BACKGROUND: The Affordable Care Act creates financial incentives for hospitals to minimize readmissions shortly after discharge for several conditions, with percutaneous coronary intervention (PCI) to be a target in 2015. We aimed to develop and validate prediction models to assist clinicians and hospitals in identifying patients at highest risk for 30-day readmission after PCI. METHODS AND RESULTS: We identified all readmissions within 30 days of discharge after PCI in nonfederal hospitals in Massachusetts between October 1, 2005, and September 30, 2008. Within a two-thirds random sample (Developmental cohort), we developed 2 parsimonious multivariable models to predict all-cause 30-day readmission, the first incorporating only variables known before cardiac catheterization (pre-PCI model), and the second incorporating variables known at discharge (Discharge model). Models were validated within the remaining one-third sample (Validation cohort), and model discrimination and calibration were assessed. Of 36,060 PCI patients surviving to discharge, 3760 (10.4%) patients were readmitted within 30 days. Significant pre-PCI predictors of readmission included age, female sex, Medicare or State insurance, congestive heart failure, and chronic kidney disease. Post-PCI predictors of readmission included lack of β-blocker prescription at discharge, post-PCI vascular or bleeding complications, and extended length of stay. Discrimination of the pre-PCI model (C-statistic=0.68) was modestly improved by the addition of post-PCI variables in the Discharge model (C-statistic=0.69; integrated discrimination improvement, 0.009; P<0.001). CONCLUSIONS: These prediction models can be used to identify patients at high risk for readmission after PCI and to target high-risk patients for interventions to prevent readmission.

BACKGROUND: Cardiologists are distributed unevenly across regions of the United States. It is unknown whether patients in regions with fewer cardiologists have worse outcomes after hospitalization for acute myocardial infarction (AMI) or heart failure (HF). METHODS AND RESULTS: Using Medicare administrative claims data from 2010, we examined the relationship between regional density of cardiologists and risk of death after hospitalization for AMI and HF using hospitalizations for pneumonia as a comparison. We defined density as the number of cardiologists divided by population aged≥65 years within hospital referral regions, categorized into quintiles. Among 171 126 admissions for AMI, 352 853 admissions for HF, and 343 053 admissions for pneumonia, we tested associations between density of cardiologists and 30-day and 1-year mortality for each condition. We used 2-level hierarchical logistic regression models that adjusted for characteristics of patients and hospital referral regions. Patients hospitalized for AMI (odds ratios [OR], 1.13; 95% confidence interval [CI], 1.06-1.21) and HF (OR, 1.19; 95% CI, 1.12-1.27) in the lowest quintile of density had modestly higher 30-day mortality risk compared with patients in the highest quintile, unlike patients hospitalized for pneumonia (OR, 1.02; 95% CI, 0.96-1.09). Patients hospitalized for AMI (OR, 1.06; 95% CI, 1.00-1.12) and HF (OR, 1.09; 95% CI, 1.04-1.13) in the lowest quintile had slightly higher 1-year mortality risk, unlike patients hospitalized for pneumonia (OR, 1.00; 95% CI, 0.95-1.05). CONCLUSIONS: Patients hospitalized for AMI and HF in regions with a low density of cardiologists experienced modestly higher 30-day and 1-year mortality risk, unlike patients with pneumonia.

IMPORTANCE: The Centers for Medicare & Medicaid Services publicly reports hospital 30-day, all-cause, risk-standardized mortality rates (RSMRs) and 30-day, all-cause, risk-standardized readmission rates (RSRRs) for acute myocardial infarction, heart failure, and pneumonia. The evaluation of hospital performance as measured by RSMRs and RSRRs has not been well characterized. OBJECTIVE: To determine the relationship between hospital RSMRs and RSRRs overall and within subgroups defined by hospital characteristics. DESIGN, SETTING, AND PARTICIPANTS: We studied Medicare fee-for-service beneficiaries discharged with acute myocardial infarction, heart failure, or pneumonia between July 1, 2005, and June 30, 2008 (4506 hospitals for acute myocardial infarction, 4767 hospitals for heart failure, and 4811 hospitals for pneumonia). We quantified the correlation between hospital RSMRs and RSRRs using weighted linear correlation; evaluated correlations in groups defined by hospital characteristics; and determined the proportion of hospitals with better and worse performance on both measures. MAIN OUTCOME MEASURES: Hospital 30-day RSMRs and RSRRs. RESULTS: Mean RSMRs and RSRRs, respectively, were 16.60% and 19.94% for acute myocardial infarction, 11.17% and 24.56% for heart failure, and 11.64% and 18.22% for pneumonia. The correlations between RSMRs and RSRRs were 0.03 (95% CI, -0.002 to 0.06) for acute myocardial infarction, -0.17 (95% CI, -0.20 to -0.14) for heart failure, and 0.002 (95% CI, -0.03 to 0.03) for pneumonia. The results were similar for subgroups defined by hospital characteristics. Although there was a significant negative linear relationship between RSMRs and RSRRs for heart failure, the shared variance between them was only 2.9% (r2 = 0.029), with the correlation most prominent for hospitals with RSMR <11%. CONCLUSION AND RELEVANCE: Risk-standardized mortality rates and readmission rates were not associated for patients admitted with an acute myocardial infarction or pneumonia and were only weakly associated, within a certain range, for patients admitted with heart failure.

BACKGROUND: Monitoring mental health treatment outcomes for populations requires an understanding as to which patient information is needed in electronic format and is feasible to obtain in routine care. OBJECTIVE: To examine whether bipolar disorder outcomes can be accurately predicted and how much clinical detail is needed to do so. RESEARCH DESIGN, DATA SOURCES, AND PARTICIPANTS: Longitudinal study of bipolar disorder patients treated during 2000 to 2004 in the 19-site Systematic Treatment Enhancement Program for Bipolar Disorder observational study arm (N=3168). Clinical data were obtained at baseline and quarterly for over 1 year. We fit a "gold standard" longitudinal random-effects regression model using a detailed clinical information and estimated the area under the receiver operating characteristic curve (AUC) to predict accuracy using a validation sample. The model was then modified to include patient characteristics feasible in routinely collected electronic data (eg, administrative data). We compared the AUCs for the "limited-detail" and gold standard models, testing for differences between the AUCs using the validation sample. MEASURE: Remission, defined as Montgomery-Asberg Depression Rating Scale score <5 and Young Mania Rating Scale score <4. RESULTS: The gold standard models had baseline AUC=0.80 (95% confidence interval=0.74 to 0.86) and 0.75(0.64 to 0.86) at 1-year follow-up. The predicted accuracies of the limited-detail model were lower at baseline [AUC=0.67(0.60 to 0.75)]; correlated test χ=14.25, P=0.002] and not statistically different from the gold standard model at 1 year [AUC=0.67(0.54-0.80); correlated test χ=2.88, P=0.090]. CONCLUSIONS: Future work is needed to develop clinically accurate and feasible models to predict bipolar disorder outcomes. Clinically detailed and limited models performed similarly for shorter-term prediction at 1-year; however, there is room for improvement in prediction accuracy.

Safety-net hospitals, which include urban hospitals serving large numbers of low-income, uninsured, and otherwise vulnerable populations, have historically faced greater financial strains than hospitals that serve more affluent populations. These strains can affect hospitals' quality of care, perhaps resulting in worse outcomes that are commonly used as indicators of care quality-mortality and readmission rates. We compared risk-standardized rates of both of these clinical outcomes among fee-for-service Medicare beneficiaries admitted for acute myocardial infarction, heart failure, or pneumonia. These beneficiaries were admitted to urban hospitals within Metropolitan Statistical Areas that contained at least one safety-net and at least one non-safety-net hospital. We found that outcomes varied across the urban areas for both safety-net and non-safety-net hospitals for all three conditions. However, mortality and readmission rates were broadly similar, with non-safety-net hospitals outperforming safety-net hospitals on average by less than one percentage point across most conditions. For heart failure mortality, there was no difference between safety-net and non-safety-net hospitals. These findings suggest that safety-net hospitals are performing better than many would have expected.

BACKGROUND: Randomized trials show improved outcomes among acute coronary syndrome patients treated with bivalirudin. The objective of this analysis was to compare clinical and economic outcomes in ST-elevation myocardial infarction (STEMI) patients encountered in routine clinical practice undergoing primary percutaneous coronary intervention (PPCI), treated with bivalirudin or heparin+GP IIb/IIIa receptor inhibitor (heparin+GPI). METHODS AND RESULTS: STEMI admissions from January 1, 2004 through March 31, 2008 among patients receiving PPCI and bivalirudin or heparin+GPI in the Premier hospital database were identified. The probability of receiving bivalirudin was estimated using individual and hospital variables; using propensity scores, each bivalirudin patient was matched to 3 heparin+GPI treated patients. The primary outcome was in-hospital death. Rates of bleeding, transfusion, length of stay, and in-hospital cost were secondary outcomes. There were 59,917 STEMI PPCIs receiving bivalirudin (n=6735) or heparin+GPI (n=53,182). Seventy-nine percent of bivalirudin patients matched, resulting in 21,316 STEMI PPCIs for analysis. Compared with heparin+GPI patients, bivalirudin patients had fewer deaths (3.2% versus 4.0%; P=0.011) and less inpatient bleeding (clinically apparent bleeding [6.9% versus 10.5%, P<0.0001], clinically apparent bleeding with transfusion [1.6% versus 3.0%, P<0.0001], and transfusion [5.9% versus 7.6%, P<0.0001]). Patients receiving bivalirudin had shorter average length of stay (mean 4.3 versus 4.5 days; P<0.0001), with lower in-hospital cost (mean $18,640 versus $19,967 [median $14,462 versus $16,003], P<0.0001). CONCLUSIONS: This large "real-world" retrospective analysis demonstrates that bivalirudin therapy compared with heparin+GPI is associated with a lower rate of inpatient death, inpatient bleeding, and decreased overall in-hospital cost in STEMI patients undergoing PPCI.

In this commentary, we argue that although randomization has many benefits, not all questions we seek to answer fit into a randomized setting. Our argument utilizes the clinical setting of carotid atherosclerosis management where specific clinical questions are answered by using a variety of comparative effectiveness designs. Observational studies should not be ruled out when designing studies to address questions of comparative effectiveness.

BACKGROUND: In-hospital mortality measures, which are widely used to assess hospital quality, are not based on a standardized follow-up period and may systematically favor hospitals with shorter lengths of stay (LOSs). OBJECTIVE: To assess the agreement between performance measures of U.S. hospitals by using risk-standardized in-hospital and 30-day mortality rates. DESIGN: Observational study. SETTING: Nonfederal acute care hospitals in the United States with at least 30 admissions for acute myocardial infarction (AMI), heart failure (HF), and pneumonia from 2004 to 2006. PATIENTS: Medicare fee-for-service patients admitted for AMI, HF, or pneumonia from 2004 to 2006. MEASUREMENTS: The primary outcomes were in-hospital and 30-day risk-standardized mortality rates (RSMRs). RESULTS: Included patients comprised 718,508 admissions to 3135 hospitals for AMI, 1,315,845 admissions to 4209 hospitals for HF, and 1,415,237 admissions to 4498 hospitals for pneumonia. The hospital-level mean patient LOS varied across hospitals for each condition, ranging from 2.3 to 13.7 days for AMI, 3.5 to 11.9 days for HF, and 3.8 to 14.8 days for pneumonia. The mean RSMR differences (30-day RSMR minus in-hospital RSMR) were 5.3% (SD, 1.3) for AMI, 6.0% (SD, 1.3) for HF, and 5.7% (SD, 1.4) for pneumonia; distributions varied widely across hospitals. Performance classifications differed between the in-hospital and 30-day models for 257 hospitals (8.2%) for AMI, 456 (10.8%) for HF, and 662 (14.7%) for pneumonia. Hospital mean LOS was positively correlated with in-hospital RSMRs for all 3 conditions. LIMITATION: Medicare claims data were used for risk adjustment. CONCLUSION: In-hospital mortality measures provide a different assessment of hospital performance than 30-day mortality and are biased in favor of hospitals with shorter LOSs. PRIMARY FUNDING SOURCE: The Centers for Medicare & Medicaid Services and National Heart, Lung, and Blood Institute.

PURPOSE: To compare the performance of U.S. teaching and nonteaching hospitals using a portfolio of contemporary, publicly reported metrics. METHOD: The authors classified acute care general hospitals filing a Medicare Institutional Cost Report according to teaching intensity: nonteaching, teaching, or Council of Teaching Hospitals member. They compared aggregate results across categories for Hospital Compare process compliance, mortality, and readmission rates (acute myocardial infarction [AMI], heart failure, pneumonia); Surgical Care Improvement Project (SCIP) performance; compliance with Leapfrog standards; patient experience; patient services and key technologies; safety (computerized physician order entry, intensive care unit staffing, National Quality Forum safe practices, hospital-acquired conditions); and cost/resource utilization (Medicare-adjusted expense per case; Leapfrog efficiency and resource use standards). RESULTS: Availability of patient services and advanced technologies were associated with teaching intensity (P < .0001), as were most hospital safety metrics. Teaching intensity was favorably associated with SCIP performance, AMI and heart failure process scores, and mortality (P < .0001). It was unfavorably associated with higher AMI and pneumonia readmission rates (P < .0001) and lower scores for individual patient satisfaction measures. Costs per case were similar (P = .4194) across hospital categories after correction for federally allowed adjustments (case mix, wages, and low-income patient care). CONCLUSIONS: Teaching hospitals offer advanced clinical capabilities, educate the next generation of providers, care for disadvantaged urban populations, and are leaders in health care research and innovation. However, many stakeholders may be unaware of an additional value-relatively higher quality and safety in many areas, with similar adjusted costs.

BACKGROUND: The use of coronary artery bypass grafting (CABG) surgery in China is growing, but little is known about hospital-level performance. We sought to characterize the variation in performance across hospitals participating in a national registry in China. METHODS AND RESULTS: The study sample was drawn from the Chinese Cardiac Surgery Registry, a national multicenter database that includes 43 hospitals across 13 provinces and 4 direct-controlled municipalities in China. We assessed consecutive patients undergoing isolated CABG surgery during the period of January 1, 2007, through December 31, 2008. Hierarchical generalized linear models were used to estimate hospital-level risk-standardized in-hospital all-cause mortality rates (RSMR) and major complication rates (RSMCR), which included death, myocardial infarction, reoperation for bleeding, mediastinal infection, stroke, reintubation, and renal failure. Among 8739 patients who underwent isolated CABG surgery, the mean age was 62.2 years (SD=9.2), and 78% were male. Observed in-hospital mortality and complication rates were 2.2% (95% confidence interval [CI], 1.9-2.5%) and 6.6% (95% CI, 6.1-7.1%), respectively. The mean RSMR was 1.9% (SD=1.1), with a range of 0.7-5.8%, and the mean RSMCR was 6.4% (SD=1.5), with a range of 3.8-10.1%. The odds of dying and the odds of having a complication after CABG surgery at a hospital 1 SD below the average relative to a hospital 1 SD above the average were 2.06 (95% CI, 1.40-3.04) and 1.53 (95% CI, 1.31-1.79), respectively. The Eastern region had the lowest RSMR and RSMCR (1.6% and 5.8%, respectively), whereas the Central region had the highest RSMR (2.5%) and the Southern region had the highest RSMCR (7.7%). CONCLUSIONS: Mortality and complication rates after CABG surgery in the Chinese Cardiac Surgery Registry are generally low but vary by hospital and region within China. These results suggest that there are opportunities to improve outcomes in some CABG facilities.

The impact of parity coverage on the quantity of behavioral health services used by enrollees and on the prices of these services was examined in a set of Federal Employees Health Benefit (FEHB) Program plans. After parity implementation, the quantity of services used in the FEHB plans declined in five service categories, compared with plans that did not have parity coverage. The decline was significant for all service types except inpatient care. Because a previous study of the FEHB Program found that total spending on behavioral health services did not increase after parity implementation, it can be inferred that average prices must have increased over the period. The finding of a decline in service use and increase in prices provides an empirical window on what might be expected after implementation of the federal parity law and the parity requirement under the health care reform law.

OBJECTIVE: This study evaluated the effect of race-ethnicity and geography on the adoption of a pharmacological innovation (long-acting injectable risperidone [LAIR]) among Medicaid beneficiaries with schizophrenia as well as the contribution of geographic location to observed racial-ethnic disparities. METHODS: The data source was a claims data set from the Florida Medicaid program for the 2.5-year period that followed the launch of LAIR in the U.S. market. Study participants were beneficiaries with schizophrenia who had filled at least one antipsychotic prescription during the study period. The outcome variable was any use of LAIR; model variables were need indicators and random effects for 11 Medicaid areas, which are multicounty units used by the Medicaid program to administer benefits. Adjusted probability of use of LAIR for blacks and Latinos versus whites was estimated with logistic regression models. RESULTS: The study cohort included 13,992 Medicaid beneficiaries: 25% of the cohort was black, 37% Latino, and 38% white. Unadjusted probability of LAIR use was lower for Latinos than whites, and use varied across the state's geographic areas. Adjustment for need confirmed the unadjusted finding of a disparity between Latinos and whites (odds ratio=.58, 95% confidence interval=.49-.70). The inclusion of geographic location in the model eliminated the Latino-white disparity but confirmed the unadjusted finding of geographic variation in adoption. CONCLUSIONS: Within a state Medicaid program, the initial finding of a disparity between Latinos and whites in adopting LAIR was driven by geographic disparities in adoption rates and the geographic concentration of Latinos in a low-adoption area. Possible contributors and implications of these results are discussed.

OBJECTIVE: To evaluate the clinical outcomes after aortic valve replacement or aortic valve replacement and coronary artery bypass grafting in a large contemporary population, and to determine if outcomes are associated with patient ethnicity and gender status. METHODS: Using the Massachusetts Cardiac Surgery Database, we identified 6809 adults aged 18 years or older who had undergone isolated aortic valve replacement or aortic valve replacement and coronary artery bypass grafting in all non-federal acute-care Massachusetts hospitals from 2002 to 2008. Univariate and multivariate logistic regression analyses were used to identify differences in patient characteristics, major morbidity, and 30-day and 1-year mortality between men (n=4043) and women (n=2766) and between whites (n=6481) and nonwhites (n=328). RESULTS: The unadjusted 30-day mortality rate was 2.6% for the men and 3.1% for the women (P=.296) and 2.8% for whites and 3.7% for nonwhites (P=.342). In adjusted logistic regression models, the 30-day mortality was not different between the female and male patients (odds ratio, 0.88; 95% confidence interval, 0.26-3.02, P=.84) nor between the nonwhites and whites (odds ratio, 1.57; 95% confidence interval, 0.45-5.44; P=.48). The incidence of postoperative stroke was greater in women (3.0% women and 2.2% men, P=.031), and the incidence of postoperative myocardial infarction (10.9% women and 13.6% men; P=.001) and septicemia (1.2% women and 2.0% men; P=.009) was greater in men. CONCLUSIONS: Ethnicity and gender were not associated with greater 30-day and 1-year mortality after aortic valve replacement or aortic valve replacement and coronary artery bypass grafting. Differences in postoperative outcomes were not observed between ethnic groups.

BACKGROUND: Improvements in prevention have led to declines in incidence and mortality of myocardial infarction (MI) in selected populations. However, no studies have examined regional differences in recent trends in MI incidence, and few have examined whether known regional disparities in MI care have narrowed over time. METHODS AND RESULTS: We compared trends in incidence rates of MI, associated procedures and mortality for all US Census Divisions (regions) in Medicare fee-for-service patients between 2000-2008 (292 773 151 patient-years). Two-stage hierarchical models were used to account for patient characteristics and state-level random effects. To assess trends in geographic disparities, we calculated changes in between-state variance for outcomes over time. Although the incidence of MI declined in all regions (P<0.001 for trend for each) between 2000-2008, adjusted rates of decline varied by region (annual declines ranging from 2.9-6.1%). Widening geographic disparities, as measured by percent change of between-state variance from 2000-2008, were observed for MI incidence (37.6% increase, P=0.03) and percutaneous coronary intervention rates (31.4% increase, P=0.06). Significant declines in risk-adjusted 30-day mortality were observed in all regions, with the fastest declines observed in states with higher baseline mortality rates. CONCLUSIONS: In a large contemporary analysis of geographic trends in MI epidemiology, the incidence of MI and associated mortality declined significantly in all US Census Divisions between 2000-2008. Although geographic disparities in MI incidence may have increased, regional differences in MI-associated mortality have narrowed.

OBJECTIVES: This study sought to determine hospital variation in the use of positive inotropic agents in patients with heart failure. BACKGROUND: Clinical guidelines recommend targeted use of positive inotropic agents in highly selected patients, but data are limited and the recommendations are not specific. METHODS: We analyzed data from 376 hospitals including 189,948 hospitalizations for heart failure from 2009 through 2010. We used hierarchical logistic regression models to estimate hospital-level risk-standardized rates of inotrope use and risk-standardized in-hospital mortality rates. RESULTS: The risk-standardized rates of inotrope use ranged across hospitals from 0.9% to 44.6% (median: 6.3%, interquartile range: 4.3% to 9.2%). We identified various hospital patterns based on the type of agents: dobutamine-predominant (29% of hospitals), dopamine-predominant (25%), milrinone-predominant (1%), mixed dobutamine and dopamine pattern (32%), and mixed pattern including all 3 agents (13%). When studying the factors associated with interhospital variation, the best model performance was with the hierarchical generalized linear models that adjusted for patient case mix and an individual hospital effect (receiver operating characteristic curves from 0.77 to 0.88). The intraclass correlation coefficients of the hierarchical generalized linear models (0.113 for any inotrope) indicated that a noteworthy proportion of the observed variation was related to an individual institutional effect. Hospital rates or patterns of use were not associated with differences in length of stay or risk-standardized mortality rates. CONCLUSIONS: We found marked differences in the use of inotropic agents for heart failure patients among a diverse group of hospitals. This variability, occurring in the context of little clinical evidence, indicates an urgent need to define the appropriate use of these medications.

Hospital-wide mortality rates are used as a measure of overall hospital quality. However, their parsimony and apparent simplicity belie significant conceptual and methodological concerns. For many diagnoses included in hospital-wide mortality, the association between short-term mortality and quality of care is not well established. Furthermore, compared with condition-specific or procedure-specific mortality, hospital-wide mortality rates pose greater methodological challenges (ie, eligibility and exclusion criteria, risk adjustment, statistical techniques for aggregating across diagnoses, usability). Many of these result from substantial interprovider heterogeneity in diagnosis frequency, sample sizes, and patient severity. Hospital-wide mortality is problematic as a quality metric for public reporting, although hospitals may elect to use such measures for other purposes. Potential alternative approaches include multidimensional composite metrics or mortality measurement limited to selected conditions and procedures for which the link between hospital mortality and quality is clear, legitimate exclusions are uncommon, and sample sizes, end points, and risk adjustment are adequate.

OBJECTIVE: How the introduction of new pharmaceuticals affects spending for treatment of children with attention-deficit hyperactivity disorder (ADHD) is unknown. This study examined trends in use of pharmaceuticals and their costs among children with ADHD from 1996 to 2005. METHODS: This observational study used annual cohorts of children ages three to 17 with ADHD (N=107,486 unique individuals during the study period) from Florida Medicaid claims to examine ten-year trends in the predicted probability for medication use for children with ADHD with and without psychiatric comorbidities as well as mental health spending and its components. Additional outcome measures included average price per day and average number of days filled for medication classes. RESULTS: Overall, the percentage of children with ADHD treated with ADHD drugs increased from 60% to 63%, and the percentage taking antipsychotics more than doubled, from 8% to 18%. In contrast, rates of antidepressant use declined from 21% to 15%, and alpha agonist use was constant, at 15%. Mental health spending increased 61%, with pharmaceutical spending representing the fastest-rising component (up 192%). Stimulant spending increased 157%, mostly because of increases in price per prescription. Antipsychotic spending increased 588% because of increases in both price and quantity (number of days used). By 2005, long-acting ADHD drugs accounted for over 90% of stimulant spending. CONCLUSIONS: Long-acting ADHD drugs have rapidly replaced short-acting stimulant use among children with ADHD. The use of antipsychotics as a second-tier agent in treating ADHD has overtaken traditional agents such as antidepressants or alpha agonists, suggesting a need for research into the efficacy and side effects of second-generation antipsychotics among children with ADHD.