from January 1, 2010 to January 1, 2015. Outpatient practices were stratified into quintiles by the proportion of most disadvantaged patients-defined by an area deprivation score in the highest 20% nationally-served at each practice site. Prescription of guideline recommended therapies for CAD as well as clinical outcomes (emergency department presentation for chest pain, hospital admission for unstable angina or acute myocardial infarction [AMI], 30-day readmission after AMI, and 30-day mortality after AMI) were evaluated by practice-level socioeconomic disadvantage with hierarchical logistic regression models, using practices serving the fewest socioeconomically disadvantaged patients as a reference. The study included 453 783 Medicare fee-for-service patients ≥65 years of age with CAD (mean [SD] age, 75.3 [7.7] years; 39.7% female) cared for at 271 outpatient practices. At practices serving the highest proportion of socioeconomically disadvantaged patients (group 5), compared with practices serving the lowest proportion (group 1), there was no significant difference in the likelihood of prescription of antiplatelet therapy (odds ratio [OR], 0.94 [95% CI, 0.69-1.27]), β-blocker therapy if prior myocardial infarction or left ventricular ejection fraction <40% (OR, 0.97 [95% CI, 0.69-1.35]), ACE (angiotensin-converting enzyme) inhibitor or angiotensin receptor blocker if left ventricular ejection fraction <40% and/or diabetes mellitus (OR, 0.93 [95% CI, 0.74-1.19]), statin therapy (OR, 0.88 [95% CI, 0.68-1.14]), or cardiac rehabilitation (OR, 0.45 [95% CI, 0.20-1.00]). Patients cared for at the most disadvantaged-serving practices (group 5) were more likely to be admitted for unstable angina (adjusted OR, 1.46 [95% CI, 1.04-2.05]). There was no significant difference in the likelihood of emergency department presentation for chest pain or hospital admission for AMI between practices. Thirty day mortality rates after AMI were higher among patients at the most disadvantaged-serving practices (aOR, 1.31 [95% CI, 1.02-1.68]), but 30-day readmission rates did not differ. All associations were attenuated after additional adjustment for patient-level area deprivation index., Conclusions: Physician outpatient practices that serve the most socioeconomically disadvantaged patients with CAD perform worse on some clinical outcomes, despite providing similar guideline-recommended care as other practices, and consequently could fare poorly under value-based payment programs. Social factors beyond care provided by outpatient practices may partly explain worse outcomes. Policymakers should consider accounting for socioeconomic disadvantage in value-based payment programs initiatives that target outpatient practices.

Background: To combat the high cost and increasing burden of quality reporting, the Medicare Payment Advisory (MedPAC) has recommended using claims data wherever possible to measure clinical quality. In this article, we use a cohort of Medicare beneficiaries with heart failure with reduced ejection fraction and existing quality metrics to explore the impact of changes in quality metric methodology on measured quality performance, the association with patient outcomes, and hospital rankings., Methods and Results: We used 100% Medicare Parts A and B and a random 40% sample of Part D from 2008 to 2015 to create (1) a cohort of 295 494 fee-for-service beneficiaries with ≥1 hospitalization for heart failure with reduced ejection fraction and (2) a cohort of 1079 hospitals with ≥11 heart failure with reduced ejection fraction admissions in 2014 and 2015. We used Part D data to calculate β-blocker use after discharge and β-blocker use over time. We then varied the quality metric methodologies to explore the impact on measured performance. We then used multivariable time-to-event analyses to explore the impact of metric methodology on the association between quality performance and patient outcomes and Kendall's Tau to describe impact of quality metric methodology on hospital rankings. We found that quality metric methodology had a significant impact on measured quality performance. The association between quality performance and readmissions was sensitive to changes in methodology but the association with 1-year mortality was not. Changes in quality metric methodology also had a substantial impact on hospital quality rankings., Conclusions: This article highlights how small changes in quality metric methodology can have a significant impact on measured quality performance, the association between quality performance and utilization-based outcomes, and hospital rankings. These findings highlight the need for standardized quality metric methodologies, better case-mix adjustment and cast further doubt on the use of utilization-based outcomes as quality metrics in chronic diseases.

Background: Quality improvement initiatives have been developed to improve acute coronary syndrome care largely in high-income country settings. We sought to synthesize the effect size and quality of evidence from randomized controlled trials (RCTs) and nonrandomized studies for hospital-based acute coronary syndrome quality improvement interventions on clinical outcomes and process of care measures for their potential implementation in low- and middle-income country settings., Methods and Results: We conducted a bibliometric search of databases and trial registers and a hand search in 2016 and performed an updated search in May 2018 and May 2019. We performed data extraction, risk of bias assessment, and quality of evidence assessments in duplicate. We assessed differences in outcomes by study design comparing RCTs to nonrandomized quasi-experimental studies and by country income status. A meta-analysis was not feasible due to substantial, unexplained heterogeneity among the included studies, and thus, we present a qualitative synthesis. We screened 5858 records and included 32 studies (14 RCTs [n=109 763] and 18 nonrandomized quasi-experimental studies [n=54-423]). In-hospital mortality ranged from 2.1% to 4.8% in the intervention groups versus 3.3% to 5.1% in the control groups in 5 RCTs (n=55 942). Five RCTs (n=64 313) reported 3.0% to 31.0% higher rates of reperfusion for patients with ST-segment-elevation myocardial infarction in the intervention groups. The effect sizes for in-hospital and discharge medical therapies in a majority of RCTs were 3.0% to 10.0% higher in the intervention groups. There was no significant difference in 30-day mortality evaluated by 4 RCTs (n=42 384), which reported 2.5% to 15.0% versus 5.9% to 22% 30-day mortality rates in the intervention versus control groups. In contrast, nonrandomized quasi-experimental studies reported larger effect sizes compared to RCTs. There were no significant consistent differences in outcomes between high-income and middle-income countries. Low-income countries were not represented in any of the included studies., Conclusions: Hospital-based acute coronary syndrome quality improvement interventions have a modest effect on process of care measures but not on clinical outcomes with expected differences by study design. Although quality improvement programs have an ongoing and important role for acute coronary syndrome quality of care in high-income country settings, further research will help to identify key components for contextualizing and implementing such interventions to new settings to achieve their desired effects. Systematic Review Registration: URL: https://www.crd.york.ac.uk/PROSPERO/. Unique identifier: CRD42016047604.

Background: The Centers for Disease Control and Prevention's Million Hearts initiative includes an ambitious ≥80% blood pressure control goal in US adults with hypertension by 2022. We used the validated Blood Pressure Control Model to quantify changes in clinic-based hypertension management processes needed to attain ≥80% blood pressure control., Methods and Results: The Blood Pressure Control Model simulates patient blood pressures weekly using 3 key modifiable hypertension management processes: office visit frequency, clinician treatment intensification given uncontrolled blood pressure, and continued antihypertensive medication use (medication adherence rate). We compared blood pressure control rates (using the Seventh Joint National Committee on hypertension targets) achieved over 4 years between usual care and the best-observed values for management processes identified from the literature (1-week return visit interval, 20%-44% intensification rate, and 76% adherence rate). We determined the management process values needed to achieve ≥80% blood pressure control in US adults. In adults with uncontrolled blood pressure, usual care achieved 45.6% control (95% uncertainty interval, 39.6%-52.5%) and literature-based best-observed values achieved 79.7% control (95% uncertainty interval, 79.3%-80.1%) over 4 years. Increasing treatment intensification rates to 62% of office visits with an uncontrolled blood pressure resulted in ≥80% blood pressure control, even when the return visit interval and adherence remained at usual care values. Improving to best-observed values for all 3 management processes would achieve 78.1% blood pressure control in the overall US population with hypertension, approaching the ≥80% Million Hearts 2022 goal., Conclusions: Achieving the Million Hearts blood pressure control goal by 2022 will require simultaneously increasing visit frequency, overcoming therapeutic inertia, and improving patient medication adherence. As the relative importance of each of these 3 processes will depend on local characteristics, simulation models like the Blood Pressure Control Model can help local healthcare systems tailor strategies to reach local and national benchmarks.

Background Hospitals participating in the national Get With The Guidelines-Resuscitation registry receive an award for high rates of adherence to quality metrics for in-hospital cardiac arrest. We sought to evaluate whether awards based on these quality metrics can be considered a proxy for performance on cardiac arrest survival. Methods and Results Among 195 hospitals with continuous participation in Get With The Guidelines-Resuscitation between 2012 and 2015, we identified 78 that received an award (Gold or Silver) for ≥85% compliance for all 4 metrics for in-hospital cardiac arrest-time to chest compressions, ≤1 minute; time to defibrillation, ≤2 minutes; device confirmation of endotracheal tube placement; and a monitored/witnessed arrest-for at least 12 consecutive months during 2014 to 2015. Award hospitals had higher cardiac arrest volumes than nonaward hospitals but otherwise had similar site characteristics. During 2014 to 2015, award hospitals had higher rates of return of spontaneous circulation for in-hospital cardiac arrest than nonaward hospitals (median [interquartile range], 71% [64%-77%] versus 66% [59%-74%]; Spearman ρ, 0.19; P=0.009). However, rates of risk-standardized survival to discharge at award hospitals (median, 25% [interquartile range, 22%-30%]) were similar to nonaward hospitals (median, 24% [interquartile range, 12%-27%]; Spearman ρ, 0.13; P=0.06). Among hospitals in the best tertile for survival to discharge in 2014 to 2015, 55.4% (36/65) did not receive an award, with poor discrimination of high-performing hospitals by award status (C statistic, 0.53). Similarly, there was only a weak association between hospitals' award status in 2014 to 2015 and their rates of survival to discharge in the preceding 2-year period (Spearman ρ, 0.16; P=0.03). Conclusions The current recognition mechanism within a national registry for in-hospital cardiac arrest captures hospital performance on return of spontaneous circulation but is not well correlated with survival to discharge. This suggests that current awards for resuscitation quality may not adequately capture hospital performance on overall survival-the outcome of greatest interest to patients.

Background: Stroke is the leading cause of death in China. Despite the wide dissemination of evidence-based guidelines, data about adherence to these in routine clinical practice are scarce. We conducted a study using a nationwide registry to evaluate the implementation of evidence-based stroke performance indicators and associated guidelines, for patients with an ischemic stroke in China., Methods and Results: The China National Stroke Registry is a prospective cohort study, including 12 416 patients diagnosed with acute ischemic stroke from 132 hospitals across China, for 1 year beginning September 2007. Twelve performance indicators were selected to evaluate the quality of stroke care. Multivariable Cox models were used to determine the association between optimal compliance and clinical outcomes. Conformity with performance measures ranged from a median of 6.5% for the use of intravenous tPA (tissue-type plasminogen activator) to 81.8% for early use of antithrombotics. The optimal compliance with all in-hospital measures was associated with 1-year death after admission (hazard ratio, 0.66; 95% CI, 0.55-0.79). The optimal compliance with all discharge measures was associated with the 1-year death after discharge (hazard ratio, 0.55; 95% CI, 0.44-0.69), 1-year stroke recurrence (hazard ratio, 0.81; 95% CI, 0.70-0.93), and favorable functional outcomes (defined as modified Rankin Scale score of ≤2) (hazard ratio, 1.10; 95% CI, 1.04-1.16)., Conclusions: Adherence to evidence-based ischemic stroke care measures in China revealed substantial gaps, and select measures were associated with improved outcomes. These findings support the need for ongoing quality measurement and improvement in stroke care in China.

Background To improve value in the care of patients with acute myocardial infarction (MI), payment models increasingly hold providers accountable for costs. As such, providers need tools to predict length of stay (LOS) during hospitalization and the likelihood of needing postacute care facilities after discharge for acute MI patients. We developed models to estimate risk for prolonged LOS and postacute care for acute MI patients at time of hospital admission to facilitate coordinated care planning. Methods and Results We identified patients in the National Cardiovascular Data Registry ACTION registry (Acute Coronary Treatment and Intervention Outcomes Network) who were discharged alive after hospitalization for acute MI between July 1, 2008 and March 31, 2017. Within a 70% random sample (Training cohort) we developed hierarchical, proportional odds models to predict LOS and hierarchical logistic regression models to predict discharge to postacute care. Models were validated in the remaining 30%. Of 633 737 patients in the Training cohort, 16.8% had a prolonged LOS (≥7 days) and 7.8% were discharged to a postacute facility (extended care, a transitional care unit, or rehabilitation). Model discrimination was moderate in the validation dataset for predicting LOS (C statistic=0.640) and strong for predicting discharge to postacute care (C statistic=0.827). For both models, discrimination was similar in ST-segment-elevation MI and non-ST-segment-elevation MI subgroups and calibration was excellent. Conclusions These models developed in a national registry can be used at the time of initial hospitalization to predict LOS and discharge to postacute facilities. Prospective testing of these models is needed to establish how they can improve care coordination and lower costs.

Background: Hospital profiling is typically undertaken using risk-standardized 30-day mortality, but obtaining these data for hospitals can be difficult. We sought to determine whether risk-standardized in-hospital mortality could serve as an adequate proxy for risk-standardized 30-day mortality data for the purposes of identifying outlier hospitals., Methods and Results: Acute ischemic stroke cases entered into GWTG (Get With The Guidelines)-Stroke between 2003 and 2013 were linked to fee-for-service Medicare files to obtain 30-day mortality. Risk-standardized mortality rates (RSMR) for in-hospital and 30-day mortality were generated using previously developed risk score models, and the proportion of hospitals classified as statistical outliers compared. We also assessed the impact of using the combined outcome of in-hospital mortality or discharge to hospice. A total of 535 332 ischemic stroke patients from 1494 GWTG-Stroke hospitals were included; mean age was 80 years, 59% female, and 19% nonwhite. At the hospital level, mean in-hospital RSMRs and 30-day RSMRs were 6.0% and 14.6%, respectively, but the correlation between the 2 was modest ( r =0.53). Overall agreement in the designation of outlier hospitals between in-hospital and 30-day RSMRs was 78%, but chance-corrected agreement was only fair (κ=0.29). However, when using the combined outcome of in-hospital mortality or discharge to hospice (risk-standardized mean =11.8%), the correlation with 30-day RSMR was much stronger ( r = 0.83) and outlier agreement improved substantially (κ=0.60)., Conclusions: When used to identify outlier hospitals with high or low mortality, the agreement between risk-standardized in-hospital mortality and 30-day mortality was modest. However, the combined outcome of in-hospital mortality or discharge to hospice showed much better agreement with 30-day mortality. This composite outcome could serve as a proxy for 30-day mortality when used to identify low- or high-performing hospitals., (© 2017 American Heart Association, Inc.)

Background: We explored regional variation in 30-day ischemic stroke mortality and readmission rates and the extent to which regional differences in patients, hospitals, healthcare resources, and a quality of care composite care measure explain the observed variation., Methods and Results: This ecological analysis aggregated patient and hospital characteristics from the Get With The Guidelines-Stroke registry (2007-2011), healthcare resource data from the Dartmouth Atlas of Health Care (2006), and Medicare fee-for-service data on 30-day mortality and readmissions (2007-2011) to the hospital referral region (HRR) level. We used linear regression to estimate adjusted HRR-level 30-day outcomes, to identify HRR-level characteristics associated with 30-day outcomes, and to describe which characteristics explained variation in 30-day outcomes. The mean adjusted HRR-level 30-day mortality and readmission rates were 10.3% (SD=1.1%) and 13.1% (SD=1.1%), respectively; a modest, negative correlation ( r =-0.17; P =0.003) was found between one another. Demographics explained more variation in readmissions than mortality (25% versus 6%), but after accounting for demographics, comorbidities accounted for more variation in mortality compared with readmission rates (17% versus 7%). The combination of hospital characteristics and healthcare resources explained 11% and 16% of the variance in mortality and readmission rates, beyond patient characteristics. Most of the regional variation in mortality (65%) and readmission (50%) rates remained unexplained., Conclusions: Thirty-day mortality and readmission rates vary substantially across HRRs and exhibit an inverse relationship. While regional variation in 30-day outcomes were explained by patient and hospital factors differently, much of the regional variation in both outcomes remains unexplained., (© 2017 American Heart Association, Inc.)

Background: The Acute Cardiovascular Care Association defined quality indicators (QIs) for the management of acute myocardial infarction. The application of these QIs to existing databases is appealing. It remains to be determined what the rates of implementation are, how the QIs are related to long-term survival, and whether quality categorization is possible., Methods and Results: The QIs were extracted from the French nationwide registries French Registry of Acute ST-Elevation or Non-ST-Elevation Myocardial Infarction (FAST-MI) 2005 (n=3670) and FAST-MI 2010 (n=4169). Implementation rates for each QI are reported for both cohorts. The composite QI was used for benchmarking, and the relationship between QIs and 3-year survival was determined using a Cox model. In FAST-MI 2010, 12 individual and 2 composite QIs could be assessed. Four QIs were not recorded in FAST-MI 2010 and 4 in 2005, either because of treatment nonavailability or because of data not recorded. The degree of implementation ranged from 12% to 89%, with higher rates in 2010 as compared with 2005. Seven individual QIs were associated with survival, and there was a significant and gradual association between survival and categories of the composite QI. Center categorization was possible in 26% to 30% of participating centers; 16 (27%) centers in 2005 and 14 (20%) in 2010 were categorized as low quality., Conclusions: Twelve of 17 individual QIs could be assessed from FAST-MI 2010. The composite QI was significantly associated with 3-year survival and distinguished centers with high, average, and low quality of care., (© 2017 American Heart Association, Inc.)

Background: Timely reperfusion is critical in acute ischemic stroke (AIS) and ST-segment-elevation myocardial infarction (STEMI). The degree to which hospital performance is correlated on emergent STEMI and AIS care is unknown. Primary objective of this study was to determine whether there was a positive correlation between hospital performance on door-to-balloon (D2B) time for STEMI and door-to-needle (DTN) time for AIS, with and without controlling for patient and hospital differences., Methods and Results: Prospective study of all hospitals in both Get With The Guidelines-Stroke and Get With The Guidelines-Coronary Artery Disease from 2006 to 2009 and treating ≥10 patients. We compared hospital-level DTN time and D2B time using Spearman rank correlation coefficients and hierarchical linear regression modeling. There were 43 hospitals with 1976 AIS and 59 823 STEMI patients. Hospitals' DTN times for AIS did not correlate with D2B times for STEMI (ρ=-0.09; P =0.55). There was no correlation between hospitals' proportion of eligible patients treated within target time windows for AIS and STEMI (median DTN time <60 minutes: 21% [interquartile range, 11-30]; median D2B time <90 minutes: 68% [interquartile range, 62-79]; ρ=-0.14; P =0.36). The lack of correlation between hospitals' DTN and D2B times persisted after risk adjustment. We also correlated hospitals' DTN time and D2B time data from 2013 to 2014 using Get With The Guidelines (DTN time) and Hospital Compare (D2B time). From 2013 to 2014, hospitals' DTN time performance in Get With The Guidelines was not correlated with D2B time performance in Hospital Compare (n=546 hospitals)., Conclusions: We found no correlation between hospitals' observed or risk-adjusted DTN and D2B times. Opportunities exist to improve hospitals' performance of time-critical care processes for AIS and STEMI in a coordinated approach., (© 2017 American Heart Association, Inc.)

Background: Although continuous electrocardiographic (ECG) monitoring is ubiquitous in hospitals, monitoring practices are inconsistent. We evaluated implementation of American Heart Association practice standards for ECG monitoring on nurses' knowledge, quality of care, and patient outcomes., Methods and Results: The PULSE (Practical Use of the Latest Standards of Electrocardiography) Trial was a 6-year multisite randomized clinical trial with crossover that took place in 65 cardiac units in 17 hospitals. We measured outcomes at baseline, time 2 after group 1 hospitals received the intervention, and time 3 after group 2 hospitals received the intervention. Measurement periods were 15 months apart. The 2-part intervention consisted of an online ECG monitoring education program and strategies to implement and sustain change in practice. Nurses' knowledge (N=3013 nurses) was measured by a validated 20-item online test, quality of care related to ECG monitoring (N=4587 patients) by on-site observation, and patient outcomes (mortality, in-hospital myocardial infarction, and not surviving a cardiac arrest; N=95 884 hospital admissions) by review of administrative, laboratory, and medical record data. Nurses' knowledge improved significantly immediately after the intervention in both groups but was not sustained 15 months later. For most measures of quality of care (accurate electrode placement, accurate rhythm interpretation, appropriate monitoring, and ST-segment monitoring when indicated), the intervention was associated with significant improvement, which was sustained 15 months later. Of the 3 patient outcomes, only in-hospital myocardial infarction declined significantly after the intervention and was sustained., Conclusions: Online ECG monitoring education and strategies to change practice can lead to improved nurses' knowledge, quality of care, and patient outcomes., Clinical Trial Registration: URL: http://www.clinicaltrials.gov. Unique identifier: NCT01269736., (© 2017 American Heart Association, Inc.)

Background: Functional status is a key patient-centric outcome, but there are little data on whether functional recovery post-stroke varies among hospitals. This study examined the distribution of functional status 3 months after stroke, determined whether these outcomes vary among hospitals, and identified hospital characteristics associated with better (or worse) functional outcomes., Methods and Results: Observational analysis of the AVAIL study (Adherence Evaluation After Ischemic Stroke-Longitudinal) included 2083 ischemic stroke patients enrolled from 82 US hospitals participating in Get With The Guidelines-Stroke and AVAIL. The primary outcome was dependence or death at 3 months (modified Rankin Scale [mRS] score of 3-6). Secondary outcomes included functional dependence (mRS score of 3-5), disabled (mRS score of 2-5), and mRS evaluated as a continuous score. By 3 months post-discharge, 36.5% of patients were functionally dependent or dead. Rates of dependence or death varied widely by discharging hospitals (range: 0%-67%). After risk adjustment, patients had lower rates of 3-month dependence or death when treated at teaching hospitals (odds ratio, 0.72; 95% confidence interval, 0.54-0.96) and certified primary stroke centers (odds ratio, 0.69; 95% confidence interval, 0.53-0.91). In contrast, a composite measure of hospital-level adherence to acute stroke care performance metrics, stroke volume, and bed size was not associated with downstream patient functional status. Findings were robust across mRS end points and sensitivity analyses., Conclusions: One third of acute ischemic stroke patients were functionally dependent or dead 3 months postacute stroke; functional recovery rates varied considerably among hospitals, supporting the need to better determine which care processes can maximize functional outcomes., (© 2017 American Heart Association, Inc.)

Background: Although risk adjustment remains a cornerstone for comparing outcomes across hospitals, optimal strategies continue to evolve in the presence of many confounders. We compared conventional regression-based model to approaches particularly suited to leveraging big data., Methods and Results: We assessed hospital all-cause 30-day excess mortality risk among 8952 adults undergoing percutaneous coronary intervention between October 1, 2011, and September 30, 2012, in 24 Massachusetts hospitals using clinical registry data linked with billing data. We compared conventional logistic regression models with augmented inverse probability weighted estimators and targeted maximum likelihood estimators to generate more efficient and unbiased estimates of hospital effects. We also compared a clinically informed and a machine-learning approach to confounder selection, using elastic net penalized regression in the latter case. Hospital excess risk estimates range from -1.4% to 2.0% across methods and confounder sets. Some hospitals were consistently classified as low or as high excess mortality outliers; others changed classification depending on the method and confounder set used. Switching from the clinically selected list of 11 confounders to a full set of 225 confounders increased the estimation uncertainty by an average of 62% across methods as measured by confidence interval length. Agreement among methods ranged from fair, with a κ statistic of 0.39 (SE: 0.16), to perfect, with a κ of 1 (SE: 0.0)., Conclusions: Modern causal inference techniques should be more frequently adopted to leverage big data while minimizing bias in hospital performance assessments., (© 2016 American Heart Association, Inc.)

Background: Despite increasing awareness regarding evidence-based guidelines, considerable gaps exist for heart failure (HF) quality of care at teaching hospitals (TH) and nonteaching hospitals (NTH). We analyzed data from Get With The Guidelines (GWTG)-HF to compare the rates and trends of guideline-recommended care at TH and NTH for patients with HF., Method and Results: Baseline patient characteristics, performance measures, and in-hospital outcomes were compared between 197 187 HF patients admitted to TH and 106 924 patients admitted to NTH between 2005 and 2014. Patients treated in TH were younger and were more likely to be black and uninsured. Defect-free care (defined as 100% compliance with performance measures) was similar in both group of hospitals (crude rates: 88% at TH versus 86% at NTH, adjusted odds ratio 0.99, 95% confidence interval 0.73-1.34) as were individual performance measures: discharge instruction, documentation of ejection fraction, use of angiotensin-converting enzyme inhibitors/angiotensin receptor antagonists, use of β-blocker, and smoking cessation counseling. During the study period, there was improvement in adherence with performance measures over time, with no significant difference at TH (adjusted odds ratio 1.20, 95% confidence interval 1.11-1.30; P <0.01) and NTH (adjusted odds ratio 1.09, 95% confidence interval 1.02-1.17; P =0.01; interaction P value 0.07)., Conclusions: Data from the GWTG-HF program suggest that there was improving and comparable adherence with HF performance measures and use of guideline-recommended therapies irrespective of hospital teaching status., (© 2016 American Heart Association, Inc.)

Between 2013 and 2014, the Centers for Medicare and Medicaid Services and the National Cardiovascular Data Registry publically reported risk-adjusted 30-day readmission rates after percutaneous coronary intervention (PCI) as a pilot project. A key strength of this public reporting effort included risk adjustment with clinical rather than administrative data. Furthermore, because readmission after PCI is common, expensive, and preventable, this metric has substantial potential to improve quality and value in American cardiology care. Despite this, concerns about the metric exist. For example, few PCI readmissions are caused by procedural complications, limiting the extent to which improved procedural technique can reduce readmissions. Also, similar to other readmission measures, PCI readmission is associated with socioeconomic status and race. Accordingly, the metric may unfairly penalize hospitals that care for underserved patients. Perhaps in the context of these limitations, Centers for Medicare and Medicaid Services has not yet included PCI readmission among metrics that determine Medicare financial penalties. Nevertheless, provider organizations may still wish to focus on this metric to improve value for cardiology patients. PCI readmission is associated with low-risk chest discomfort and patient anxiety. Therefore, patient education, improved triage mechanisms, and improved care coordination offer opportunities to minimize PCI readmissions. Because PCI readmission is common and costly, reducing PCI readmission offers provider organizations a compelling target to improve the quality of care, and also performance in contracts involve shared financial risk., (© 2016 American Heart Association, Inc.)

Background: In 2009, national legislation promoted wide-spread adoption of electronic health records (EHRs) across US hospitals; however, the association of EHR use with quality of care and outcomes after acute myocardial infarction (AMI) remains unclear., Methods and Results: Data on EHR use were collected from the American Hospital Association Annual Surveys (2007-2010) and data on AMI care and outcomes from the National Cardiovascular Data Registry Acute Coronary Treatment and Interventions Outcomes Network Registry-Get With The Guidelines. Comparisons were made between patients treated at hospitals with fully implemented EHR (n=43 527), partially implemented EHR (n=72 029), and no EHR (n=9270). Overall EHR use increased from 82.1% (183/223) hospitals in 2007 to 99.3% (275/277) hospitals in 2010. Patients treated at hospitals with fully implemented EHRs had fewer heparin overdosing errors (45.7% versus 72.8%; P<0.01) and a higher likelihood of guideline-recommended care (adjusted odds ratio, 1.40 [confidence interval, 1.07-1.84]) compared with patients treated at hospitals with no EHR. In non-ST-segment-elevation AMI, fully implemented EHR use was associated with lower risk of major bleeding (adjusted odds ratio, 0.78 [confidence interval, 0.67-0.91]) and mortality (adjusted odds ratio, 0.82 [confidence interval, 0.69-0.97]) compared with no EHR. In ST-segment-elevation MI, outcomes did not significantly differ by EHR status., Conclusions: EHR use has risen to high levels among hospitals in the National Cardiovascular Data Registry. EHR use was associated with less frequent heparin overdosing and modestly greater adherence to acute MI guideline-recommended therapies. In non-ST-segment-elevation MI, slightly lower adjusted risk of major bleeding and mortality were seen in hospitals implemented with full EHRs; however, in ST-segment-elevation MI, differences in outcomes were not seen., (© 2015 American Heart Association, Inc.)

Background: The CArdiovascular HEalth in Ambulatory care Research Team (CANHEART) is conducting a unique, population-based observational research initiative aimed at measuring and improving cardiovascular health and the quality of ambulatory cardiovascular care provided in Ontario, Canada. A particular focus will be on identifying opportunities to improve the primary and secondary prevention of cardiovascular events in Ontario's diverse multiethnic population., Methods and Results: A population-based cohort comprising 9.8 million Ontario adults ≥20 years in 2008 was assembled by linking multiple electronic survey, health administrative, clinical, laboratory, drug, and electronic medical record databases using encoded personal identifiers. The cohort includes ≈9.4 million primary prevention patients and ≈400,000 secondary prevention patients. Follow-up on clinical events is achieved through record linkage to comprehensive hospitalization, emergency department, and vital statistics administrative databases. Profiles of cardiovascular health and preventive care will be developed at the health region level, and the cohort will be used to study the causes of regional variation in the incidence of major cardiovascular events and other important research questions., Conclusions: Linkage of multiple databases will enable the CANHEART study cohort to serve as a powerful big data resource for scientific research aimed at improving cardiovascular health and health services delivery. Study findings will be shared with clinicians, policy makers, and the public to facilitate population health interventions and quality improvement initiatives., (© 2015 American Heart Association, Inc.)

Background: Single-site studies have demonstrated inadequate quality of discharge summaries in timeliness, transmission, and content, potentially contributing to adverse outcomes. However, degree of hospital-level variation in discharge summary quality for patients hospitalized with heart failure (HF) is uncertain., Methods and Results: We analyzed discharge summaries of patients enrolled in the Telemonitoring to Improve Heart Failure Outcomes (Tele-HF) study. We assessed hospital-level performance on timeliness (fraction of summaries completed on the day of discharge), documented transmission to the follow-up physician, and content (presence of components suggested by the Transitions of Care Consensus Conference). We obtained 1501 discharge summaries from 1640 (91.5%) patients discharged alive from 46 hospitals. Among hospitals contributing ≥ 10 summaries, the median hospital dictated 69.2% of discharge summaries on the day of discharge (range, 0.0%-98.0%; P<0.001); documented transmission of 33.3% of summaries to the follow-up physician (range, 0.0%-75.7%; P<0.001); and included 3.6 of 7 Transitions of Care Consensus Conference elements (range, 2.9-4.5; P<0.001). Hospital course was typically included (97.2%), but summaries were less likely to include discharge condition (30.7%), discharge volume status (16.0%), or discharge weight (15.7%). No discharge summary included all 7 Transitions of Care Consensus Conference-endorsed content elements, was dictated on the day of discharge, and was sent to a follow-up physician., Conclusions: Even at the highest performing hospital, discharge summary quality is insufficient in terms of timeliness, transmission, and content. Improvements in all aspects of discharge summary quality are necessary to enable the discharge summary to serve as an effective transitional care tool., (© 2015 American Heart Association, Inc.)

Background: Although the value of clinical registries has been well recognized in developed countries, their use for measuring the quality of emergency medical service care remains relatively unknown. We report the methodology and findings of a statewide emergency medical service surveillance initiative, which is used to measure the quality of systems of care for patients with out-of-hospital cardiac arrest., Methods and Results: Between July 1, 2002, and June 30, 2012, data for adult out-of-hospital cardiac arrest cases of presumed cardiac cause occurring in the Australian Southeastern state of Victoria were extracted from the Victorian Ambulance Cardiac Arrest Registry. Regional and temporal trends in bystander cardiopulmonary resuscitation, event survival, and survival to hospital discharge were analyzed using logistic regression and multilevel modeling. A total of 32,097 out-of-hospital cardiac arrest cases were identified, of whom 14,083 (43.9%) received treatment by the emergency medical service. The risk-adjusted odds of receiving bystander cardiopulmonary resuscitation (odds ratio [OR], 2.96; 95% confidence interval, 2.62-3.33), event survival (OR, 1.55; 95% confidence interval, 1.30-1.85), and survival to hospital discharge (OR, 2.81; 95% confidence interval, 2.07-3.82) were significantly improved by 2011 to 2012 compared with baseline. Significant variation in rates of bystander cardiopulmonary resuscitation and survival were observed across regions, with arrests in rural regions less likely to survive to hospital discharge. The median OR for interhospital variability in survival to hospital discharge outcome was 70% (median OR, 1.70)., Conclusions: Between 2002 and 2012, there have been significant improvements in bystander cardiopulmonary resuscitation and survival outcome for out-of-hospital cardiac arrest patients in Victoria, Australia. However, regional survival disparities and interhospital variability in outcomes pose significant challenges for future improvements in care., (© 2015 American Heart Association, Inc.)

Background: Despite effective treatments to reduce cardiovascular disease risk, their translation into practice is limited., Methods and Results: Using a parallel arm cluster-randomized controlled trial in 60 Australian primary healthcare centers, we tested whether a multifaceted quality improvement intervention comprising computerized decision support, audit/feedback tools, and staff training improved (1) guideline-indicated risk factor measurements and (2) guideline-indicated medications for those at high cardiovascular disease risk. Centers had to use a compatible software system, and eligible patients were regular attendees (Aboriginal and Torres Strait Islander people aged ≥ 35 years and others aged ≥ 45 years). Patient-level analyses were conducted using generalized estimating equations to account for clustering. Median follow-up for 38,725 patients (mean age, 61.0 years; 42% men) was 17.5 months. Mean monthly staff support was <1 hour/site. For the coprimary outcomes, the intervention was associated with improved overall risk factor measurements (62.8% versus 53.4% risk ratio; 1.25; 95% confidence interval, 1.04-1.50; P=0.02), but there was no significant differences in recommended prescriptions for the high-risk cohort (n=10,308; 56.8% versus 51.2%; P=0.12). There were significant treatment escalations (new prescriptions or increased numbers of medicines) for antiplatelet (4.3% versus 2.7%; P=0.01), and BP lowering (18.2% versus 11.0%; P=0.02) but not lipid-lowering medications., Conclusions: In Australian primary healthcare settings, a computer-guided quality improvement intervention, requiring minimal support, improved cardiovascular disease risk measurement but did not increase prescription rates in the high-risk group. Computerized quality improvement tools offer an important, albeit partial, solution to improving primary healthcare system capacity for cardiovascular disease risk management., Clinical Trial Registration Url: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=336630. Australian New Zealand Clinical Trials Registry No. 12611000478910., (© 2015 American Heart Association, Inc.)

Background: We sought to determine inter-rater reliability of the 2009 Appropriate Use Criteria for radionuclide imaging and whether physicians at various levels of training can effectively identify nuclear stress tests with inappropriate indications., Methods and Results: Four hundred patients were randomly selected from a consecutive cohort of patients undergoing nuclear stress testing at an academic medical center. Raters with different levels of training (including cardiology attending physicians, cardiology fellows, internal medicine hospitalists, and internal medicine interns) classified individual nuclear stress tests using the 2009 Appropriate Use Criteria. Consensus classification by 2 cardiologists was considered the operational gold standard, and sensitivity and specificity of individual raters for identifying inappropriate tests were calculated. Inter-rater reliability of the Appropriate Use Criteria was assessed using Cohen κ statistics for pairs of different raters. The mean age of patients was 61.5 years; 214 (54%) were female. The cardiologists rated 256 (64%) of 400 nuclear stress tests as appropriate, 68 (18%) as uncertain, 55 (14%) as inappropriate; 21 (5%) tests were unable to be classified. Inter-rater reliability for noncardiologist raters was modest (unweighted Cohen κ, 0.51, 95% confidence interval, 0.45-0.55). Sensitivity of individual raters for identifying inappropriate tests ranged from 47% to 82%, while specificity ranged from 85% to 97%., Conclusions: Inter-rater reliability for the 2009 Appropriate Use Criteria for radionuclide imaging is modest, and there is considerable variation in the ability of raters at different levels of training to identify inappropriate tests., (© 2015 American Heart Association, Inc.)

Background: Post-percutaneous coronary intervention (PCI) bleeding complications are an important quality metric. We sought to characterize site-level variation in post-PCI bleeding and explore the influence of patient and procedural factors on hospital bleeding performance., Methods and Results: Hospital-level bleeding performance was compared pre- and postadjustment using the newly revised CathPCI Registry(®) bleeding risk model (c-index, 0.77) among 1292 National Cardiovascular Data Registry(®) hospitals performing >50 PCIs from 7/2009 to 9/2012 (n=1,984,998 procedures). Using random effects models, outlier sites were identified based on 95% confidence intervals around the hospital's random intercept. Bleeding 72 hours post-PCI was defined as: arterial access site, retroperitoneal, gastrointestinal, or genitourinary bleeding; intracranial hemorrhage; cardiac tamponade; nonbypass surgery-related blood transfusion with preprocedure hemoglobin ≥ 8 g/dL; or absolute decrease in hemoglobin value ≥ 3 g/dL with preprocedure hemoglobin ≤ 16 g/dL. Overall, the median unadjusted post-PCI bleeding rate was 5.2% and varied among hospitals from 2.6% to 10.4% (5th, 95th percentiles). Center-level bleeding variation persisted after case-mix adjustment (2.8%-9.5%; 5th, 95th percentiles). Although hospitals' observed and risk-adjusted bleeding ranks were correlated (Spearman ρ: 0.88), individual rankings shifted after risk-adjustment (median Δ rank order: ± 91.5; interquartile range: 37.0, 185.5). Outlier classification changed postadjustment for 29.3%, 16.1%, and 26.5% of low-, non-, and high-outlier sites, respectively. Hospital use of bleeding avoidance strategies (bivalirudin, radial access, or vascular closure device) was associated with risk-adjusted bleeding rates., Conclusions: Despite adjustment for patient case-mix, there is wide variation in rates of hospital PCI-related bleeding in the United States. Opportunities may exist for best performers to share practices with other sites., (© 2014 American Heart Association, Inc.)

Background: Translation of evidence-based heart failure (HF) therapies to clinical practice is incomplete and may vary internationally. We examined common measures of quality of care in patients enrolled in the international Acute Study of Clinical Effectiveness of Nesiritide in Decompensated Heart Failure trial., Methods and Results: Patients were admitted to 398 hospitals for acute HF in 5 regions (North America, n=3149; Latin America, n=658; Asia Pacific, n=1744; Central Europe, n=966; and Western Europe, n=490). Predefined quality indicators assessed at hospital discharge included the following: medications (angiotensin-converting enzyme inhibitors, angiotensin II receptor blockers, β-blockers, aldosterone antagonists, hydralazine/nitrates, statin therapy, and warfarin), use (or planned use) of implantable intracardiac devices, and blood pressure control (<140/90 mm Hg). We determined regional variations in quality indicators as well as the temporal variation of these indicators during the course of the trial. There was significant variation in conformity among different quality indicators, ranging from 0% to 89%. Of all potential performance opportunities, 19 076 of 32 268 (59%) were met, with Central Europe highest at 64%, followed by North America (63%), Western Europe (61%), Latin America (56%), and Asia Pacific (51%; P<0.0001). North America, Central Europe, and Asia Pacific regions demonstrated a modest increase in quality indicator conformity over time, although there was no significant change in other regions., Conclusions: Quality of care for patients hospitalized with acute HF varies and remains suboptimal even within a randomized clinical trial, which included quality improvement interventions. Specific measures designed to improve performance measures should be implemented even within multicenter clinical trials.

Background: In-hospital and postdischarge treatment rates for acute coronary syndrome (ACS) remain low in India. However, little is known about the prevalence and associations of the package of optimal ACS medical care in India. Our objective was to define the prevalence, associations, and impact of optimal in-hospital and discharge medical therapy in the Kerala ACS Registry of 25,718 admissions., Methods and Results: We defined optimal in-hospital ACS medical therapy as receiving the following 5 medications: aspirin, clopidogrel, heparin, β-blocker, and statin. We defined optimal discharge ACS medical therapy as receiving all of the above therapies except heparin. Comparisons by optimal versus nonoptimal ACS care were made via Student t test for continuous variables and χ(2) test for categorical variables. We created random effects logistic regression models to evaluate the association between Global Registry of Acute Coronary Events risk score variables and optimal in-hospital or discharge medical therapy. Optimal in-hospital and discharge medical care were delivered in 40% and 46% of admissions, respectively. Wide variability in both in-hospital and discharge medical care was present, with few hospitals reaching consistently high (>90%) levels. Patients receiving optimal in-hospital medical therapy had an adjusted odds ratio (95% confidence interval)=0.93 (0.71, 1.22) for in-hospital death and an adjusted odds ratio (95% confidence interval)=0.79 (0.63, 0.99) for major adverse cardiovascular event rates. Patients who received optimal in-hospital medical care were far more likely to receive optimal discharge care (adjusted odds ratio [95% confidence interval] = 10.48 [9.37, 11.72])., Conclusions: Strategies to improve in-hospital and discharge medical therapy are needed to improve local process-of-care measures and ACS outcomes in Kerala.

Background: Reducing hospital readmission rates is a national priority; however, evidence about hospital strategies that are associated with lower readmission rates is limited. We sought to identify hospital strategies that were associated with lower readmission rates for patients with heart failure., Methods and Results: Using data from a Web-based survey of hospitals participating in national quality initiatives to reduce readmission (n=599; 91% response rate) during 2010-2011, we constructed a multivariable linear regression model, weighted by hospital volume, to determine strategies independently associated with risk-standardized 30-day readmission rates (RSRRs) adjusted for hospital teaching status, geographic location, and number of staffed beds. Strategies that were associated with lower hospital RSRRs included the following: (1) partnering with community physicians or physician groups to reduce readmission (0.33% percentage point lower RSRRs; P=0.017), (2) partnering with local hospitals to reduce readmissions (0.34 percentage point; P=0.020), (3) having nurses responsible for medication reconciliation (0.18 percentage point; P=0.002), (4) arranging follow-up appointments before discharge (0.19 percentage point; P=0.037), (5) having a process in place to send all discharge paper or electronic summaries directly to the patient's primary physician (0.21 percentage point; P=0.004), and (6) assigning staff to follow up on test results that return after the patient is discharged (0.26 percentage point; P=0.049). Although statistically significant, the magnitude of the effects was modest with individual strategies associated with less than half a percentage point reduction in RSRRs; however, hospitals that implemented more strategies had significantly lower RSRRs (reduction of 0.34 percentage point for each additional strategy)., Conclusions: Several strategies were associated with lower hospital RSRRs for patients with heart failure.

Background- Evidence has accrued that cardiopulmonary resuscitation quality affects cardiac arrest outcome. However, the relative contributions of chest compression components (such as rate and depth) to successful resuscitation remain unclear. Methods and Results- We sought to measure the effect of cardiopulmonary resuscitation quality on cardiac arrest outcome through systematic review and meta-analysis. We searched for any clinical study assessing cardiopulmonary resuscitation performance on adult cardiac arrest patients in which survival was a reported outcome, either return of spontaneous circulation or survival to admission or discharge. Of 603 identified abstracts, 10 studies met inclusion criteria. Effect sizes were reported as mean differences. Missing data were resolved by author contact. Estimates were segregated by cardiopulmonary resuscitation metric (chest compression rate, depth, no-flow fraction, and ventilation rate), and a random-effects model was applied to estimate an overall pooled effect. Arrest survivors were significantly more likely to have received deeper chest compressions than nonsurvivors (mean difference, 2.44 mm; 95% confidence interval, 1.19-3.69 [P<0.001]; n=6 studies; I(2)=0.0%; P for heterogeneity=0.9). Likewise, survivors were significantly more likely to have received chest compression rates closer to 85 to 100 compressions per minute (cpm) than nonsurvivors (absolute mean difference from 85 cpm, -4.81 cpm; 95% confidence interval, -8.19 to -1.43 [P=0.005]; from 100 cpm, -5.04 cpm; 95% confidence interval, -8.44 to -1.65 [P=0.004]; n=6 studies; I(2)<49%; P for heterogeneity >0.2). No significant difference in no-flow fraction (n=7 studies) or ventilation rate (n=4 studies) was detected between survivors and nonsurvivors. Conclusions- Deeper chest compressions and rates closer to 85 to 100 cpm are significantly associated with improved survival from cardiac arrest.

Background: Clinical guidelines recommend similar medical therapy for patients with ST-segment elevation myocardial infarction (STEMI) and non-ST-segment elevation MI (NSTEMI)., Methods and Results: Using the Get with the Guidelines-Coronary Artery Disease registry (GWTG-CAD), we analyzed data including 72 352 patients (48 966, NSTEMI; 23 386, STEMI) from 237 US sites between May 1, 2006 and March 21, 2010. Performance and quality measures were compared between NSTEMI and STEMI patients. NSTEMI patients were older and had a higher rate of medical comorbidities compared with STEMI patients, including prior coronary artery disease (38.5% versus 24.7%; P<0.0001), heart failure (17.5% versus 6.2%; P<0.0001), hypertension (70.8% versus 59.1%; P<0.0001) and diabetes mellitus (34.9 versus 23.3%; P<0.0001). Adjusting for confounding variables, STEMI patients were more likely to receive aspirin within 24 hours 98.5% versus 97.1% (adjusted odds ratio [AOR], 1.63; 95% confidence interval [CI], 1.32-2.02), be discharged on aspirin 98.5% versus 97.3% (AOR, 1.33; 95% CI, 1.19-1.49), β-blockers 98.2% versus 96.9% (AOR, 1.48; 95% CI, 1.35-1.63), or lipid-lowering medication for low-density lipoprotein level >100 mg/dL 96.8% versus 91.0% (AOR, 1.85; 95% CI, 1.61-2.13). STEMI patients were also more likely to receive β-blockers within 24 hours of hospital arrival 93.9% versus 90.8% (AOR, 1.57; 95% CI, 1.37-1.79) and the following discharge medications: angiotensin-converting enzyme inhibitors or angiotensin receptor blocking agents 85.3% versus 77.4% (AOR, 1.62; 95% CI, 1.51-1.75), clopidogrel 85.6% versus 67.0% (AOR, 2.42; 95% CI, 2.23-2.61) or lipid-lowering medications 94.8% versus 88.0% (AOR, 1.71; 95% CI, 1.56-1.86)., Conclusions: Among hospitals participating in GWTG-CAD, adherence with guideline-based medical therapy was high for patients with both STEMI and NSTEMI. Yet, there is still room for further improvement, particularly in the care of NSTEMI patients.

Background: Cardiovascular disease continues to cause significant morbidity, mortality, and impaired quality of life, with unrealized health gains from the underuse of available evidence. The Transitions, Risks, and Actions in Coronary Events Center for Outcomes Research and Education (TRACE-CORE) aims to advance the science of acute coronary syndromes by examining the determinants and outcomes of the quality of transition from hospital to community and by quantifying the impact of potentially modifiable characteristics associated with decreased quality of life, rehospitalization, and mortality., Methods and Results: TRACE-CORE comprises a longitudinal multiracial cohort of patients hospitalized with acute coronary syndromes, 2 research projects, and development of a nucleus of early stage investigators. We are currently enrolling 2500 adults hospitalized for acute coronary syndromes at 6 hospitals in the northeastern and southeastern United States. We will follow these patients for 24 months after hospitalization through medical record abstraction and 5 patient interviews focusing on quality of life, cardiac events, rehospitalizations, mortality, and medical, behavioral, and psychosocial characteristics. The Transitions Project studies determinants of and disparities in outcomes of the quality of patients' transition from hospital to community. Focusing on potentially modifiable factors, the Action Scores Project will develop and validate action scores to predict recurrent cardiac events, death, and quality of life, describe longitudinal variation in these scores, and develop a dashboard for patient and provider action on the basis of these scores., Conclusions: In TRACE-CORE, sound methodologic principles of observational studies converge with outcomes and effectiveness research approaches. We expect that our data, research infrastructure, and research projects will inform the development of novel secondary prevention approaches and underpin the careers of cardiovascular outcomes researchers.

Background: The left ventricular ejection fraction (LVEF) has prognostic and therapeutic utility after acute myocardial infarction (AMI). Although LVEF assessment is a key performance measure among AMI patients, contemporary rates of in-hospital assessment and its association with therapy use have not been well characterized., Methods and Results: We examined rates of in-hospital LVEF assessment among 77 982 non-ST-elevation myocardial infarction patients and 50 863 ST-elevation myocardial infarction patients in Acute Coronary Treatment and Intervention Outcomes Network Registry-Get With The Guidelines between January 2007 and September 2009, after excluding patients who died in-hospital or who were transferred to another acute care facility, discharged to end-of-life care, or had missing LVEF assessment status. LVEF assessment increased significantly over time, with higher rates among ST-elevation myocardial infarction than non-ST-elevation myocardial infarction patients (95.1% versus 91.6%; P<0.001). Excluding patients with prior heart failure did not alter these observations. Significant interhospital variability in LVEF assessment rates was observed. Compared with patients with in-hospital LVEF assessment, patients who did not have LVEF assessed were older and more likely to have clinical comorbidities. In multivariable modeling, lower overall hospital quality of AMI care was also associated with lower likelihood of LVEF assessment (odds ratio for failure to assess LVEF, 1.09; 95% confidence interval, 1.05-1.13 per 10% decrease in defect-free care). Patients with in-hospital LVEF assessment were more likely to be discharged on evidence-based secondary prevention medication therapies compared with patients without LVEF assessment., Conclusions: The assessment of LVEF among patients with AMI has improved significantly over time, yet significant interhospital variability exists. Patients who did not have in-hospital LVEF assessment were less likely to receive evidence-based medications at discharge. These patients represent targets for future quality improvement efforts.

Background: Variation in outcomes after percutaneous coronary interventions (PCI) may reflect differences in quality of care. To date, however, we lack a methodology to monitor and improve national hospital 30-day mortality rates among patients undergoing PCI., Methods and Results: We developed hierarchical logistic regression models to calculate hospital risk-standardized 30-day all-cause PCI mortality rates. Due to differences in risk, patients were divided into 2 cohorts: those with ST-segment elevation myocardial infarction or cardiogenic shock, and those with no ST-segment elevation myocardial infarction and no cardiogenic shock. The models were derived using 2006 data from the CathPCI Registry linked with administrative claims data, and validated using comparable 2005 data. In the derivation cohort of the ST-segment elevation myocardial infarction or shock model (n=15 123), the unadjusted 30-day mortality rate was 9.2%. The final model included 13 variables with the observed mortality rates ranging from 1.4% to 40.3% across deciles of the predicted patient mortality rates. The 25th and 75th percentiles of the risk-standardized mortality rate were 8.5% and 9.7%, with 5th and 95th percentiles of 7.6% and 11.0%. In the derivation cohort of the no ST-segment elevation myocardial infarction and no shock model (n=110 529), the unadjusted 30-day mortality rate was 1.4%. The final model included 16 variables with the observed predicted mortality rates ranging from 0.1% to 7.0% across deciles of the predicted patient mortality rates. The 25th and 75th percentiles of the risk-standardized mortality rate across 612 hospitals were 1.3% and 1.6%, with 5th and 95th percentiles of 1.0% and 2.0%., Conclusions: These National Quality Forum endorsed registry-based models produce estimates of hospital risk-standardized mortality rates for patients undergoing PCI.

Background: The Centers for Medicare and Medicaid Services is considering developing a 30-day ischemic stroke hospital-level mortality model using administrative data. We examined whether inclusion of the National Institutes of Health Stroke Scale (NIHSS), a measure of stroke severity not included in administrative data, would alter 30-day mortality rates in the Veterans Health Administration., Methods and Results: A total of 2562 veterans admitted with ischemic stroke to 64 Veterans Health Administration Hospitals in the fiscal year 2007 were included. First, we examined the distribution of unadjusted mortality rates across the Veterans Health Administration. Second, we estimated 30-day all-cause, risk standardized mortality rates (RSMRs) for each hospital by adjusting for age, sex, and comorbid conditions using hierarchical models with and without the inclusion of the NIHSS. Finally, we examined whether adjustment for the NIHSS significantly changed RSMRs for each hospital compared with other hospitals. The median unadjusted mortality rate was 3.6%. The RSMR interquartile range without the NIHSS ranged from 5.1% to 5.6%. Adjustment with the NIHSS did not change the RSMR interquartile range (5.1%-5.6%). Among veterans ≥65 years, the RSMR interquartile range without the NIHSS ranged from 9.2% to 10.3%. With adjustment for the NIHSS, the RSMR interquartile range changed from 9.4% to 10.0%. The plot of 30-day RSMRs estimated with and without the inclusion of the NIHSS in the model demonstrated overlapping 95% confidence intervals across all hospitals, with no hospital significantly below or above the mean-unadjusted 30-day mortality rate. The 30-day mortality measure did not discriminate well among hospitals., Conclusions: The impact of the NIHSS on RSMRs was limited. The small number of stroke admissions and the narrow range of 30-day stroke mortality rates at the facility level in the Veterans Health Administration cast doubt on the value of using 30-day RSMRs as a means of identifying outlier hospitals based on their stroke care quality.

Background: Clopidogrel prescription is a class I guideline recommendation for medically managed patients with non-ST-segment-elevation myocardial infarction (NSTEMI). However, clopidogrel has historically been underused in this population. We evaluated contemporary rates of its use and evaluated associated factors, with a particular focus on hospital quality of myocardial infarction (MI) care., Methods and Results: We examined clopidogrel prescription rates among 23 186 patients with NSTEMI discharged from 382 US hospitals between October 2009 and March 2011. Associations between clopidogrel prescription and various patient and hospital factors, including hospital quality of MI care, were determined with regression modeling. Of the sample, 54.9% of eligible patients with NSTEMI received clopidogrel prescription at hospital discharge. Variation in rate by hospital was large, ranging from 22% to 97%. A variety of patient and hospital factors were associated with clopidogrel prescription. Hospital quality of MI care demonstrated modest association with clopidogrel prescription (odds ratio, 0.68; 95% CI, 0.54-0.85) between the lowest and highest hospital quality quartile) and accounted for 5.7% of the variation in prescription rates., Conclusions: Clopidogrel prescription is significantly underused in the medically managed NSTEMI population and demonstrates wide variability by hospital. Although hospital quality of MI care is associated with its use, the findings suggest that it only has a modest effect. Therefore, efforts to improve clopidogrel use likely will require measures beyond improving the overall hospital quality of MI care.

Background: Previous studies have identified hospitals with poor performance on cardiac process measures. How these hospitals fare in other domains, such as patient satisfaction, remains unknown., Methods and Results: We used Hospital Compare data to identify hospitals reporting acute myocardial infarction (AMI) and heart failure (HF) process measures during 2006 to 2008, and calculated respective composite performance scores. Using these scores, we classified hospitals as low-performing (bottom decile for all 3 years), top-performing (top decile for all 3 years), and intermediate (all others). We used Hospital Consumer Assessment of Healthcare Providers and Systems 2008 data to compare overall satisfaction between low, intermediate, and top-performing hospitals. Low-performing hospitals had fewer beds, fewer nurses per patient, and were more likely rural, safety-net hospitals located in the South, compared with intermediate and top-performing hospitals (P<0.01 for all). After adjusting for hospital characteristics, patients were less likely to recommend low-performing hospitals to family or friends, relative to intermediate and top-performing hospitals (AMI: 58.8% versus 63.9% versus 68.8%, HF: 61.3% versus 64.0% versus 66.8%; P<0.001 for all), or provide an overall rating of ≥ 9 out of 10 (AMI: 56.7% versus 60.7% versus 64.9%, HF: 57.8% versus 61.1% versus 63.6%; P<0.01 for all). Despite the association between the hospital's performance on process measures and patient satisfaction, we noted discordance between these measures (kappa statistic <0.20)., Conclusions: Hospitals with consistently poor performance on cardiac process measures also have lower patient satisfaction on average, suggesting that these hospitals have overall poor quality of care. However, there is discordance between the 2 measures in profiling hospital quality.