Empirical use of causal inference methods to evaluate survival differences in a real-world registry vs those found in randomized clinical trials.

With heighted interest in causal inference based on real-world evidence, this empirical study sought to understand differences between the results of observational analyses and long-term randomized clinical trials. We hypothesized that patients deemed "eligible" for clinical trials would follow a different survival trajectory from those deemed "ineligible" and that this factor could partially explain results. In a large observational registry dataset, we estimated separate survival trajectories for hypothetically trial-eligible vs ineligible patients under both coronary artery bypass surgery (CABG) and percutaneous coronary intervention (PCI). We also explored whether results would depend on the causal inference method (inverse probability of treatment weighting vs optimal full propensity matching) or the approach to combine propensity scores from multiple imputations (the "across" vs "within" approaches). We found that, in this registry population of PCI/CABG multivessel patients, 32.5% would have been eligible for contemporaneous RCTs, suggesting that RCTs enroll selected populations. Additionally, we found treatment selection bias with different distributions of propensity scores between PCI and CABG patients. The different methodological approaches did not result in different conclusions. Overall, trial-eligible patients appeared to demonstrate at least marginally better survival than ineligible patients. Treatment comparisons by eligibility depended on disease severity. Among trial-eligible three-vessel diseased and trial-ineligible two-vessel diseased patients, CABG appeared to have at least a slight advantage with no treatment difference otherwise. In conclusion, our analyses suggest that RCTs enroll highly selected populations, and our findings are generally consistent with RCTs but less pronounced than major registry findings.

I-CARE randomized clinical trial integrating depression and acute coronary syndrome care in low-resource hospitals in China: Design and rationale.

Depression and acute coronary syndromes (ACS) are both common public health challenges. Patients with ACS often develop depression, which in turn adversely affects prognosis. Low-cost, sustainable, and effective service models that integrate depression care into the management of ACS patients to reduce depression and improve ACS outcomes are critically needed. Integrating Depression Care in ACS patients in Low Resource Hospitals in China (I-CARE) is a multicenter, randomized controlled trial to evaluate the efficacy of an 11-month integrated care (IC) intervention compared to usual care (UC) in management of ACS patients. Four thousand inpatients will be recruited and then randomized in a 1:1 ratio to an IC intervention consisting of nurse-led risk factor management, group-based counseling supplemented by individual problem-solving therapy, and antidepressant medications as needed, or to UC. The primary outcomes are depression symptoms measured by the Patient Health Questionnaire-9 at 6 and 12 months. Secondary endpoints include anxiety measured by the Generalized Anxiety Disorder-7; quality of life measured by the EQ-5D at 6 and 12 months; and major adverse events including the combined end point of all-cause death, suicide attempts, nonfatal myocardial infarction, nonfatal stroke, and all-cause rehospitalization at yearly intervals for a median follow-up of 2 years. Analyses of the cost-effectiveness and cost-utility of IC also will be performed. I-CARE trial will be the largest study to test the effectiveness of an integrated care model on depression and cardiovascular outcomes among ACS patients in resource-limited clinical settings.

An evaluation of constrained randomization for the design and analysis of group-randomized trials with binary outcomes.

Group-randomized trials are randomized studies that allocate intact groups of individuals to different comparison arms. A frequent practical limitation to adopting such research designs is that only a limited number of groups may be available, and therefore, simple randomization is unable to adequately balance multiple group-level covariates between arms. Therefore, covariate-based constrained randomization was proposed as an allocation technique to achieve balance. Constrained randomization involves generating a large number of possible allocation schemes, calculating a balance score that assesses covariate imbalance, limiting the randomization space to a prespecified percentage of candidate allocations, and randomly selecting one scheme to implement. When the outcome is binary, a number of statistical issues arise regarding the potential advantages of such designs in making inference. In particular, properties found for continuous outcomes may not directly apply, and additional variations on statistical tests are available. Motivated by two recent trials, we conduct a series of Monte Carlo simulations to evaluate the statistical properties of model-based and randomization-based tests under both simple and constrained randomization designs, with varying degrees of analysis-based covariate adjustment. Our results indicate that constrained randomization improves the power of the linearization F-test, the KC-corrected GEE t-test (Kauermann and Carroll, 2001, Journal of the American Statistical Association 96, 1387-1396), and two permutation tests when the prognostic group-level variables are controlled for in the analysis and the size of randomization space is reasonably small. We also demonstrate that constrained randomization reduces power loss from redundant analysis-based adjustment for non-prognostic covariates. Design considerations such as the choice of the balance metric and the size of randomization space are discussed.

An evaluation of constrained randomization for the design and analysis of group-randomized trials.

In group-randomized trials, a frequent practical limitation to adopting rigorous research designs is that only a small number of groups may be available, and therefore, simple randomization cannot be relied upon to balance key group-level prognostic factors across the comparison arms. Constrained randomization is an allocation technique proposed for ensuring balance and can be used together with a permutation test for randomization-based inference. However, several statistical issues have not been thoroughly studied when constrained randomization is considered. Therefore, we used simulations to evaluate key issues including the following: the impact of the choice of the candidate set size and the balance metric used to guide randomization; the choice of adjusted versus unadjusted analysis; and the use of model-based versus randomization-based tests. We conducted a simulation study to compare the type I error and power of the F-test and the permutation test in the presence of group-level potential confounders. Our results indicate that the adjusted F-test and the permutation test perform similarly and slightly better for constrained randomization relative to simple randomization in terms of power, and the candidate set size does not substantially affect their power. Under constrained randomization, however, the unadjusted F-test is conservative, while the unadjusted permutation test carries the desired type I error rate as long as the candidate set size is not too small; the unadjusted permutation test is consistently more powerful than the unadjusted F-test and gains power as candidate set size changes. Finally, we caution against the inappropriate specification of permutation distribution under constrained randomization. An ongoing group-randomized trial is used as an illustrative example for the constrained randomization design.

Statistical lessons learned for designing cluster randomized pragmatic clinical trials from the NIH Health Care Systems Collaboratory Biostatistics and Design Core.

BACKGROUND/AIMS: Pragmatic clinical trials embedded within health care systems provide an important opportunity to evaluate new interventions and treatments. Networks have recently been developed to support practical and efficient studies. Pragmatic trials will lead to improvements in how we deliver health care and promise to more rapidly translate research findings into practice. METHODS: The National Institutes of Health (NIH) Health Care Systems Collaboratory was formed to conduct pragmatic clinical trials and to cultivate collaboration across research areas and disciplines to develop best practices for future studies. Through a two-stage grant process including a pilot phase (UH2) and a main trial phase (UH3), investigators across the Collaboratory had the opportunity to work together to improve all aspects of these trials before they were launched and to address new issues that arose during implementation. Seven Cores were created to address the various considerations, including Electronic Health Records; Phenotypes, Data Standards, and Data Quality; Biostatistics and Design Core; Patient-Reported Outcomes; Health Care Systems Interactions; Regulatory/Ethics; and Stakeholder Engagement. The goal of this article is to summarize the Biostatistics and Design Core's lessons learned during the initial pilot phase with seven pragmatic clinical trials conducted between 2012 and 2014. RESULTS: Methodological issues arose from the five cluster-randomized trials, also called group-randomized trials, including consideration of crossover and stepped wedge designs. We outlined general themes and challenges and proposed solutions from the pilot phase including topics such as study design, unit of randomization, sample size, and statistical analysis. Our findings are applicable to other pragmatic clinical trials conducted within health care systems. CONCLUSION: Pragmatic clinical trials using the UH2/UH3 funding mechanism provide an opportunity to ensure that all relevant design issues have been fully considered in order to reliably and efficiently evaluate new interventions and treatments. The integrity and generalizability of trial results can only be ensured if rigorous designs and appropriate analysis choices are an essential part of their research protocols.

Population impact of a high cardiovascular risk management program delivered by village doctors in rural China: design and rationale of a large, cluster-randomized controlled trial.

BACKGROUND: The high-risk strategy has been proven effective in preventing cardiovascular disease; however, the population benefits from these interventions remain unknown. This study aims to assess, at the population level, the effects of an evidence-based high cardiovascular risk management program delivered by village doctors in rural China. METHODS: The study will employ a cluster-randomized controlled trial in which a total of 120 villages in five northern provinces of China, will be assigned to either intervention (60 villages) or control (60 villages). Village doctors in intervention villages will be trained to implement a simple evidence-based management program designed to identify, treat and follow-up as many as possible individuals at high-risk of cardiovascular disease in the village. The intervention will also include performance feedback as well as a performance-based incentive payment scheme and will last for 2 years. We will draw two different (independent) random samples, before and after the intervention, 20 men aged≥50 years and 20 women aged≥60 years from each village in each sample and a total of 9,600 participants from 2 samples to measure the study outcomes at the population level. The primary outcome will be the pre-post difference in mean systolic blood pressure, analyzed with a generalized estimating equations extension of linear regression model to account for cluster effect. Secondary outcomes will include monthly clinic visits, provision of lifestyle advice, use of antihypertensive medications and use of aspirin. Process and economic evaluations will also be conducted. DISCUSSION: This trial will be the first implementation trial in the world to evaluate the population impact of the high-risk strategy in prevention and control of cardiovascular disease. The results are expected to provide important information (effectiveness, cost-effectiveness, feasibility and acceptability) to guide policy making for rural China as well as other resource-limited countries. TRIAL REGISTRATION: The trial is registered at ClinicalTrials.gov (NCT01259700). Date of initial registration is December 13, 2010.

Prediction of long-term mortality after percutaneous coronary intervention in older adults: results from the National Cardiovascular Data Registry.

BACKGROUND: The purpose of this study was to develop a long-term model to predict mortality after percutaneous coronary intervention in both patients with ST-segment elevation myocardial infarction and those with more stable coronary disease. METHODS AND RESULTS: The American College of Cardiology Foundation CathPCI Registry data were linked to the Centers for Medicare and Medicaid Services 100% denominator file by probabilistic matching. Preprocedure demographic and clinical variables from the CathPCI Registry were used to predict the probability of death over 3 years as recorded in the Centers for Medicare and Medicaid Services database. Between 2004 and 2007, 343 466 patients (66%) of 518 195 patients aged ≥65 years undergoing first percutaneous coronary intervention in the CathPCI Registry were successfully linked to Centers for Medicare and Medicaid Services data. This study population was randomly divided into 60% derivation and 40% validation cohorts. Median follow-up was 15 months, with mortality of 3.0% at 30 days and 8.7%, 13.4%, and 18.7% at 1, 2, and 3 years, respectively. Twenty-four characteristics related to demographics, clinical comorbidity, prior history of disease, and indices of disease severity and acuity were identified as being associated with mortality. The C indices in the validation cohorts for patients with and without ST-segment elevation myocardial infarction were 0.79 and 0.78. The model calibrated well across a wide range of predicted probabilities. CONCLUSIONS: On the basis of the large and nationally representative CathPCI Registry, we have developed a model that has excellent discrimination, calibration, and validation to predict survival up to 3 years after percutaneous coronary intervention.

Predictors of long-term survival after coronary artery bypass grafting surgery: results from the Society of Thoracic Surgeons Adult Cardiac Surgery Database (the ASCERT study).

BACKGROUND: Most survival prediction models for coronary artery bypass grafting surgery are limited to in-hospital or 30-day end points. We estimate a long-term survival model using data from the Society of Thoracic Surgeons Adult Cardiac Surgery Database and Centers for Medicare and Medicaid Services. METHODS AND RESULTS: The final study cohort included 348 341 isolated coronary artery bypass grafting patients aged ≥65 years, discharged between January 1, 2002, and December 31, 2007, from 917 Society of Thoracic Surgeons-participating hospitals, randomly divided into training (n=174 506) and validation (n=173 835) samples. Through linkage with Centers for Medicare and Medicaid Services claims data, we ascertained vital status from date of surgery through December 31, 2008 (1- to 6-year follow-up). Because the proportional hazards assumption was violated, we fit 4 Cox regression models conditional on being alive at the beginning of the following intervals: 0 to 30 days, 31 to 180 days, 181 days to 2 years, and >2 years. Kaplan-Meier-estimated mortality was 3.2% at 30 days, 6.4% at 180 days, 8.1% at 1 year, and 23.3% at 3 years of follow-up. Harrell's C statistic for predicting overall survival time was 0.732. Some risk factors (eg, emergency status, shock, reoperation) were strong predictors of short-term outcome but, for early survivors, became nonsignificant within 2 years. The adverse impact of some other risk factors (eg, dialysis-dependent renal failure, insulin-dependent diabetes mellitus) continued to increase. CONCLUSIONS: Using clinical registry data and longitudinal claims data, we developed a long-term survival prediction model for isolated coronary artery bypass grafting. This provides valuable information for shared decision making, comparative effectiveness research, quality improvement, and provider profiling.

Secondary prevention after coronary artery bypass graft surgery: findings of a national randomized controlled trial and sustained society-led incorporation into practice.

BACKGROUND: Despite evidence supporting the use of aspirin, ß-blockers, angiotensin-converting enzyme inhibitors, and lipid-lowering therapies in eligible patients, adoption of these secondary prevention measures after coronary artery bypass grafting has been inconsistent. We sought to rigorously test on a national scale whether low-intensity continuous quality improvement interventions can be used to speed secondary prevention adherence after coronary artery bypass grafting. METHODS AND RESULTS: A total of 458 hospitals participating in the Society of Thoracic Surgeons National Cardiac Database and treating 361 328 patients undergoing isolated coronary artery bypass grafting were randomized to either a control or an intervention group. The intervention group received continuous quality improvement materials designed to influence the prescription of the secondary prevention medications at discharge. The primary outcome measure was discharge prescription rates of the targeted secondary prevention medications at intervention versus control sites, assessed by measuring preintervention and postintervention site differences. Prerandomization treatment patterns and baseline data were similar in the control (n=234) and treatment (n=224) groups. Individual medication use and composite adherence increased over 24 months in both groups, with a markedly more rapid rate of adherence uptake among the intervention hospitals and a statistically significant therapy hazard ratio in the intervention versus control group for all 4 secondary prevention medications. CONCLUSIONS: Provider-led, low-intensity continuous quality improvement efforts can improve the adoption of care processes into national practice within the context of a medical specialty society infrastructure. The findings of the present trial have led to the incorporation of study outcome metrics into a medical society rating system for ongoing quality improvement.

ACCF/AHA methodology for the development of quality measures for cardiovascular technology: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Performance Measures.

Consistent with the growing national focus on healthcare quality, the American College of Cardiology Foundation (ACCF) and the American Heart Association (AHA) have taken a leadership role over the past decade in developing measures of the quality of cardiovascular care by convening a joint ACCF/AHA Task Force on Performance Measures. The Task Force is charged with identifying the clinical topics appropriate for the development of performance measures and with assembling writing committees composed of clinical and methodological experts in collaboration with appropriate subspecialty societies. The Task Force has also created methodology documents that offer guidance in the development of process, outcome, composite, and efficiency measures. Cardiovascular performance measures using existing ACCF/AHA methodology are based on Class I or Class III guidelines recommendations, usually with Level A evidence. These performance measures, based on evidence-based ACCF/AHA guidelines, remain the most rigorous quality measures for both internal quality improvement and public reporting. However, many of the tools for diagnosis and treatment of cardiovascular disease involve advanced technologies, such as cardiac imaging, for which there are often no underlying guideline documents. Because these technologies affect the quality of cardiovascular care and also have the potential to contribute to cardiovascular health expenditures, there is a need for more critical assessment of the use of technology, including the development of quality and performance measures in areas in which guideline recommendations are absent. The evaluation of quality in the use of cardiovascular technologies requires consideration of multiple parameters that differ from other healthcare processes. The present document describes methodology for development of 2 new classes of quality measures in these situations, appropriate use measures and structure/safety measures. Appropriate use measures are based on specific indications, processes, or parameters of care for which high level of evidence data and Class I or Class III guideline recommendations may be lacking but are addressed in ACCF appropriate use criteria documents. Structure/safety measures represent measures developed to address structural aspects of the use of healthcare technology (e.g., laboratory accreditation, personnel training, and credentialing) or quality issues related to patient safety when there are neither guidelines recommendations nor appropriate use criteria. Although the strength of evidence for appropriate use measures and structure/safety measures may not be as strong as that for formal performance measures, they are quality measures that are otherwise rigorously developed, reviewed, tested, and approved in the same manner as ACCF/AHA performance measures. The ultimate goal of the present document is to provide direction in defining and measuring the appropriate use-avoiding not only underuse but also overuse and misuse-and proper application of cardiovascular technology and to describe how such appropriate use measures and structure/safety measures might be developed for the purposes of quality improvement and public reporting. It is anticipated that this effort will help focus the national dialogue on the use of cardiovascular technology and away from the current concerns about volume and cost alone to a more holistic emphasis on value.

Reclassification of cardiovascular risk using integrated clinical and molecular biosignatures: Design of and rationale for the Measurement to Understand the Reclassification of Disease of Cabarrus and Kannapolis (MURDOCK) Horizon 1 Cardiovascular Disease Study.

BACKGROUND: Clinical predictive models leave gaps in our ability to stratify cardiovascular risk. High-throughput molecular profiling promises to improve risk classification. METHODS: Horizon 1 of the Measurement to Understand the Reclassification of Disease of Cabarrus and Kannapolis (MURDOCK) Study was conceived to apply emerging molecular techniques to existing data sets to characterize mechanistic diversity underlying complex human diseases, response to therapy, and prognosis. No previous studies have applied multiple, complementary molecular techniques in combination with well-developed clinical risk models to refine cardiovascular risk prediction. The MURDOCK Cardiovascular Disease Study will assess molecular profiles integrated with clinical data in "clinomic" profiles for cardiovascular risk classification. CONCLUSION: Herein, we describe the design of and rationale for the MURDOCK Cardiovascular Disease Study.

ACC/AHA classification of care metrics: performance measures and quality metrics: a report of the American College of Cardiology/American Heart Association Task Force on Performance Measures.

The American College of Cardiology (ACC) and the American Heart Association (AHA) have provided leadership in enhancing the quality of cardiovascular care, including the development of clinical performance measures and clinical registries that permit the evaluation of quality of care and stimulate quality improvement. Compliance with ACC/AHA performance measures and metrics encourages the provision of the strongest evidence-based quality of care, including therapies that are life-extending or life-enhancing. Among quality metrics, only a subset should be considered performance measures-that is, those measures specifically suitable for public reporting, external comparisons, and possibly pay-for-performance programs, in addition to quality improvement. These performance measures have been developed using ACC/AHA methodology, often in collaboration with other organizations, and include the process of public comment and peer review. Quality metrics are those measures that have been developed to support self assessment and quality improvement at the provider, hospital, and/or health care system level. These metrics represent valuable tools to aid clinicians and hospitals in improving quality of care and enhancing patient outcomes, but may not meet all specifications of formal performance measures. These quality metrics may also be considered "candidate" measures that with further research or field testing would meet the criteria for formal performance measures in the future. This measure classification is intended to aid providers, hospitals, health systems, and payers in identifying those measures that the ACC and AHA formally endorse as performance measures, while at the same time promoting the broader range of clinical metrics that are useful for quality improvement efforts.

Exploring the behavior of hospital composite performance measures: an example from coronary artery bypass surgery.

BACKGROUND: Composite scores that combine several performance measures into a single ranking are becoming the accepted metric for assessing hospital performance. In particular, the Centers for Medicare & Medicaid Services Hospital Quality Incentive Demonstration (HQID) project bases financial rewards and penalties on these scores. Although the HQID composite calculation is straightforward and easily understood, its method of combining process and outcome measures has not been validated. METHODS AND RESULTS: Using data on 530 hospitals from the Society of Thoracic Surgeons National Cardiac Database, we replicated the HQID methodology with 6 nationally endorsed performance measures (5 process measures plus survival) for coronary artery bypass surgery. Composite scores were essentially determined by process measure performance alone; the survival component explained only 4% of the composite score's total variance. This result persisted even when the survival component was allowed a 5-fold greater weighting in the composite summary. The popular "all-or-none" measurement approach was also dominated by the process component. Substantial disagreement was found among hospital rankings when several alternative methods were used; up to 60% of hospitals eligible for the top financial reward under HQID would change designation depending on the composite methodology used. The application of a simple statistical adjustment (standardization) to each method would provide more consistent results and a more balanced assessment of performance based on both process and outcomes. CONCLUSIONS: Existing methods used to create composite performance measures have remarkably different weighting of process versus outcomes metrics and lead to highly divergent provider rankings. Simple alternative methods can create more balanced process-outcome performance assessments.

Patterns of transfer for patients with non-ST-segment elevation acute coronary syndrome from community to tertiary care hospitals.

BACKGROUND: Practice guidelines for non-ST-segment elevation acute coronary syndromes (NSTE ACS) recommend early invasive management (cardiac catheterization and revascularization within 48 hours of hospital presentation) for high-risk patients, but interhospital transfer is necessary to provide rapid access to revascularization procedures for patients who present to community hospitals without revascularization capabilities. METHODS: We analyzed patterns and factors associated with interhospital transfer among 19,238 patients with NSTE ACS (positive cardiac markers and/or ischemic ST-segment changes) from 124 community hospitals without revascularization capabilities in the Can Rapid risk stratification of Unstable angina patients Suppress ADverse outcomes with Early implementation of the ACC/AHA Guidelines quality improvement initiative from January 2001 through June 2004. RESULTS: Less than half of the patients (46.3%) admitted to community hospitals were transferred to tertiary hospitals, and fewer (20%) were transferred early (within 48 hours of presentation). Early transfer rates increased by 16% over 10 quarters in patients with a predicted low or moderate risk of inhospital mortality, compared with 5% in high-risk patients. By the last quarter of the analysis, 41.4% of low-risk patients were transferred early versus 12.5% of high-risk patients. Factors significantly associated with early transfer included younger age, lack of prior heart failure, cardiology inpatient care, and ischemic ST-segment electrocardiographic changes. Among patients who were not transferred, 29% had no further risk stratification performed with stress testing, ejection fraction measurement, or diagnostic cardiac catheterization (at hospitals with catheterization laboratories). CONCLUSIONS: Most patients with NSTE ACS presenting to community hospitals without revascularization capabilities are not rapidly transferred to tertiary hospitals, and lower-risk patients appear to be preferentially transferred early. Further investigation is needed to determine if improved risk-based triage at community hospitals can optimize transfer decision making for high-risk patients with NSTE ACS.

Strategies for analyzing multilevel cluster-randomized studies with binary outcomes collected at varying intervals of time.

Frequently, studies are conducted in a real clinic setting. When the outcome of interest is collected longitudinally over a specified period of time, this design can lead to unequally spaced intervals and varying numbers of assessments. In our study, these features were embedded in a randomized, factorial design in which interventions to improve blood pressure control were delivered to both patients and providers. We examine the effect of the intervention and compare methods of estimation of both fixed effects and variance components in the multilevel generalized linear mixed model. Methods of comparison include penalized quasi-likelihood (PQL), adaptive quadrature, and Bayesian Monte Carlo methods. We also investigate the implications of reducing the data and analysis to baseline and final measurements. In the full analysis, the PQL fixed-effects estimates were closest to zero and confidence intervals were generally narrower than those of the other methods. The adaptive quadrature and Bayesian fixed-effects estimates were similar, but the Bayesian credible intervals were consistently wider. Variance component estimation was markedly different across methods, particularly for the patient-level random effects. In the baseline and final measurement analysis, we found that estimates and corresponding confidence intervals for the adaptive quadrature and Bayesian methods were very similar. However, the time effect was diminished and other factors also failed to reach statistical significance, most likely due to decreased power. When analyzing data from this type of design, we recommend using either adaptive quadrature or Bayesian methods to fit a multilevel generalized linear mixed model including all available measurements.

Long-term adherence to evidence-based secondary prevention therapies in coronary artery disease.

BACKGROUND: Studies have examined the use of evidence-based therapies for coronary artery disease (CAD) in the short term and at hospital discharge, but few have evaluated long-term use. METHODS AND RESULTS: Using the Duke Databank for Cardiovascular Disease for the years 1995 to 2002, we determined the annual prevalence and consistency of self-reported use of aspirin, beta-blockers, lipid-lowering agents, and their combinations in all CAD patients and of angiotensin-converting enzyme inhibitors (ACEIs) in those with and without heart failure. Logistic-regression models identified characteristics associated with consistent use (reported on > or =2 consecutive follow-up surveys and then through death, withdrawal, or study end), and Cox proportional-hazards models explored the association of consistent use with mortality. Use of all agents and combinations thereof increased yearly. In 2002, 83% reported aspirin use; 61%, beta-blocker use; 63%, lipid-lowering therapy use; 54%, aspirin and beta-blocker use; and 39%, use of all 3. Consistent use was as follows: For aspirin, 71%; beta-blockers, 46%; lipid-lowering therapy, 44%; aspirin and beta-blockers, 36%; and all 3, 21%. Among patients without heart failure, 39% reported ACEI use in 2002; consistent use was 20%. Among heart failure patients, ACEI use was 51% in 2002 and consistent use, 39%. Except for ACEIs among patients without heart failure, consistent use was associated with lower adjusted mortality: Aspirin hazard ratio (HR), 0.58 and 95% confidence interval (CI), 0.54 to 0.62; beta-blockers, HR, 0.63 and 95% CI, 0.59 to 0.67; lipid-lowering therapy, HR, 0.52 and 95% CI, 0.42 to 0.65; all 3, HR, 0.67 and 95% CI, 0.59 to 0.77; aspirin and beta-blockers, HR, 0.61 and 95% CI, 0.57 to 0.65; and ACEIs among heart failure patients, HR, 0.75 and 95% CI, 0.67 to 0.84. CONCLUSIONS: Use of evidence-based therapies for CAD has improved but remains suboptimal. Although improved discharge prescription of these agents is needed, considerable attention must also be focused on understanding and improving long-term adherence.

Insurance coverage and care of patients with non-ST-segment elevation acute coronary syndromes.

BACKGROUND: The impact of insurance coverage on the care of patients with non-ST-segment elevation acute coronary syndromes (NSTE ACS) is unclear. OBJECTIVE: To compare NSTE ACS care patterns by insurance type. DESIGN: Comparison of Medicaid patients younger than 65 years of age and Medicare patients 65 years of age or older with patients of similar age who have health maintenance organization (HMO) or private insurance coverage. SETTING: 521 U.S. hospitals participating in the CRUSADE (Can Rapid Risk Stratification of Unstable Angina Patients Suppress ADverse Outcomes with Early Implementation of the ACC [American College of Cardiology]/AHA [American Heart Association] Guidelines) quality improvement initiative from January 2001 through March 2005. PATIENTS: 37,345 NSTE ACS patients younger than 65 years of age and 59,550 patients 65 years of age or older. MEASUREMENTS: Guideline-recommended treatments, and in-hospital outcomes. RESULTS: Medicaid was the primary payer for 18.7% (6999 of 37,345) of patients younger than age 65 years, whereas Medicare was the primary payer for 67.5% (40,199 of 59,550) of patients age 65 years or older. Medicaid patients were statistically significantly less likely to receive short-term (less than 24 hours) medications and to undergo invasive cardiac procedures than patients covered by HMO and private insurance. They also had higher mortality rates (2.9% vs. 1.2%; adjusted odds ratio, 1.33; 95% CI, 1.08 to 1.63). Medications and invasive procedures were used to a similar extent in patients with Medicare and HMO or private insurance, and respective mortality rates were not significantly different (6.2% vs. 5.6%; adjusted odds ratio, 1.08; 95% CI, 0.99 to 1.18). LIMITATIONS: Self-pay patients and patients without insurance were not assessed. CONCLUSIONS: NSTE ACS patients with Medicaid (but not Medicare) as the primary payer were less likely to receive evidence-based therapies and had worse outcomes than patients with HMO or private insurance as the primary payer. The causes of these treatment differences and solutions for narrowing the gaps in quality require further investigation.

Pay for performance, quality of care, and outcomes in acute myocardial infarction.

CONTEXT: Pay for performance has been promoted as a tool for improving quality of care. In 2003, the Centers for Medicare & Medicaid Services (CMS) launched the largest pay-for-performance pilot project to date in the United States, including indicators for acute myocardial infarction. OBJECTIVE: To determine if pay for performance was associated with either improved processes of care and outcomes or unintended consequences for acute myocardial infarction at hospitals participating in the CMS pilot project. DESIGN, SETTING, AND PARTICIPANTS: An observational, patient-level analysis of 105,383 patients with acute non-ST-segment elevation myocardial infarction enrolled in the Can Rapid Risk Stratification of Unstable Angina Patients Suppress Adverse Outcomes With Early Implementation of the American College of Cardiology/American Heart Association (ACC/AHA) Guidelines (CRUSADE) national quality-improvement initiative. Patients were treated between July 1, 2003, and June 30, 2006, at 54 hospitals in the CMS program and 446 control hospitals. MAIN OUTCOME MEASURES: The differences in the use of ACC/AHA class I guideline recommended therapies and in-hospital mortality between pay for performance and control hospitals. RESULTS: Among treatments subject to financial incentives, there was a slightly higher rate of improvement for 2 of 6 targeted therapies at pay-for-performance vs control hospitals (odds ratio [OR] comparing adherence scores from 2003 through 2006 at half-year intervals for aspirin at discharge, 1.31; 95% confidence interval [CI], 1.18-1.46 vs OR, 1.17; 95% CI, 1.12-1.21; P = .04) and for smoking cessation counseling (OR, 1.50; 95% CI, 1.29-1.73 vs OR, 1.28; 95% CI, 1.22-1.35; P = .05). There was no significant difference in a composite measure of the 6 CMS rewarded therapies between the 2 hospital groups (change in odds per half-year period of receiving CMS therapies: OR, 1.23; 95% CI, 1.15-1.30 vs OR, 1.17; 95% CI, 1.14-1.20; P = .16). For composite measures of acute myocardial infarction treatments not subject to incentives, rates of improvement were not significantly different (OR, 1.09; 95% CI, 1.05-1.14 vs OR, 1.08; 95% CI, 1.06-1.09; P = .49). Overall, there was no evidence that improvements in in-hospital mortality were incrementally greater at pay-for-performance sites (change in odds of in-hospital death per half-year period, 0.91; 95% CI, 0.84-0.99 vs 0.97; 95% CI, 0.94-0.99; P = .21). CONCLUSIONS: Among hospitals participating in a voluntary quality-improvement initiative, the pay-for-performance program was not associated with a significant incremental improvement in quality of care or outcomes for acute myocardial infarction. Conversely, we did not find evidence that pay for performance had an adverse association with improvement in processes of care that were not subject to financial incentives. Additional studies of pay for performance are needed to determine its optimal role in quality-improvement initiatives.

Influence of racial disparities in procedure use on functional status outcomes among patients with coronary artery disease.

BACKGROUND: Although black cardiac patients receive fewer revascularization procedures than whites, it is unclear whether this has a detrimental impact on outcomes. The objective of our study was to compare 6-month functional status and angina outcomes among blacks and whites with documented coronary disease and to assess whether differential use of revascularization procedures affects these outcomes. METHODS AND RESULTS: We identified a prospective cohort of 1534 white and 337 black patients undergoing cardiac catheterization between August 1998 and April 2001. Health status was assessed at baseline and 6 months with the Short-Form 36 (SF-36) Health Survey and the Seattle Angina Questionnaire (SAQ) Angina Frequency Scale. Compared with whites, blacks received fewer coronary revascularization procedures (52.5% versus 66.0%; P<0.01). By 6 months, blacks had similar mortality (odds ratio, 1.03; 95% CI, 0.57 to 1.9) but worse scores in 5 SF-36 domains (physical, social, role physical, role emotional, and mental health function). Blacks also reported higher rates of angina at 6 months than whites (34.2% versus 24.6%; P<0.01). After adjustment for baseline functional status and clinical and demographic variables, blacks had significantly worse summary physical component scores, summary mental component scores, and SAQ Angina Frequency Scale scores. However, differences in physical component summary scores and SAQ scores between blacks and whites were no longer significant after adjustment for revascularization status. CONCLUSIONS: Our study is among the first to document greater symptoms and functional impairment among black cardiac patients relative to whites. Differential use of coronary revascularization may contribute to the poorer functional outcomes observed among black patients with documented coronary disease.