Healthcare Access for a Diverse Population with Schizophrenia Following the Onset of the COVID-19 Pandemic.

COVID-19 has had a disproportionate impact on the most disadvantaged members of society, including minorities and those with disabling chronic illnesses such as schizophrenia. We examined the pandemic's impacts among New York State's Medicaid beneficiaries with schizophrenia in the immediate post-pandemic surge period, with a focus on equity of access to critical healthcare. We compared changes in utilization of key behavioral health outpatient services and inpatient services for life-threatening conditions between the pre-pandemic and surge periods for White and non-White beneficiaries. We found racial and ethnic differences across all outcomes, with most differences stable over time. The exception was pneumonia admissions-while no differences existed in the pre-pandemic period, Black and Latinx beneficiaries were less likely than Whites to be hospitalized in the surge period despite minorities' heavier COVID-19 disease burden. The emergence of racial and ethnic differences in access to scarce life-preserving healthcare may hold lessons for future crises.

Antipsychotics and the risk of diabetes and death among adults with serious mental illnesses.

BACKGROUND: Individuals with schizophrenia exposed to second-generation antipsychotics (SGA) have an increased risk for diabetes, with aripiprazole purportedly a safer drug. Less is known about the drugs' mortality risk or whether serious mental illness (SMI) diagnosis or race/ethnicity modify these effects. METHODS: Authors created a retrospective cohort of non-elderly adults with SMI initiating monotherapy with an SGA (olanzapine, quetiapine, risperidone, and ziprasidone, aripiprazole) or haloperidol during 2008-2013. Three-year diabetes incidence or all-cause death risk differences were estimated between each drug and aripiprazole, the comparator, as well as effects within SMI diagnosis and race/ethnicity. Sensitivity analyses evaluated potential confounding by indication. RESULTS: 38 762 adults, 65% White and 55% with schizophrenia, initiated monotherapy, with haloperidol least (6%) and quetiapine most (26·5%) frequent. Three-year mortality was 5% and diabetes incidence 9.3%. Compared with aripiprazole, haloperidol and olanzapine reduced diabetes risk by 1.9 (95% CI 1.2-2.6) percentage points, or a 18.6 percentage point reduction relative to aripiprazole users' unadjusted risk (10.2%), with risperidone having a smaller advantage. Relative to aripiprazole users' unadjusted risk (3.4%), all antipsychotics increased mortality risk by 1.1-2.2 percentage points, representing 32.4-64.7 percentage point increases. Findings within diagnosis and race/ethnicity were generally consistent with overall findings. Only quetiapine's higher mortality risk held in sensitivity analyses. CONCLUSIONS: Haloperidol's, olanzapine's, and risperidone's lower diabetes risks relative to aripiprazole were not robust in sensitivity analyses but quetiapine's higher mortality risk proved robust. Findings expand the evidence on antipsychotics' risks, suggesting a need for caution in the use of quetiapine among individuals with SMI.

Significance and Factors Associated with Antipsychotic Polypharmacy Utilization Among Publicly Insured US Adults.

Antipsychotic polypharmacy (APP) lacks evidence of effectiveness in the care of schizophrenia or other disorders for which antipsychotic drugs are indicated, also exposing patients to more risks. Authors assessed APP prevalence and APP association with beneficiary race/ethnicity and payer among publicly-insured adults regardless of diagnosis. Retrospective repeated panel study of fee-for-service (FFS) Medicare, Medicaid, and dually-eligible white, black, and Latino adults residing in California, Georgia, Iowa, Mississippi, Oklahoma, South Dakota, or West Virginia, filling antipsychotic prescriptions between July 2008 and June 2013. Primary outcome was any monthly APP utilization. Across states and payers, 11% to 21% of 397,533 antipsychotic users and 12% to 19% of 9,396,741 person-months had some APP utilization. Less than 50% of person-months had a schizophrenia diagnosis and up to 19% had no diagnosed mental illness. Payer modified race/ethnicity effects on APP utilization only in CA; however, the odds of APP utilization remained lower for minorities than for whites. Elsewhere, the odds varied by race/ethnicity only in OK, with Latinos having lower odds than whites (odds ratio 0.76; 95% confidence interval 0.60-0.96). The odds of APP utilization varied by payer in several study states, with odds generally higher for Dual eligibles, although the differences were generally small; the odds also varied by year (lower at study end). APP was frequently utilized but mostly declined over time. APP utilization patterns varied across states, with no consistent association with race/ethnicity and small payer effects. Greater use of APP-reducing strategies are needed, particularly among non-schizophrenia populations.

Quality of primary health care in China: challenges and recommendations.

China has substantially increased financial investment and introduced favourable policies for strengthening its primary health care system with core responsibilities in preventing and managing chronic diseases such as hypertension and emerging infectious diseases such as coronavirus disease 2019 (COVID-19). However, widespread gaps in the quality of primary health care still exist. In this Review, we aim to identify the causes for this poor quality, and provide policy recommendations. System challenges include: the suboptimal education and training of primary health-care practitioners, a fee-for-service payment system that incentivises testing and treatments over prevention, fragmentation of clinical care and public health service, and insufficient continuity of care throughout the entire health-care system. The following recommendations merit consideration: (1) enhancement of the quality of training for primary health-care physicians, (2) establishment of performance accountability to incentivise high-quality and high-value care; (3) integration of clinical care with the basic public health services, and (4) strengthening of the coordination between primary health-care institutions and hospitals. Additionally, China should consider modernising its primary health-care system through the establishment of a learning health system built on digital data and innovative technologies.

A maximum likelihood approach to power calculations for stepped wedge designs of binary outcomes.

In stepped wedge designs (SWD), clusters are randomized to the time period during which new patients will receive the intervention under study in a sequential rollout over time. By the study's end, patients at all clusters receive the intervention, eliminating ethical concerns related to withholding potentially efficacious treatments. This is a practical option in many large-scale public health implementation settings. Little statistical theory for these designs exists for binary outcomes. To address this, we utilized a maximum likelihood approach and developed numerical methods to determine the asymptotic power of the SWD for binary outcomes. We studied how the power of a SWD for detecting risk differences varies as a function of the number of clusters, cluster size, the baseline risk, the intervention effect, the intra-cluster correlation coefficient, and the time effect. We studied the robustness of power to the assumed form of the distribution of the cluster random effects, as well as how power is affected by variable cluster size. % SWD power is sensitive to neither, in contrast to the parallel cluster randomized design which is highly sensitive to variable cluster size. We also found that the approximate weighted least square approach of Hussey and Hughes (2007, Design and analysis of stepped wedge cluster randomized trials. Contemporary Clinical Trials 28, 182-191) for binary outcomes under-estimates the power in some regions of the parameter spaces, and over-estimates it in others. The new method was applied to the design of a large-scale intervention program on post-partum intra-uterine device insertion services for preventing unintended pregnancy in the first 1.5 years following childbirth in Tanzania, where it was found that the previously available method under-estimated the power.

Hospital-Readmission Risk - Isolating Hospital Effects from Patient Effects.

BACKGROUND: To isolate hospital effects on risk-standardized hospital-readmission rates, we examined readmission outcomes among patients who had multiple admissions for a similar diagnosis at more than one hospital within a given year. METHODS: We divided the Centers for Medicare and Medicaid Services hospital-wide readmission measure cohort from July 2014 through June 2015 into two random samples. All the patients in the cohort were Medicare recipients who were at least 65 years of age. We used the first sample to calculate the risk-standardized readmission rate within 30 days for each hospital, and we classified hospitals into performance quartiles, with a lower readmission rate indicating better performance (performance-classification sample). The study sample (identified from the second sample) included patients who had two admissions for similar diagnoses at different hospitals that occurred more than 1 month and less than 1 year apart, and we compared the observed readmission rates among patients who had been admitted to hospitals in different performance quartiles. RESULTS: In the performance-classification sample, the median risk-standardized readmission rate was 15.5% (interquartile range, 15.3 to 15.8). The study sample included 37,508 patients who had two admissions for similar diagnoses at a total of 4272 different hospitals. The observed readmission rate was consistently higher among patients admitted to hospitals in a worse-performing quartile than among those admitted to hospitals in a better-performing quartile, but the only significant difference was observed when the patients were admitted to hospitals in which one was in the best-performing quartile and the other was in the worst-performing quartile (absolute difference in readmission rate, 2.0 percentage points; 95% confidence interval, 0.4 to 3.5; P=0.001). CONCLUSIONS: When the same patients were admitted with similar diagnoses to hospitals in the best-performing quartile as compared with the worst-performing quartile of hospital readmission performance, there was a significant difference in rates of readmission within 30 days. The findings suggest that hospital quality contributes in part to readmission rates independent of factors involving patients. (Funded by Yale-New Haven Hospital Center for Outcomes Research and Evaluation and others.).

Medication Utilization for Alcohol Use Disorder in a Commercially Insured Population.

OBJECTIVE: Examine patterns of alcohol use disorder (AUD) medication use and identify factors associated with prescription fill among commercially insured individuals with an index AUD visit. DESIGN: Using 2008-2018 claims data from a large national insurer, estimate days to first AUD medication using cause-specific hazards approach to account for competing risk of benefits loss. PARTICIPANTS: Aged 17-64 with ≥ 1 AUD visit. MAIN MEASURE: Days to AUD medication fill. KEY RESULTS: A total of 13.3% of the 151,128 with an index visit filled an AUD prescription after that visit, while 69.8% lost benefits before filling and 17.0% remained enrolled but did not fill (median days observed = 305). Almost half (46.3%) of those who filled a prescription received substance use disorder (SUD) inpatient care within 7 days before the fill, and 63.4% received SUD outpatient care. Likelihood of medication use was higher for those aged 26-35, 36-45, and 46-55 years relative to 56-64 years (e.g., 26-35: hazard ratio = 1.29 [95% confidence interval 1.23-1.36]); those diagnosed with moderate/severe AUD (2.05 [1.98-2.12]), co-occurring opioid use disorder (OUD) (1.33 [1.26-1.39]), or severe mental illness (1.31 [1.27-1.35]); those with a chronic alcohol-related diagnosis (1.08 [1.04-1.12]); and those whose index visit was in an inpatient/emergency department (1.27 [1.23-1.31]) or intermediate care setting (1.13 [1.07-1.20]) relative to outpatient. Likelihood of use was higher in later years relative to 2008 (e.g., 2018:2.02 [1.89-2.15]) and higher for those who received the majority of AUD care in a practice with a psychiatrist/addiction medicine specialist (1.13 [1.10-1.16]). Likelihood of use was lower for those diagnosed with a SUD other than AUD or OUD (0.88 [0.85-0.92]), those with an acute alcohol-related condition (0.79 [0.75-0.84]), and males (0.71 [0.69-0.73]). CONCLUSIONS: While AUD medication use increased and was more common among individuals with greater severity, few patients who could benefit from medications are using them. More efforts are needed to identify and treat individuals in non-acute care settings earlier in their course of AUD.

Life Expectancy after Myocardial Infarction, According to Hospital Performance.

BACKGROUND: Thirty-day risk-standardized mortality rates after acute myocardial infarction are commonly used to evaluate and compare hospital performance. However, it is not known whether differences among hospitals in the early survival of patients with acute myocardial infarction are associated with differences in long-term survival. METHODS: We analyzed data from the Cooperative Cardiovascular Project, a study of Medicare beneficiaries who were hospitalized for acute myocardial infarction between 1994 and 1996 and who had 17 years of follow-up. We grouped hospitals into five strata that were based on case-mix severity. Within each case-mix stratum, we compared life expectancy among patients admitted to high-performing hospitals with life expectancy among patients admitted to low-performing hospitals. Hospital performance was defined by quintiles of 30-day risk-standardized mortality rates. Cox proportional-hazards models were used to calculate life expectancy. RESULTS: The study sample included 119,735 patients with acute myocardial infarction who were admitted to 1824 hospitals. Within each case-mix stratum, survival curves of the patients admitted to hospitals in each risk-standardized mortality rate quintile separated within the first 30 days and then remained parallel over 17 years of follow-up. Estimated life expectancy declined as hospital risk-standardized mortality rate quintile increased. On average, patients treated at high-performing hospitals lived between 0.74 and 1.14 years longer, depending on hospital case mix, than patients treated at low-performing hospitals. When 30-day survivors were examined separately, there was no significant difference in unadjusted or adjusted life expectancy across hospital risk-standardized mortality rate quintiles. CONCLUSIONS: In this study, patients admitted to high-performing hospitals after acute myocardial infarction had longer life expectancies than patients treated in low-performing hospitals. This survival benefit occurred in the first 30 days and persisted over the long term. (Funded by the National Heart, Lung, and Blood Institute and the National Institute of General Medical Sciences Medical Scientist Training Program.).

Diffusion of Bevacizumab Across Oncology Practices: An Observational Study.

BACKGROUND: Technological advances can improve care and outcomes but are a primary driver of health care spending growth. Understanding diffusion and use of new oncology therapies is important, given substantial increases in prices and spending on such treatments. OBJECTIVES: Examine diffusion of bevacizumab, a novel (in 2004) and high-priced biologic cancer therapy, among US oncology practices during 2005-2012 and assess variation in use across practices. RESEARCH DESIGN: Population-based observational study. SETTING: A total of 2329 US practices providing cancer chemotherapy. PARTICIPANTS: Random 20% sample of 236,304 Medicare fee-for-service beneficiaries aged above 65 years in 2004-2012 undergoing infused chemotherapy for cancer. MEASURES: Diffusion of bevacizumab (cumulative time to first use and 10% use) in practices, variation in use across practices overall and by higher versus lower-value use. We used hierarchical models with practice random effects to estimate the between-practice variation in the probability of receiving bevacizumab and to identify factors associated with use. RESULTS: We observed relatively rapid diffusion of bevacizumab, particularly in independent practices and larger versus smaller practices. We observed substantial variation in use; the adjusted odds ratio (95% confidence interval) of bevacizumab use was 2.90 higher (2.73-3.08) for practices 1 SD above versus one standard deviation below the mean. Variation was less for higher-value [odds ratio=2.72 (2.56-2.89)] than lower-value uses [odds ratio=3.61 (3.21-4.06)]. CONCLUSIONS: Use of bevacizumab varied widely across oncology practices, particularly for lower-value indications. These findings suggest that interventions targeted to practices have potential for decreasing low-value use of high-cost cancer therapies.

Bayesian propensity scores for high-dimensional causal inference: A comparison of drug-eluting to bare-metal coronary stents.

High-dimensional data provide many potential confounders that may bolster the plausibility of the ignorability assumption in causal inference problems. Propensity score methods are powerful causal inference tools, which are popular in health care research and are particularly useful for high-dimensional data. Recent interest has surrounded a Bayesian treatment of propensity scores in order to flexibly model the treatment assignment mechanism and summarize posterior quantities while incorporating variance from the treatment model. We discuss methods for Bayesian propensity score analysis of binary treatments, focusing on modern methods for high-dimensional Bayesian regression and the propagation of uncertainty. We introduce a novel and simple estimator for the average treatment effect that capitalizes on conjugacy of the beta and binomial distributions. Through simulations, we show the utility of horseshoe priors and Bayesian additive regression trees paired with our new estimator, while demonstrating the importance of including variance from the treatment regression model. An application to cardiac stent data with almost 500 confounders and 9000 patients illustrates approaches and facilitates comparison with existing alternatives. As measured by a falsifiability endpoint, we improved confounder adjustment compared with past observational research of the same problem.

Twelve or 30 months of dual antiplatelet therapy after drug-eluting stents.

BACKGROUND: Dual antiplatelet therapy is recommended after coronary stenting to prevent thrombotic complications, yet the benefits and risks of treatment beyond 1 year are uncertain. METHODS: Patients were enrolled after they had undergone a coronary stent procedure in which a drug-eluting stent was placed. After 12 months of treatment with a thienopyridine drug (clopidogrel or prasugrel) and aspirin, patients were randomly assigned to continue receiving thienopyridine treatment or to receive placebo for another 18 months; all patients continued receiving aspirin. The coprimary efficacy end points were stent thrombosis and major adverse cardiovascular and cerebrovascular events (a composite of death, myocardial infarction, or stroke) during the period from 12 to 30 months. The primary safety end point was moderate or severe bleeding. RESULTS: A total of 9961 patients were randomly assigned to continue thienopyridine treatment or to receive placebo. Continued treatment with thienopyridine, as compared with placebo, reduced the rates of stent thrombosis (0.4% vs. 1.4%; hazard ratio, 0.29 [95% confidence interval {CI}, 0.17 to 0.48]; P<0.001) and major adverse cardiovascular and cerebrovascular events (4.3% vs. 5.9%; hazard ratio, 0.71 [95% CI, 0.59 to 0.85]; P<0.001). The rate of myocardial infarction was lower with thienopyridine treatment than with placebo (2.1% vs. 4.1%; hazard ratio, 0.47; P<0.001). The rate of death from any cause was 2.0% in the group that continued thienopyridine therapy and 1.5% in the placebo group (hazard ratio, 1.36 [95% CI, 1.00 to 1.85]; P=0.05). The rate of moderate or severe bleeding was increased with continued thienopyridine treatment (2.5% vs. 1.6%, P=0.001). An elevated risk of stent thrombosis and myocardial infarction was observed in both groups during the 3 months after discontinuation of thienopyridine treatment. CONCLUSIONS: Dual antiplatelet therapy beyond 1 year after placement of a drug-eluting stent, as compared with aspirin therapy alone, significantly reduced the risks of stent thrombosis and major adverse cardiovascular and cerebrovascular events but was associated with an increased risk of bleeding. (Funded by a consortium of eight device and drug manufacturers and others; DAPT ClinicalTrials.gov number, NCT00977938.).

Quality of Care in the United States Territories, 1999-2012.

BACKGROUND: Millions of Americans live in the US territories, but health outcomes and payments among Medicare beneficiaries in these territories are not well characterized. METHODS: Among Fee-for-Service Medicare beneficiaries aged 65 years and older hospitalized between 1999 and 2012 for acute myocardial infarction (AMI), heart failure (HF), and pneumonia, we compared hospitalization rates, patient outcomes, and inpatient payments in the territories and states. RESULTS: Over 14 years, there were 4,350,813 unique beneficiaries in the territories and 402,902,615 in the states. Hospitalization rates for AMI, HF, and pneumonia declined overall and did not differ significantly. However, 30-day mortality rates were higher in the territories for all 3 conditions: in the most recent time period (2008-2012), the adjusted odds of 30-day mortality were 1.34 [95% confidence interval (CI), 1.21-1.48], 1.24 (95% CI, 1.12-1.37), and 1.85 (95% CI, 1.71-2.00) for AMI, HF, and pneumonia, respectively; adjusted odds of 1-year mortality were also higher. In the most recent study period, inflation-adjusted Medicare in-patient payments, in 2012 dollars, were lower in the territories than the states, at $9234 less (61% lower than states), $4479 less (50% lower), and $4403 less (39% lower) for AMI, HF, and pneumonia hospitalizations, respectively (P<0.001 for all). CONCLUSIONS AND RELEVANCE: Among Medicare Fee-for-Service beneficiaries, in 2008-2012 mortality rates were higher, or not significantly different, and hospital reimbursements were lower for patients hospitalized with AMI, HF, and pneumonia in the territories. Improvement of health care and policies in the territories is critical to ensure health equity for all Americans.

Association of Changing Hospital Readmission Rates With Mortality Rates After Hospital Discharge.

IMPORTANCE: The Affordable Care Act has led to US national reductions in hospital 30-day readmission rates for heart failure (HF), acute myocardial infarction (AMI), and pneumonia. Whether readmission reductions have had the unintended consequence of increasing mortality after hospitalization is unknown. OBJECTIVE: To examine the correlation of paired trends in hospital 30-day readmission rates and hospital 30-day mortality rates after discharge. DESIGN, SETTING, AND PARTICIPANTS: Retrospective study of Medicare fee-for-service beneficiaries aged 65 years or older hospitalized with HF, AMI, or pneumonia from January 1, 2008, through December 31, 2014. EXPOSURE: Thirty-day risk-adjusted readmission rate (RARR). MAIN OUTCOMES AND MEASURES: Thirty-day RARRs and 30-day risk-adjusted mortality rates (RAMRs) after discharge were calculated for each condition in each month at each hospital in 2008 through 2014. Monthly trends in each hospital's 30-day RARRs and 30-day RAMRs after discharge were examined for each condition. The weighted Pearson correlation coefficient was calculated for hospitals' paired monthly trends in 30-day RARRs and 30-day RAMRs after discharge for each condition. RESULTS: In 2008 through 2014, 2 962 554 hospitalizations for HF, 1 229 939 for AMI, and 2 544 530 for pneumonia were identified at 5016, 4772, and 5057 hospitals, respectively. In January 2008, mean hospital 30-day RARRs and 30-day RAMRs after discharge were 24.6% and 8.4% for HF, 19.3% and 7.6% for AMI, and 18.3% and 8.5% for pneumonia. Hospital 30-day RARRs declined in the aggregate across hospitals from 2008 through 2014; monthly changes in RARRs were -0.053% (95% CI, -0.055% to -0.051%) for HF, -0.044% (95% CI, -0.047% to -0.041%) for AMI, and -0.033% (95% CI, -0.035% to -0.031%) for pneumonia. In contrast, monthly aggregate changes across hospitals in hospital 30-day RAMRs after discharge varied by condition: HF, 0.008% (95% CI, 0.007% to 0.010%); AMI, -0.003% (95% CI, -0.005% to -0.001%); and pneumonia, 0.001% (95% CI, -0.001% to 0.003%). However, correlation coefficients in hospitals' paired monthly changes in 30-day RARRs and 30-day RAMRs after discharge were weakly positive: HF, 0.066 (95% CI, 0.036 to 0.096); AMI, 0.067 (95% CI, 0.027 to 0.106); and pneumonia, 0.108 (95% CI, 0.079 to 0.137). Findings were similar in secondary analyses, including with alternate definitions of hospital mortality. CONCLUSIONS AND RELEVANCE: Among Medicare fee-for-service beneficiaries hospitalized for heart failure, acute myocardial infarction, or pneumonia, reductions in hospital 30-day readmission rates were weakly but significantly correlated with reductions in hospital 30-day mortality rates after discharge. These findings do not support increasing postdischarge mortality related to reducing hospital readmissions.

Race, Socioeconomic Status, and Life Expectancy After Acute Myocardial Infarction.

BACKGROUND: Previous studies have been unable to disentangle the negative associations of black race and low socioeconomic status (SES) with long-term outcomes of patients after acute myocardial infarction (AMI). Such information could assist in efforts to address both racial and socioeconomic disparities. METHODS AND RESULTS: We used data from the Cooperative Cardiovascular Project, a prospective cohort study of Medicare beneficiaries hospitalized with AMI with 17 years of follow-up, to evaluate the relationship between race, area-level SES (measured by zip code-level median household income), and life expectancy after AMI. Life expectancy was estimated by using Cox proportional hazards regression with extrapolation using exponential models. Of the 141 095 patients with AMI, 6.3% were black and 6.8% resided in low-SES areas; 26% of black patients lived in low-SES areas in comparison with 5.7% of white patients. Post-myocardial infarction life expectancy estimates were shorter for black patients than for white patients across all socioeconomic levels in patients ≤ 75 years of age. After adjustment for patient and treatment characteristics, the association between race and life expectancy persisted but was attenuated. Younger black patients (<68 years) had shorter life expectancies than white patients, whereas older black patients had longer life expectancies. The largest white-black gap in life expectancy occurred in patients residing in high- and medium-SES areas (P=0.02 interaction). CONCLUSIONS: Black and white patients residing in low-SES areas have similar life expectancies after AMI, which are lower than those living in higher-SES areas. Racial disparities were most prominent among patients living in high-SES areas.

Relation between door-to-balloon times and mortality after primary percutaneous coronary intervention over time: a retrospective study.

BACKGROUND: Recent reductions in average door-to-balloon (D2B) times have not been associated with decreases in mortality at the population level. We investigated this seemingly paradoxical finding by assessing components of this association at the individual and population levels simultaneously. We postulated that the changing population of patients undergoing primary percutaneous coronary intervention (pPCI) contributed to secular trends toward an increasing mortality risk, despite consistently decreased mortality in individual patients with shorter D2B times. METHODS: This was a retrospective study of ST-elevation myocardial infarction (STEMI) patients who underwent pPCI between Jan 1, 2005, and Dec 31, 2011, in the National Cardiovascular Data Registry (NCDR) CathPCI Registry. We looked for catheterisation laboratory visits associated with STEMI. We excluded patients not undergoing pPCI, transfer patients for pPCI, patients with D2B times less than 15 min or more than 3 h, and patients at hospitals that did not consistently report data across the study period. We assessed in-hospital mortality in the entire cohort and 6-month mortality in elderly patients aged 65 years or older matched to data from the Centers for Medicare and Medicaid Services. We built multilevel models to assess the relation between D2B time and in-hospital and 6-month mortality, including both individual and population-level components of this association after adjusting for patient and procedural factors. FINDINGS: 423 hospitals reported data on 150,116 procedures with a 55% increase in the number of patients undergoing pPCI at these facilities over time, as well as many changes in patient and procedural factors. Annual D2B times decreased significantly from a median of 86 min (IQR 65-109) in 2005 to 63 min (IQR 47-80) in 2011 (p<0·0001) with a concurrent rise in risk-adjusted in-hospital mortality (from 4·7% to 5·3%; p=0·06) and risk-adjusted 6-month mortality (from 12·9% to 14·4%; p=0·001). In multilevel models, shorter patient-specific D2B times were consistently associated at the individual level with lower in-hospital mortality (adjusted OR for each 10 min decrease 0·92; 95% CI 0·91-0·93; p<0·0001) and 6-month mortality (adjusted OR for each 10 min decrease, 0·94; 95% CI 0·93-0·95; p<0·0001). By contrast, risk-adjusted in-hospital and 6-month mortality at the population level, independent of patient-specific D2B times, rose in the growing and changing population of patients undergoing pPCI during the study period. INTERPRETATION: Shorter patient-specific D2B times were consistently associated with lower mortality over time, whereas secular trends suggest increased mortality risk in the growing and changing pPCI population. The absence of association of annual D2B time and changes in mortality at the population level should not be interpreted as an indication of its individual-level relation in patients with STEMI undergoing primary PCI. FUNDING: National Heart, Lung, and Blood Institute.

Nonemergency PCI at hospitals with or without on-site cardiac surgery.

BACKGROUND: Emergency surgery has become a rare event after percutaneous coronary intervention (PCI). Whether having cardiac-surgery services available on-site is essential for ensuring the best possible outcomes during and after PCI remains uncertain. METHODS: We enrolled patients with indications for nonemergency PCI who presented at hospitals in Massachusetts without on-site cardiac surgery and randomly assigned these patients, in a 3:1 ratio, to undergo PCI at that hospital or at a partner hospital that had cardiac surgery services available. A total of 10 hospitals without on-site cardiac surgery and 7 with on-site cardiac surgery participated. The coprimary end points were the rates of major adverse cardiac events--a composite of death, myocardial infarction, repeat revascularization, or stroke--at 30 days (safety end point) and at 12 months (effectiveness end point). The primary end points were analyzed according to the intention-to-treat principle and were tested with the use of multiplicative noninferiority margins of 1.5 (for safety) and 1.3 (for effectiveness). RESULTS: A total of 3691 patients were randomly assigned to undergo PCI at a hospital without on-site cardiac surgery (2774 patients) or at a hospital with on-site cardiac surgery (917 patients). The rates of major adverse cardiac events were 9.5% in hospitals without on-site cardiac surgery and 9.4% in hospitals with on-site cardiac surgery at 30 days (relative risk, 1.00; 95% one-sided upper confidence limit, 1.22; P<0.001 for noninferiority) and 17.3% and 17.8%, respectively, at 12 months (relative risk, 0.98; 95% one-sided upper confidence limit, 1.13; P<0.001 for noninferiority). The rates of death, myocardial infarction, repeat revascularization, and stroke (the components of the primary end point) did not differ significantly between the groups at either time point. CONCLUSIONS: Nonemergency PCI procedures performed at hospitals in Massachusetts without on-site surgical services were noninferior to procedures performed at hospitals with on-site surgical services with respect to the 30-day and 1-year rates of clinical events. (Funded by the participating hospitals without on-site cardiac surgery; MASS COM ClinicalTrials.gov number, NCT01116882.).

Hospital Phenotypes in the Management of Patients Admitted for Acute Myocardial Infarction.

OBJECTIVES: To characterize hospital phenotypes by their combined utilization pattern of percutaneous coronary interventions (PCI), coronary artery bypass grafting (CABG) procedures, and intensive care unit (ICU) admissions for patients hospitalized for acute myocardial infarction (AMI). RESEARCH DESIGN: Using the Premier Analytical Database, we identified 129,138 hospitalizations for AMI from 246 hospitals with the capacity for performing open-heart surgery during 2010-2013. We calculated year-specific, risk-standardized estimates of PCI procedure rates, CABG procedure rates, and ICU admission rates for each hospital, adjusting for patient clinical characteristics and within-hospital correlation of patients. We used a mixture modeling approach to identify groups of hospitals (ie, hospital phenotypes) that exhibit distinct longitudinal patterns of risk-standardized PCI, CABG, and ICU admission rates. RESULTS: We identified 3 distinct phenotypes among the 246 hospitals: (1) high PCI-low CABG-high ICU admission (39.2% of the hospitals), (2) high PCI-low CABG-low ICU admission (30.5%), and (3) low PCI-high CABG-moderate ICU admission (30.4%). Hospitals in the high PCI-low CABG-high ICU admission phenotype had significantly higher risk-standardized in-hospital costs and 30-day risk-standardized payment yet similar risk-standardized mortality and readmission rates compared with hospitals in the low PCI-high CABG-moderate ICU admission phenotype. Hospitals in these phenotypes differed by geographic region. CONCLUSIONS: Hospitals differ in how they manage patients hospitalized for AMI. Their distinctive practice patterns suggest that some hospital phenotypes may be more successful in producing good outcomes at lower cost.

Regional Variation in Physician Adoption of Antipsychotics: Impact on US Medicare Expenditures.

BACKGROUND: Regional variation in US Medicare prescription drug spending is driven by higher prescribing of costly brand-name drugs in some regions. This variation likely arises from differences in the speed of diffusion of newly-approved medications. Second-generation antipsychotics were widely adopted for treatment of severe mental illness and for several off-label uses. Rapid diffusion of new psychiatric drugs likely increases drug spending but its relationship to non-drug spending is unclear. The impact of antipsychotic diffusion on drug and medical spending is of great interest to public payers like Medicare, which finance a majority of mental health spending in the US. AIMS: We examine the association between physician adoption of new antipsychotics and antipsychotic spending and non-drug medical spending among disabled and elderly Medicare enrollees. METHODS: We linked physician-level data on antipsychotic prescribing from an all-payer dataset (IMS Health's XponentTM) to patient-level data from Medicare. Our physician sample included 16,932 US. psychiatrists and primary care providers with > 10 antipsychotic prescriptions per year from 1997-2011. We constructed a measure of physician adoption of 3 antipsychotics introduced during this period (quetiapine, ziprasidone and aripiprazole) by estimating a shared frailty model of the time to first prescription for each drug. We then assigned physicians to one of 306 U.S. hospital referral regions (HRRs) and measured the average propensity to adopt per region. Using 2010 data for a random sample of 1.6 million Medicare beneficiaries, we identified 138,680 antipsychotic users. A generalized linear model with gamma distribution and log link was used to estimate the effect of region-level adoption propensity on beneficiary-level antipsychotic spending and non-drug medical spending adjusting for patient demographic and socioeconomic characteristics, health status, eligibility category, and whether the antipsychotic was for an on- vs. off-label use. RESULTS: In our sample, mean patient age was 62 years, 42% were male, and 86% had low-income. Half of antipsychotic users in Medicare had an on-label indication. The weighted average propensity to adopt the three new antipsychotics varied four-fold across HRRs. For every one standard deviation increase in the propensity to adopt there was a 5% increase in antipsychotic spending after adjusting for covariates (adjusted ratio of spending 1.05, 95% CI 1.01-1.08, p = 0.005). Physician propensity to adopt new antipsychotics was not associated with non-drug medical spending (adjusted ratio 0.96, 95% CI 0.91-1.01, p < 0.117). DISCUSSION: These findings suggest wide regional variation in physicians' propensity to adopt new antipsychotic medications. While physician adoption of new antipsychotics was positively associated with antipsychotic expenditures, it was not associated with non-drug spending. Our analysis is limited to Medicare and may not generalize to other payers. Also, claims data do not allow for the measurement of health outcomes, which would be important to evaluate when calculating the value of rapid vs. slow technology adoption.