Search

We are now on the cusp of massive adoption of digital health technologies. Medicine is becoming an information science intertwined with technology and data science. This talk aims to describe the current state of digital transformation in healthcare, to identify reasons for enthusiasm and caution, and to provide a framework for thinking about what is necessary for hospitals and health systems to be confident about incorporating these innovations into practice. I have three key recommendations. First, we should buy results, not claims. Those in positions that influence decisions about endorsing or purchasing digital products designed to improve care or outcomes ought to buy results, not claims or intermediate results. Moreover, although analytic validity and clinical validity are important, they sometimes do not reflect the impact of a product in its entirety. Ultimately, we need to know whether patients benefit. Second, we should insist on transparency. The performance of a product cannot be a secret. The basis on which developers make claims about their products should be open to all, including patients. Better yet, data on which experts reach a conclusion should be shared, just as many companies share research data on drugs and devices. Third, we should be aware of unintended adverse consequences. We should evaluate every intervention for unintended adverse consequences. Changes to systems, with all good intentions, can always go awry. In conclusion, insistence on good and evolving evidence is the best way to arrive at our destination: the use of innovations to improve outcomes., (© Copyright: Yonsei University College of Medicine 2022.)

Objective: Access to acute cardiovascular care has improved and health services capacity has increased over the past decades. We assessed national changes in (1) patient characteristics, (2) in-hospital management and (3) patient outcomes among patients presenting with ST segment elevation myocardial infarction (STEMI) in 2011-2015 in China., Methods: In a nationally representative sample of hospitals in China, we created two random cohorts of patients in 2011 and 2015 separately. We weighted our findings to estimate nationally representative numbers and assessed changes from 2011 to 2015. Data were abstracted from medical charts centrally using standardised definitions., Results: While the proportion of patients with STEMI among all patients with acute myocardial infarction decreased over time from 82.5% (95% CI 81.7 to 83.3) in 2011 to 68.5% (95% CI 67.7 to 69.3) in 2015 (p<0.0001), the weighted national estimate of patients with STEMI increased from 210 000 to 380 000. The rate of reperfusion eligibility among patients with STEMI decreased from 49.3% (95% CI 48.1 to 50.5) to 42.2% (95% CI 41.1 to 43.4) in 2015 (p<0.0001); ineligibility was principally driven by larger proportions with prehospital delay exceeding 12 hours (67.4%-76.7%, p<0.0001). Among eligible patients, the proportion receiving reperfusion therapies increased from 54% (95% CI 52.3 to 55.7) to 59.7% (95% CI 57.9 to 61.4) (p<0.0001). Crude and risk-adjusted rates of in-hospital death did not differ significantly between 2011 and 2015., Conclusions: In this most recent nationally representative study of STEMI in China, the use of acute reperfusion increased, but no significant improvement occurred in outcomes. There is a need to continue efforts to prevent cardiovascular diseases, to monitor changes in in-hospital treatments and outcomes, and to reduce prehospital delay., Competing Interests: Competing interests: JL reported receiving research grants, through Fuwai Hospital, from the People’s Republic of China for work to improve the management of hypertension and blood lipids and to improve care quality and patient outcomes of cardiovascular disease; receiving research agreements, through the National Center for Cardiovascular Diseases and Fuwai Hospital, from Amgen for a multicentre clinical trial assessing the efficacy and safety of omecamtiv mecarbil and for dyslipidaemic patient registration; receiving a research agreement, through Fuwai Hospital, from Sanofi for a multicentre clinical trial on the effects of sotagliflozin; receiving a research agreement, through Fuwai Hospital, with the University of Oxford for a multicentre clinical trial of empagliflozin; receiving a research agreement, through the National Center for Cardiovascular Diseases, from AstraZeneca for clinical research methods training, outside the submitted work; and receiving a research agreement, through the National Center for Cardiovascular Diseases, from Lilly for physician training, outside the submitted work. HK works under contract with the Centers for Medicare & Medicaid Services to support quality measurement programmes; was a recipient of a research grant, through Yale, from Medtronic and the US Food and Drug Administration to develop methods for postmarket surveillance of medical devices; was a recipient of a research grant with Medtronic and is the recipient of a research grant from Johnson & Johnson, through Yale University, to support clinical trial data sharing; was a recipient of a research agreement, through Yale University, from the Shenzhen Center for Health Information for work to advance intelligent disease prevention and health promotion; collaborates with the National Center for Cardiovascular Diseases in Beijing; receives payment from the Arnold & Porter law firm for work related to the Sanofi clopidogrel litigation, from the Martin/Baughman law firm for work related to the Cook IVC filter litigation, and from the Siegfried and Jensen law firm for work related to Vioxx litigation; chairs a Cardiac Scientific Advisory Board for UnitedHealth; was a participant/participant representative of the IBM Watson Health Life Sciences Board; is a member of the Advisory Board for Element Science, the Advisory Board for Facebook and the Physician Advisory Board for Aetna; and is the founder of Hugo Health, a personal health information platform, and cofounder of Refactor Health, an enterprise healthcare AI-augmented data management company. FM has a contract with the American College of Cardiology as the Chief Scientific Advisor for the NCDR and has received travel expenses from the Fuwai Hospital. YL is supported by the National Heart, Lung, and Blood Institute (K12HL138037) and was a recipient of a research agreement, through Yale, from the Shenzhen Center for Health Information for work to advance intelligent disease prevention and health promotion., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Objectives: To create a straightforward scoring procedure based on widely available, inexpensive financial data that provides an assessment of the financial health of a hospital., Design: Methodological study., Setting: Multicentre study., Participants: All hospitals and health systems reporting the required financial metrics in the USA in 2017 were included for a total of 1075 participants., Interventions: We examined a list of 232 hospital financial indicators and used existing models and financial literature to select 30 metrics that sufficiently describe hospital operations. In a set of hospital financial data from 2017, we used principal coordinate analysis to assess collinearity among variables and eliminated redundant variables. We isolated 10 unique variables, each assigned a weight equal to the share of its coefficient in a regression onto Moody's Credit Rating, our predefined gold standard. The sum of weighted variables is a single composite score named the Yale Hospital Financial Score (YHFS)., Primary Outcome Measures: Ability to reproduce both financial trends from a 'gold-standard' metric and known associations with non-fiscal data., Results: The validity of the YHFS was evaluated by: (1) cross-validating it with previously excluded data; (2) comparing it to existing models and (3) replicating known associations with non-fiscal data. Ten per cent of the initial dataset had been reserved for validation and was not used in creating the model; the YHFS predicts 96.7% of the variation in this reserved sample, demonstrating reproducibility. The YHFS predicts 90.5% and 88.8% of the variation in Moody's and Standard and Poor's bond ratings, respectively, supporting its validity. As expected, larger hospitals had higher YHFS scores whereas a greater share of Medicare discharges correlated with lower YHFS scores., Conclusions: We created a reliable and publicly available composite score of hospital financial stability., Competing Interests: Competing interests: RC is the president of Merritt Research Services, a data and research provider of credit information related to municipal bonds., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Importance: Present-on-admission (POA) indicators in administrative claims data allow researchers to distinguish between preexisting conditions and those acquired during a hospital stay. The impact of adding POA information to claims-based measures of hospital quality has not yet been investigated to better understand patient underlying risk factors in the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision setting., Objective: To assess POA indicator use on Medicare claims and to assess the hospital- and patient-level outcomes associated with incorporating POA indicators in identifying risk factors for publicly reported outcome measures used by the Centers for Medicare & Medicaid Services (CMS)., Design, Setting, and Participants: This comparative effectiveness study used national CMS claims data between July 1, 2015, and June 30, 2018. Six hospital quality measures assessing readmission and mortality outcomes were modified to include POA indicators in risk adjustment models. The models using POA were then compared with models using the existing complications-of-care algorithm to evaluate changes in risk model performance. Patient claims data were included for all Medicare fee-for-service and Veterans Administration beneficiaries aged 65 years or older with inpatient hospitalizations for acute myocardial infarction, heart failure, or pneumonia within the measurement period. Data were analyzed between September 2019 and March 2020., Main Outcomes and Measures: Changes in patient-level (C statistics) and hospital-level (quintile shifts in risk-standardized outcome rates) model performance after including POA indicators in risk adjustment., Results: Data from a total of 6 027 988 index admissions were included for analysis, ranging from 491 366 admissions (269 209 [54.8%] men; mean [SD] age, 78.2 [8.3] years) for the acute myocardial infarction mortality outcome measure to 1 395 870 admissions (677 158 [48.5%] men; mean [SD] age, 80.3 [8.7] years) for the pneumonia readmission measure. Use of POA indicators was associated with improvements in risk adjustment model performance, particularly for mortality measures (eg, the C statistic increased from 0.728 [95% CI, 0.726-0.730] to 0.774 [95% CI, 0.773-0.776] when incorporating POA indicators into the acute myocardial infarction mortality measure)., Conclusions and Relevance: The findings of this quality improvement study suggest that leveraging POA indicators in the risk adjustment methodology for hospital quality outcome measures may help to more fully capture patients' risk factors and improve overall model performance. Incorporating POA indicators does not require extra effort on the part of hospitals and would be easy to implement in publicly reported quality outcome measures.

Importance: Institution-level strategic changes may be associated with heart transplant volume and outcomes., Objective: To describe changes in practice that markedly increased heart transplant volume at a single center, as well as associated patient characteristics and outcomes., Design, Setting, and Participants: A pre-post cohort study was conducted of 107 patients who underwent heart transplant between September 1, 2014, and August 31, 2019, at Yale New Haven Hospital before (September 1, 2014, to August 31, 2018; prechange era) and after (September 1, 2018, to August 31, 2019; postchange era) a strategic change in patient selection by the heart transplant program., Exposure: Strategic change in donor and recipient selection at Yale New Haven Hospital that occurred in August 2018., Main Outcomes and Measures: Outcome measures were transplant case volume, donor and recipient characteristics, and 180-day survival., Results: A total of 49 patients (12.3 per year; 20 women [40.8%]; median age, 57 years [interquartile range {IQR}, 50-63 years]) received heart transplants in the 4 years of the prechange era and 58 patients (58 per year; 19 women [32.8%]; median age, 57 years [IQR, 52-64 years]) received heart transplants in the 1 year of the postchange era. Organ offers were more readily accepted in the postchange era, with an offer acceptance rate of 20.5% (58 of 283) compared with 6.4% (49 of 768) in the prechange era (P < .001). In the postchange era, donor hearts were accepted with a higher median number of prior refusals by other centers than in the prechange era (16.5 [IQR, 6-38] vs 3 [IQR, 1-6]; P < .001). Hearts accepted in the postchange era were from older donors than in the prechange era (median age, 40 years [IQR, 29-48 years] vs 30 years [IQR, 24-42 years]; P < .001). Recipients had a significantly shorter time on the waiting list in the postchange era compared with prechange era (median, 41 days [IQR, 12-289 days] vs 242 days [IQR, 135-428 days]; P < .001). More patients were supported on temporary circulatory assist devices preoperatively in the postchange era than the prechange era (14 [24.1%] vs 0; P < .001). Survival rates at 180 days were not significantly different (43 [87.8%] in the prechange era vs 52 [89.7%] in the postchange era). Mortality while on the waiting list was similar (2.8 deaths per year in the prechange era vs 3 deaths per year in the postchange era). During the comparable time period, 4 other regional centers had volume change ranging from -10% to 68%, while this center's volume increased by 374%., Conclusions and Relevance: This study suggests that strategic changes in donor heart and recipient selection may significantly increase the number of heart transplants while maintaining short-term outcomes comparable with more conservative patient selection. Such an approach may augment the allocation of currently unused donor hearts.

Importance: Given the emerging heart failure (HF) epidemic in China, monitoring and improving the quality of care for heart failure is a top priority., Objectives: To assess the quality of HF care provided to inpatients by examining the adherence to quality measures for HF care at the hospital level and to identify factors associated with the quality of care., Design, Setting, and Participants: In this multicenter, hospital-based, retrospective cross-sectional study in China, medical records of patients hospitalized for HF from January 1, 2015, to December 31, 2015, were analyzed from January 1, 2018, to May 20, 2019. In the first stage, simple random sampling stratified by economic-geographical regions in China was used to generate a list of participating hospitals. In the second stage, 15 538 hospitalizations from the 189 selected hospitals were systematically sampled, and 10 004 HF hospitalizations were included in the final sample., Main Outcomes and Measures: Adherence to the following 4 core performance measures at the hospital level: (1) left ventricular ejection fraction assessment during hospitalization; (2) evidence-based β-blocker (bisoprolol, carvedilol, or metoprolol succinate) for eligible patients at discharge; (3) angiotensin-converting enzyme inhibitors or angiotensin receptor blockers for eligible patients at discharge; and (4) scheduled follow-up appointment at discharge. At the hospital level, a composite performance score (ranging from 0-1) was also calculated by averaging these measures., Results: In total, 10 004 hospital admissions for HF at 189 hospitals were included in this study. The median (interquartile range [IQR]) patient age at admission was 73 (65-80) years, and 5117 (51.1%) of the patients were men. Among all hospitals, the median rate of adherence to measure 1 was 66.7% (IQR, 45.5%-80.7%; range, 0%-100%). The rate for adherence to measure 2 was 14.8% (IQR, 0%-37.5%; range, 0%-81.8%), and the rate for measure 3 was 57.1% (IQR, 36.4%-75.0%; range, 0%-100%). For measure 4, the median rate of adherence was 11.5% (IQR, 3.3%-32.8%; range, 0%-96.7%). The median (IQR) composite performance score across all hospitals was 40.0% (26.9%-51.9%), with a range from 2.2% to 85.4%. The median odds ratios of adherence were 2.2 (95% CI, 2.0-2.4) for measure 1, 2.1 (95% CI, 1.8-2.4) for measure 2, 2.4 (95% CI, 2.0-2.9 for measure 3, and 4.8 (95% CI, 3.9-5.8) for measure 4 among hospitals., Conclusions and Relevance: The findings of this study suggest that quality of care for patients with HF in China may be substandard, and there is wide heterogeneity in the quality of care for HF among hospitals. The findings also suggest the need for a national strategy to improve and standardize the quality of HF care in China.

Background: Cardiovascular implantable electronic devices (CIEDs) are associated with procedure-related complications, yet little is known about variation in complication rates among institutions that may suggest disparities in care quality., Objective: To assess institutional variation in risk-standardized complication rates (RSCRs) for CIED., Design: Cohort study., Setting: 174 hospitals in Australia and New Zealand, 98 of which implanted at least 25 CIEDs during the study period., Participants: 81 304 patients older than 18 years (mean, 74.7 years [SD, 12.4]; 37.9% female) who received a new CIED (65 711 permanent pacemakers [PPMs] and 15 593 implantable cardioverter-defibrillators [ICDs]) in 2010 to 2015., Measurements: RSCRs and frequencies of major device-related complications during hospitalization or within 90 days of discharge., Results: Of the cohort, 6664 patients (8.2%) had a major complication. Although complication rates were higher for ICDs than PPMs (10.04% vs. 7.76%), 76.5% of all complications were attributable to PPMs (5098 vs. 1566 for ICDs). Among hospitals that implanted at least 25 CIEDs, the median RSCR was 8.1%; however, rates varied from 5.3% to 14.3%, with 22 hospitals identified as having RSCRs that differed significantly from the national average. Similar variation was observed when RSCRs for PPM implantation (n = 96 hospitals) (median RSCR, 7.6% [range, 5.4% to 12.9%]) were considered separately from those for ICD placement (n = 68 hospitals) (median RSCR, 9.7% [range, 6.2% to 16.9%]) and persisted when only elective procedures were assessed (n = 88 hospitals) (median RSCR, 7.4% [range, 4.7% to 13.0%])., Limitation: Possible unmeasured confounding from the use of administrative data., Conclusion: CIED complications are common and vary among hospitals, suggesting institutional variation in CIED care quality. Concerted clinical and policy interventions are needed to address CIED-related complications. These efforts should preferentially target PPMs, because most CIED complications are attributable to these devices., Primary Funding Source: The Hospitals Contribution Fund Research Foundation.

Background In the United States, patients have the right to access their protected health information. However, to the knowledge of the authors, no study has evaluated the patient request process and the barriers to patient access of their radiology images. Purpose To assess U.S. hospital compliance with federal regulations and patient ease of access to imaging studies. Materials and Methods In this cross-sectional study conducted from June 6 to December 3, 2018, 80 U.S. hospitals were contacted by telephone to determine their patient request process for imaging studies. A scripted interview was used to simulate the patient experience in requesting imaging studies. Hospitals were compared in terms of formats of release (compact disc [CD] via pick up, CD via mail, e-mail, online patient portal, or other online access), departments from which cine files can be requested, fees, and processing times. Results All 80 hospitals stated that they could provide imaging studies on CDs. Only six (8%) hospitals provided imaging studies via e-mail and three (4%) via an online patient portal. Requests for cine files were fulfilled by a department separate from diagnostic radiology in 47 of 80 (59%) hospitals. Patient charges ranged from $0 to $75 for a single CD, no charge to $6 via e-mail, and no charge via an online patient portal. Fifty-nine (74%) hospitals stated that they could release copies within 24 hours, 10 (13%) within 2-5 days, eight (10%) within 5-10 days, and three (4%) within 10-30 days from request date. Imaging studies from outside of the diagnostic radiology department may need to be requested through the departments that performed the study. Conclusion This study demonstrated that although fees and processing times are compliant with federal regulations, patient access to imaging studies is limited primarily to compact disc format. The request process is also complicated for patients because of dispersion of imaging studies across departments. © RSNA, 2019 Online supplemental material is available for this article.

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

Importance: Payers and policy makers have advocated for transitioning toward value-based payment models. However, little is known about what is the extent of hospital variation in the value of care and whether there are any hospital characteristics associated with high-value care., Objectives: To investigate the association between hospital-level 30-day risk-standardized mortality rates (RSMRs) and 30-day risk-standardized payments (RSPs) for acute myocardial infarction (AMI), heart failure (HF), and pneumonia (PNA); to characterize patterns of value in care; and to identify hospital characteristics associated with high-value care (defined by having lower than median RSMRs and RSPs)., Design, Setting, and Participants: This national cross-sectional study applied weighted linear correlation to investigate the association between hospital RSMRs and RSPs for AMI, HF, and PNA between July 1, 2011, and June 30, 2014, among all hospitals; examined correlations in subgroups of hospitals based on key characteristics; and assessed the proportion and characteristics of hospitals delivering high-value care. The data analysis was completed in October 2017. The setting was acute care hospitals. Participants were Medicare fee-for-service beneficiaries discharged with AMI, HF, or PNA., Main Outcomes and Measures: Hospital-level 30-day RSMRs and RSPs for AMI, HF, and PNA., Results: The AMI sample consisted of 4339 hospitals with 487 141 hospitalizations for mortality and 462 905 hospitalizations for payment. The HF sample included 4641 hospitals with 960 960 hospitalizations for mortality and 903 721 hospitalizations for payment. The PNA sample contained 4685 hospitals with 952 022 hospitalizations for mortality and 901 764 hospitalizations for payment. The median (interquartile range [IQR]) RSMRs and RSPs, respectively, was 14.3% (IQR, 13.8%-14.8%) and $21 620 (IQR, $20 966-$22 567) for AMI, 11.7% (IQR, 11.0%-12.5%) and $15 139 (IQR, $14 310-$16 118) for HF, and 11.5% (IQR, 10.6%-12.6%) and $14 220 (IQR, $13 342-$15 097) for PNA. There were statistically significant but weak inverse correlations between the RSMRs and RSPs of -0.08 (95% CI, -0.11 to -0.05) for AMI, -0.21 (95% CI, -0.24 to -0.18) for HF, and -0.07 (95% CI, -0.09 to -0.04) for PNA. The largest shared variance between the RSMRs and RSPs was only 4.4% (for HF). The correlations between the RSMRs and RSPs did not differ significantly across teaching status, safety-net status, urban/rural status, or the proportion of patients with low socioeconomic status. Approximately 1 in 4 hospitals (20.9% for AMI, 23.0% for HF, and 23.9% for PNA) had both lower than median RSMRs and RSPs., Conclusions and Relevance: These findings suggest that there is significant potential for improvement in the value of AMI, HF, and PNA care and also suggest that high-value care for these conditions is attainable across most hospital types.

Importance: Although studies have described differences in hospital outcomes by patient race and socioeconomic status, it is not clear whether such disparities are driven by hospitals themselves or by broader systemic effects., Objective: To determine patterns of racial and socioeconomic disparities in outcomes within and between hospitals for patients with acute myocardial infarction, heart failure, and pneumonia., Design, Setting, and Participants: Retrospective cohort study initiated before February 2013, with additional analyses conducted during the peer-review process. Hospitals in the United States treating at least 25 Medicare fee-for-service beneficiaries aged 65 years or older in each race (ie, black and white) and neighborhood income level (ie, higher income and lower income) for acute myocardial infarction, heart failure, and pneumonia between 2009 and 2011 were included., Main Outcomes and Measures: For within-hospital analyses, risk-standardized mortality rates and risk-standardized readmission rates for race and neighborhood income subgroups were calculated at each hospital. The corresponding ratios using intraclass correlation coefficients were then compared. For between-hospital analyses, risk-standardized rates were assessed according to hospitals' proportion of patients in each subgroup. These analyses were performed for each of the 12 analysis cohorts reflecting the unique combinations of outcomes (mortality and readmission), demographics (race and neighborhood income), and conditions (acute myocardial infarction, heart failure, and pneumonia)., Results: Between 74% (3545 of 4810) and 91% (4136 of 4554) of US hospitals lacked sufficient racial and socioeconomic diversity to be included in this analysis, with the number of hospitals eligible for analysis varying among cohorts. The 12 analysis cohorts ranged in size from 418 to 1265 hospitals and from 144 417 to 703 324 patients. Within included hospitals, risk-standardized mortality rates tended to be lower among black patients (mean [SD] difference between risk-standardized mortality rates in black patients compared with white patients for acute myocardial infarction, -0.57 [1.1] [P = .47]; for heart failure, -4.7 [1.3] [P < .001]; and for pneumonia, -1.0 [2.0] [P = .05]). However, risk-standardized readmission rates among black patients were higher (mean [SD] difference between risk-standardized readmission rates in black patients compared with white patients for acute myocardial infarction, 4.3 [1.4] [P < .001]; for heart failure, 2.8 [1.8] [P < .001], and for pneumonia, 3.7 [1.3] [P < .001]). Intraclass correlation coefficients ranged from 0.68 to 0.79, indicating that hospitals generally delivered consistent quality to patients of differing races. While the coefficients in the neighborhood income analysis were slightly lower (0.46-0.60), indicating some heterogeneity in within-hospital performance, differences in mortality rates and readmission rates between the 2 neighborhood income groups were small. There were no strong, consistent associations between risk-standardized outcomes for white or higher-income neighborhood patients and hospitals' proportion of black or lower-income neighborhood patients., Conclusions and Relevance: Hospital performance according to race and socioeconomic status was generally consistent within and between hospitals, even as there were overall differences in outcomes by race and neighborhood income. This finding indicates that disparities are likely to be systemic, rather than localized to particular hospitals.

Background: Amid national efforts to improve the quality of care for people with cardiovascular disease in China, the use of traditional Chinese medicine (TCM) is increasing, yet little is known about its use in the early management of acute myocardial infarction (AMI)., Methods and Results: We aimed to examine intravenous use of TCM within the first 24 hours of hospitalization (early IV TCM) for AMI. Data come from the China Patient-centered Evaluative Assessment of Cardiac Events Retrospective Study of Acute Myocardial Infarction, restricted to a large, representative sample of Western medicine hospitals throughout China (n=162). We conducted a chart review of randomly sampled patients with AMI in 2001, 2006, and 2011, comparing early intravenous TCM use across years, predictors of any early intravenous TCM use, and association with in-hospital bleeding and mortality. From 2001 to 2011, early intravenous TCM use increased (2001: 38.2% versus 2006: 49.1% versus 2011: 56.1%; P <0.01). Nearly all (99%) hospitals used early intravenous TCM. Salvia miltiorrhiza was most commonly prescribed, used in one third (35.5%) of all patients admitted with AMI. Patients receiving any early intravenous TCM, compared with those who did not, were similar in age and sex and had fewer cardiovascular risk factors. In multivariable hierarchical models, admission to a secondary (versus tertiary) hospital was most strongly associated with early intravenous TCM use (odds ratio: 2.85; 95% confidence interval: 1.98-4.11). Hospital-level factors accounted for 55% of the variance (adjusted median odds ratio: 2.84). In exploratory analyses, there were no significant associations between early intravenous TCM and in-hospital bleeding or mortality., Conclusions: Early intravenous TCM use for AMI in China is increasing despite the lack of evidence of their benefit or harm. There is an urgent need to define the effects of these medications because they have become a staple of treatment in the world's most populous country., Clinical Trial Registration: URL: https://www.clinicaltrials.gov. Unique identifier: NCT01624883., (© 2018 The Authors.)

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.).

Background: China has gaps in the quality of care provided to patients with ST-elevation myocardial infarction, but little is known about how quality varies between hospitals., Methods and Results: Using nationally representative data from the China PEACE-Retrospective AMI Study, we characterized the quality of care for ST-elevation myocardial infarction at the hospital level and examined variation between hospitals. Two summary measures were used to describe the overall quality of care at each hospital and to characterize variations in quality between hospitals in 2001, 2006, and 2011. The composite rate measured the proportion of opportunities a hospital had to deliver 6 guideline-recommended treatments for ST-elevation myocardial infarction that were successfully met, while the defect-free rate measured the proportion of patients at each hospital receiving all guideline-recommended treatments for which they were eligible. Risk-standardized mortality rates were calculated. Our analysis included 12 108 patients treated for ST-elevation myocardial infarction at 162 hospitals. The median composite rate increased from 56.8% (interquartile range [IQR], 45.9-72.0) in 2001 to 80.5% (IQR, 74.7-84.8) in 2011; however, substantial variation remained in 2011 with defect-free rates ranging from 0.0% to 76.9%. The median risk-standardized mortality rate increased from 9.9% (IQR, 9.1-11.7) in 2001 to 12.6% (IQR, 10.9-14.6) in 2006 before falling to 10.4% (IQR, 9.1-12.4) in 2011., Conclusions: Higher rates of guideline-recommended care and a decline in variation between hospitals are indicative of an improvement in quality. Although some variation persisted in 2011, very top-performing hospitals missed few opportunities to provide guideline-recommended care. Quality improvement initiatives should focus on eliminating residual variation as well as measuring and improving outcomes., Clinical Trial Registration: URL: https://www.clinicaltrials.gov. Unique identifier: NCT01624883., (© 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.)

Importance: Readmission rates declined after announcement of the Hospital Readmission Reduction Program (HRRP), which penalizes hospitals for excess readmissions for acute myocardial infarction (AMI), heart failure (HF), and pneumonia., Objective: To compare trends in readmission rates for target and nontarget conditions, stratified by hospital penalty status., Design, Setting, and Participants: Retrospective cohort study of Medicare fee-for-service beneficiaries older than 64 years discharged between January 1, 2008, and June 30, 2015, from 2214 penalty hospitals and 1283 nonpenalty hospitals. Difference-interrupted time-series models were used to compare trends in readmission rates by condition and penalty status., Exposure: Hospital penalty status or target condition under the HRRP., Main Outcomes and Measures: Thirty-day risk adjusted, all-cause unplanned readmission rates for target and nontarget conditions., Results: The study included 48 137 102 hospitalizations of 20 351 161 Medicare beneficiaries. In January 2008, the mean readmission rates for AMI, HF, pneumonia, and nontarget conditions were 21.9%, 27.5%, 20.1%, and 18.4%, respectively, at hospitals later subject to financial penalties and 18.7%, 24.2%, 17.4%, and 15.7% at hospitals not subject to penalties. Between January 2008 and March 2010, prior to HRRP announcement, readmission rates were stable across hospitals (except AMI at nonpenalty hospitals). Following announcement of HRRP (March 2010), readmission rates for both target and nontarget conditions declined significantly faster for patients at hospitals later subject to financial penalties compared with those at nonpenalized hospitals (for AMI, additional decrease of -1.24 [95% CI, -1.84 to -0.65] percentage points per year relative to nonpenalty discharges; for HF, -1.25 [95% CI, -1.64 to -0.86]; for pneumonia, -1.37 [95% CI, -1.80 to -0.95]; and for nontarget conditions, -0.27 [95% CI, -0.38 to -0.17]; P < .001 for all). For penalty hospitals, readmission rates for target conditions declined significantly faster compared with nontarget conditions (for AMI, additional decline of -0.49 [95% CI, -0.81 to -0.16] percentage points per year relative to nontarget conditions [P = .004]; for HF, -0.90 [95% CI, -1.18 to -0.62; P < .001]; and for pneumonia, -0.57 [95% CI, -0.92 to -0.23; P < .001]). In contrast, among nonpenalty hospitals, readmissions for target conditions declined similarly or more slowly compared with nontarget conditions (for AMI, additional increase of 0.48 [95% CI, 0.01-0.95] percentage points per year [P = .05]; for HF, 0.08 [95% CI, -0.30 to 0.46; P = .67]; for pneumonia, 0.53 [95% CI, 0.13-0.93; P = .01]). After HRRP implementation in October 2012, the rate of change for readmission rates plateaued (P < .05 for all except pneumonia at nonpenalty hospitals), with the greatest relative change observed among hospitals subject to financial penalty., Conclusions and Relevance: Medicare fee-for-service patients at hospitals subject to penalties under the HRRP had greater reductions in readmission rates compared with those at nonpenalized hospitals. Changes were greater for target vs nontarget conditions for patients at the penalized hospitals but not at the other hospitals.

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.).

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.

Background: Little is known regarding the relationship between hospital performance on adverse event rates and hospital performance on 30-day mortality and unplanned readmission rates for Medicare fee-for-service patients hospitalized for acute myocardial infarction (AMI)., Methods and Results: Using 2009-2013 medical record-abstracted patient safety data from the Agency for Healthcare Research and Quality's Medicare Patient Safety Monitoring System and hospital mortality and readmission data from the Centers for Medicare & Medicaid Services, we fitted a mixed-effects model, adjusting for hospital characteristics, to evaluate whether hospital performance on patient safety, as measured by the hospital-specific risk-standardized occurrence rate of 21 common adverse event measures for which patients were at risk, is associated with hospital-specific 30-day all-cause risk-standardized mortality and unplanned readmission rates for Medicare patients with AMI. The unit of analysis was at the hospital level. The final sample included 793 acute care hospitals that treated 30 or more Medicare patients hospitalized for AMI and had 40 or more adverse events for which patients were at risk. The occurrence rate of adverse events for which patients were at risk was 3.8%. A 1% point change in the risk-standardized occurrence rate of adverse events was associated with average changes in the same direction of 4.86% points (95% CI, 0.79-8.94) and 3.44% points (95% CI, 0.19-6.68) for the risk-standardized mortality and unplanned readmission rates, respectively., Conclusions: For Medicare fee-for-service patients discharged with AMI, hospitals with poorer patient safety performance were also more likely to have poorer performance on 30-day all-cause mortality and on unplanned readmissions., (© 2016 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.)

Background: Guidelines for heart failure (HF) recommend prescription of guideline-directed medical therapy before hospital discharge; some of these therapies are included in publicly reported performance measures. The burden of new medications for individual patients has not been described., Methods and Results: We used Get With The Guidelines-HF registry data from 2008 to 2013 to characterize prescribing, indications, and contraindications for angiotensin-converting enzyme inhibitors or angiotensin receptor blockers, β-blockers, aldosterone antagonists, hydralazine/isosorbide dinitrate, and anticoagulants. The difference between a patient's medication regimen at hospital admission and that recommended by HF quality measures at discharge was calculated. Among 158 922 patients from 271 hospitals with a primary discharge diagnosis of HF, initiation of angiotensin-converting enzyme inhibitors or angiotensin receptor blockers was indicated in 18.1% of all patients (55.5% of those eligible at discharge were not receiving angiotensin-converting enzyme inhibitors or angiotensin receptor blockers at admission), β-blockers in 20.3% (50.5% of eligible), aldosterone antagonists in 24.1% (87.4% of eligible), hydralazine/isosorbide dinitrate in 8.6% (93.1% of eligible), and anticoagulants in 18.0% (58.0% of eligible). Cumulatively, 0.4% of patients were eligible for 5 new medication groups, 4.1% for 4 new medication groups, 9.4% for 3 new medication groups, 10.1% for 2 new medication groups, and 22.7% for 1 new medication group; 15.0% were not eligible for new medications because of adequate prescribing at admission; and 38.4% were not eligible for any medications recommended by HF quality measures. Compared with newly indicated medications (mean, 1.45 ± 1.23), actual new prescriptions were lower (mean, 1.16 ± 1.00)., Conclusions: A quarter of patients hospitalized with HF need to start >1 medication to meet HF quality measures. Systems for addressing medication initiation and managing polypharmacy are central to HF transitional care., (© 2015 American Heart Association, Inc.)

Background: Electronic health records (EHRs) offer the opportunity to transform quality improvement by using clinical data for comparing hospital performance without the burden of chart abstraction. However, current performance measures using EHRs are lacking., Methods: With support from the Centers for Medicare & Medicaid Services (CMS), we developed an outcome measure of hospital risk-standardized 30-day mortality rates for patients with acute myocardial infarction for use with EHR data. As no appropriate source of EHR data are currently available, we merged clinical registry data from the Action Registry-Get With The Guidelines with claims data from CMS to develop the risk model (2009 data for development, 2010 data for validation). We selected candidate variables that could be feasibly extracted from current EHRs and do not require changes to standard clinical practice or data collection. We used logistic regression with stepwise selection and bootstrapping simulation for model development., Results: The final risk model included 5 variables available on presentation: age, heart rate, systolic blood pressure, troponin ratio, and creatinine level. The area under the receiver operating characteristic curve was 0.78. Hospital risk-standardized mortality rates ranged from 9.6% to 13.1%, with a median of 10.7%. The odds of mortality for a high-mortality hospital (+1 SD) were 1.37 times those for a low-mortality hospital (-1 SD)., Conclusions: This measure represents the first outcome measure endorsed by the National Quality Forum for public reporting of hospital quality based on clinical data in the EHR. By being compatible with current clinical practice and existing EHR systems, this measure is a model for future quality improvement measures.

Background: During a myocardial infarction, no single best approach of systemic anticoagulation is recommended, likely due to a lack of comparative effectiveness studies and trade-offs between treatments., Methods and Results: We investigated the patterns of use and site-level variability in anticoagulant strategies (unfractionated heparin [UFH] only, low-molecular-weight heparin [LMWH] only, UFH+LMWH, any bivalirudin) of 63 796 patients with a principal diagnosis of myocardial infarction treated with an early invasive strategy with percutaneous coronary intervention at 257 hospitals. About half (47%) of patients received UFH only, 6% UFH+LMWH, 7% LMWH only, and 40% bivalirudin. Compared with UFH, the median odds ratio was 2.90 for LMWH+UFH, 4.70 for LMWH only, and 3.09 for bivalirudin, indicating that 2 "identical" patients would have a 3- to 4-fold greater likelihood of being treated with anticoagulants other than UFH at one hospital compared with another. We then categorized hospitals as low- or high-users of LMWH and bivalirudin. Using hierarchical, multivariate regression models, we found that low bivalirudin-using hospitals had higher unadjusted bleeding rates, but the risk-adjusted and anticoagulant-adjusted bleeding rates did not differ across the hospital anticoagulation phenotypes. Risk-standardized mortality and risk-standardized length of stay also did not differ across hospital phenotypes., Conclusions: We found substantial site-level variability in the choice of anticoagulants for invasively managed acute myocardial infarction patients, even after accounting for patient factors. No single hospital-use pattern was found to be clinically superior. More studies are needed to determine which patients would derive the greatest benefit from various anticoagulants and to support consistent treatment of patients with the optimal anticoagulant strategy., (© 2015 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.)

Background: Despite recent reductions in national unplanned readmission rates, we have relatively little understanding of which hospital strategies are most associated with changes in risk-standardized readmission rates (RSRR)., Objective: We examined associations between the change in hospital 30-day RSRR for patients with heart failure and the uptake of strategies over 12-18 months in a national sample of hospitals., Design: We conducted a prospective study of hospitals using a Web-based survey at baseline (November 2010-May 2011, n = 599, 91.0% response rate) and 12-18 months later (November 2011-October 2012, n = 501, 83.6% response rate), with RSRR measured at the same time points. The final analytic sample included 478 hospitals., Participants: The study included hospitals participating in the Hospital-to-Home (H2H) and State Action on Avoidable Rehospitalizations (STAAR) initiatives., Main Measures: We examined associations between change in hospital 30-day RSRR for patients with heart failure and the uptake of strategies previously demonstrated to have increased between baseline and follow-up, using unadjusted and adjusted linear regression., Key Results: The average number of strategies taken up from baseline to follow-up was 1.6 (SE = 0.06); approximately one-quarter (25.3%) of hospitals took up at least three new strategies. Hospitals that adopted the strategy of routinely discharging patients with a follow-up appointment already scheduled experienced significant reductions in RSRR (reduction of 0.63 percentage point, p value < 0.05). Hospitals that took up three or more strategies had significantly greater reductions in RSRR compared to hospitals that took up only zero to two strategies (reduction of 1.29 versus 0.57 percentage point, p value < 0.05). Among the 117 hospitals that took up three or more strategies, 93 unique combinations of strategies were used., Conclusions: Although most individual strategies were not associated with RSRR reduction, hospitals that took up any three or more strategies showed significantly greater reduction in RSRR compared to hospitals that took up fewer than three strategies.

Background: Improving outcomes for patients with acute myocardial infarction (AMI) is a priority for hospital leadership, clinicians, and policymakers. Evidence suggests links between hospital organizational culture and hospital performance; however, few studies have attempted to shift organizational culture in order to improve performance, fewer have focused on patient outcomes, and none have addressed mortality for patients with AMI. We sought to address this gap through a novel longitudinal intervention study, Leadership Saves Lives (LSL)., Methods: This manuscript describes the methodology of LSL, a 2-year intervention study using a concurrent mixed methods design, guided by open systems theory and the Assess, Innovate, Develop, Engage, Devolve (AIDED) model of diffusion, implemented in 10 U.S. hospitals and their peer hospital networks. The intervention has three primary components: 1) annual convenings of the ten intervention hospitals; 2) semiannual workshops with guiding coalitions at each hospital; and 3) continuous remote support across all intervention hospitals through a web-based platform. Primary outcomes include 1) shifts in key dimensions of hospital organizational culture associated with lower mortality rates for patients with AMI; 2) use of targeted evidence-based practices associated with lower mortality rates for patients with AMI; and 3) in-hospital AMI mortality. Quantitative data include annual surveys of guiding coalition members in the intervention hospitals and peer network hospitals. Qualitative data include in-person, in-depth interviews with all guiding coalition members and selective observations of key interactions in care for patients with AMI, collected at three time points. Data integration will identify patterns and major themes in change processes across all intervention hospitals over time., Conclusions: LSL is novel in its use of a longitudinal mixed methods approach in a diverse sample of hospitals, its focus on objective outcome measures of mortality, and its examination of changes not only in the intervention hospitals but also in their peer hospital networks over time. This paper adds to the methodological literature for the study of complex interventions to promote hospital organizational culture change.

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

Objective: To characterize hospitals based on patterns of their combined financial and clinical outcomes for heart failure hospitalizations longitudinally., Data Source: Detailed cost and administrative data on hospitalizations for heart failure from 424 hospitals in the 2005-2011 Premier database., Study Design: Using a mixture modeling approach, we identified groups of hospitals with distinct joint trajectories of risk-standardized cost (RSC) per hospitalization and risk-standardized in-hospital mortality rate (RSMR), and assessed hospital characteristics associated with the distinct patterns using multinomial logistic regression., Principal Findings: During 2005-2011, mean hospital RSC decreased from $12,003 to $10,782, while mean hospital RSMR declined from 3.9 to 3.2 percent. We identified five distinct hospital patterns: highest cost and low mortality (3.2 percent of the hospitals), high cost and low mortality (20.4 percent), medium cost and low mortality (34.6 percent), medium cost and high mortality (6.2 percent), and low cost and low mortality (35.6 percent). Longer hospital stay and greater use of intensive care unit and surgical procedures were associated with phenotypes with higher costs or greater mortality., Conclusions: Hospitals vary substantially in the joint longitudinal patterns of cost and mortality, suggesting marked difference in value of care. Understanding determinants of the variation will inform strategies for improving the value of hospital care., (© Health Research and Educational Trust.)

Background: Existing publicly reported readmission measures are condition-specific, representing less than 20% of adult hospitalizations. An all-condition measure may better measure quality and promote innovation., Objective: To develop an all-condition, hospital-wide readmission measure., Design: Measure development study., Setting: 4821 U.S. hospitals., Patients: Medicare fee-for-service beneficiaries aged 65 years or older., Measurements: Hospital-level, risk-standardized unplanned readmissions within 30 days of discharge. The measure uses Medicare fee-for-service claims and is a composite of 5 specialty-based, risk-standardized rates for medicine, surgery/gynecology, cardiorespiratory, cardiovascular, and neurology cohorts. The 2007-2008 admissions were randomly split for development and validation. Models were adjusted for age, principal diagnosis, and comorbid conditions. Calibration in Medicare and all-payer data was examined, and hospital rankings in the development and validation samples were compared., Results: The development data set contained 8 018 949 admissions associated with 1 276 165 unplanned readmissions (15.9%). The median hospital risk-standardized unplanned readmission rate was 15.8 (range, 11.6 to 21.9). The 5 specialty cohort models accurately predicted readmission risk in both Medicare and all-payer data sets for average-risk patients but slightly overestimated readmission risk at the extremes. Overall hospital risk-standardized readmission rates did not differ statistically in the split samples (P = 0.71 for difference in rank), and 76% of hospitals' validation-set rankings were within 2 deciles of the development rank (24% were more than 2 deciles). Of hospitals ranking in the top or bottom deciles, 90% remained within 2 deciles (10% were more than 2 deciles) and 82% remained within 1 decile (18% were more than 1 decile)., Limitation: Risk adjustment was limited to that available in claims data., Conclusion: A claims-based, hospital-wide unplanned readmission measure for profiling hospitals produced reasonably consistent results in different data sets and was similarly calibrated in both Medicare and all-payer data., Primary Funding Source: Centers for Medicare & Medicaid Services.

Background: It is unknown whether hospitals with percutaneous coronary intervention (PCI) capability provide costlier care than hospitals without PCI capability for patients with acute myocardial infarction. The growing number of PCI hospitals and higher rate of PCI use may result in higher costs for episodes-of-care initiated at PCI hospitals. However, higher rates of transfers and postacute care procedures may result in higher costs for episodes-of-care initiated at non-PCI hospitals., Methods and Results: We identified all 2008 acute myocardial infarction admissions among Medicare fee-for-service beneficiaries by principal discharge diagnosis and classified hospitals as PCI- or non-PCI-capable on the basis of hospitals' 2007 PCI performance. We added all payments from admission through 30 days postadmission, including payments to hospitals other than the admitting hospital. We calculated and compared risk-standardized payment for PCI and non-PCI hospitals using 2-level hierarchical generalized linear models, adjusting for patient demographics and clinical characteristics. PCI hospitals had a higher mean 30-day risk-standardized payment than non-PCI hospitals (PCI, $20 340; non-PCI, $19 713; P<0.001). Patients presenting to PCI hospitals had higher PCI rates (39.2% versus 13.2%; P<0.001) and higher coronary artery bypass graft rates (9.5% versus 4.4%; P<0.001) during index admissions, lower transfer rates (2.2% versus 25.4%; P<0.001), and lower revascularization rates within 30 days (0.15% versus 0.27%; P<0.0001) than those presenting to non-PCI hospitals., Conclusions: Despite higher PCI and coronary artery bypass graft rates for Medicare patients initially presenting to PCI hospitals, PCI hospitals were only $627 costlier than non-PCI hospitals for the treatment of patients with acute myocardial infarction in 2008., (© 2014 American Heart Association, Inc.)

Background: Survival rates after acute myocardial infarction (AMI) vary markedly across U.S. hospitals. Although substantial efforts have been made to improve hospital performance, we lack contemporary evidence about changes in hospital strategies and features of organizational culture that might contribute to reducing hospital AMI mortality rates. We sought to describe current use of several strategies and features of organizational culture linked to AMI mortality in a national sample of hospitals and examine changes in use between 2010 and 2013., Methods: We conducted a cross-sectional survey of 543 hospitals (70% response rate) in 2013, and longitudinal analysis of a subsample of 107 hospitals that had responded to a survey in 2010 (67% response rate)., Results: Between 2010 and 2013, the use of many strategies increased, but the use of only two strategies increased significantly: the percentage of hospitals providing regular training to Emergency Medical Service (EMS) providers about AMI care increased from 36% to 71% (P-value < 0.001) and the percentage of hospitals using computerized assisted physician order entry more than doubled (P-value < 0.001). Most, but not all, hospitals reported having environments conducive to communication, coordination and problem solving., Conclusions: We found few significant changes between 2010 and 2013 in hospital strategies or in key features of organizational culture that have been associated with lower AMI mortality rates. Findings highlight several opportunities to help close remaining performance gaps in AMI mortality among hospitals.

Background: Variation in hospital admission rates of patients presenting to the emergency department (ED) may represent an opportunity to improve practice. We seek to describe national variation in hospital admission rates from the ED and to determine the degree to which variation is not explained by patient characteristics or hospital factors., Methods: We conducted a cross-sectional analysis of a nationally representative sample of ED visits among adults within the 2010 National Hospital Ambulatory Care Survey ED data of hospitals with admission rates from the ED between 5% and 50%. We calculated risk-standardized hospital admission rates (RSARs) from the ED using contemporary hospital profiling methodology, accounting for patients' sociodemographic and clinical characteristics., Results: Among 19831 adult ED visits in 252 hospitals, there were 4148 hospital admissions from the ED. After accounting for patients' sociodemographic and clinical factors, the median RSAR from the ED was 16.9% (interquartile range, 15.0%-20.4%), and 8.1% of the variation in RSARs was attributable to an institution-specific effect. Even after accounting for hospital teaching status, ownership, urban/rural location, and geographical location, 7.0% of the variation in RSARs from the ED was still attributable to an institution-specific effect., Conclusions and Relevance: There was variation in hospital admission rates from the ED in the United States, even after adjusting for patients' sociodemographic and clinical characteristics and accounting for hospital factors. Our findings suggest that suggesting that the likelihood of being admitted from the ED is not only dependent on clinical factors but also at which hospital the patient seeks care., (Published by Elsevier Inc.)

Introduction: During the past decade, the volume of percutaneous coronary intervention (PCI) in China has risen by more than 20-fold. Yet little is known about patterns of care and outcomes across hospitals, regions and time during this period of rising cardiovascular disease and dynamic change in the Chinese healthcare system., Methods and Analysis: Using the China PEACE (Patient-centered Evaluative Assessment of Cardiac Events) research network, the Retrospective Study of Coronary Catheterisation and Percutaneous Coronary Intervention (China PEACE-Retrospective CathPCI Study) will examine a nationally representative sample of 11 900 patients who underwent coronary catheterisation or PCI at 55 Chinese hospitals during 2001, 2006 and 2011. We selected patients and study sites using a two-stage cluster sampling design with simple random sampling stratified within economical-geographical strata. A central coordinating centre will monitor data quality at the stages of case ascertainment, medical record abstraction and data management. We will examine patient characteristics, diagnostic testing patterns, procedural treatments and in-hospital outcomes, including death, complications of treatment and costs of hospitalisation. We will additionally characterise variation in treatments and outcomes by patient characteristics, hospital, region and study year., Ethics and Dissemination: The China PEACE collaboration is designed to translate research into improved care for patients. The study protocol was approved by the central ethics committee at the China National Center for Cardiovascular Diseases (NCCD) and collaborating hospitals. Findings will be shared with participating hospitals, policymakers and the academic community to promote quality monitoring, quality improvement and the efficient allocation and use of coronary catheterisation and PCI in China., Registration Details: http://www.clinicaltrials.gov (NCT01624896).

Background and Purpose: Stroke is the fourth-leading cause of death and a leading cause of long-term major disability in the United States. Measuring outcomes after stroke has important policy implications. The primary goals of this consensus statement are to (1) review statistical considerations when evaluating models that define hospital performance in providing stroke care; (2) discuss the benefits, limitations, and potential unintended consequences of using various outcome measures when evaluating the quality of ischemic stroke care at the hospital level; (3) summarize the evidence on the role of specific clinical and administrative variables, including patient preferences, in risk-adjusted models of ischemic stroke outcomes; (4) provide recommendations on the minimum list of variables that should be included in risk adjustment of ischemic stroke outcomes for comparisons of quality at the hospital level; and (5) provide recommendations for further research., Methods and Results: This statement gives an overview of statistical considerations for the evaluation of hospital-level outcomes after stroke and provides a systematic review of the literature for the following outcome measures for ischemic stroke at 30 days: functional outcomes, mortality, and readmissions. Data on outcomes after stroke have primarily involved studies conducted at an individual patient level rather than a hospital level. On the basis of the available information, the following factors should be included in all hospital-level risk-adjustment models: age, sex, stroke severity, comorbid conditions, and vascular risk factors. Because stroke severity is the most important prognostic factor for individual patients and appears to be a significant predictor of hospital-level performance for 30-day mortality, inclusion of a stroke severity measure in risk-adjustment models for 30-day outcome measures is recommended. Risk-adjustment models that do not include stroke severity or other recommended variables must provide comparable classification of hospital performance as models that include these variables. Stroke severity and other variables that are included in risk-adjustment models should be standardized across sites, so that their reliability and accuracy are equivalent. There is a pressing need for research in multiple areas to better identify methods and metrics to evaluate outcomes of stroke care., Conclusions: There are a number of important methodological challenges in undertaking risk-adjusted outcome comparisons to assess the quality of stroke care in different hospitals. It is important for stakeholders to recognize these challenges and for there to be a concerted approach to improving the methods for quality assessment and improvement.

Background: Prior claims analyses suggest that the use of intravenous inotropic therapy for patients hospitalized with heart failure varies substantially by hospital. Whether differences in the clinical characteristics of the patients explain observed differences in the use of inotropic therapy is not known., Methods and Results: We sought to characterize institutional variation in inotrope use among patients hospitalized with heart failure before and after accounting for clinical factors of patients. Hierarchical generalized linear regression models estimated risk-standardized hospital-level rates of inotrope use within 209 hospitals participating in Get With The Guidelines-Heart Failure (GWTG-HF) registry between 2005 and 2011. The association between risk-standardized rates of inotrope use and clinical outcomes was determined. Overall, an inotropic agent was administered in 7691 of 126 564 (6.1%) heart failure hospitalizations: dobutamine 43%, dopamine 24%, milrinone 17%, or a combination 16%. Patterns of inotrope use were stable during the 7-year study period. Use of inotropes varied significantly between hospitals even after accounting for patient and hospital characteristics (median risk-standardized hospital rate, 5.9%; interquartile range, 3.7%-8.6%; range, 1.3%-32.9%). After adjusting for case-mix and hospital structural differences, model intraclass correlation indicated that 21% of the observed variation in inotrope use was potentially attributable to random hospital effects (ie, institutional preferences). Hospitals with higher risk-standardized inotrope use had modestly longer risk-standardized length of stay (P=0.005) but had no difference in risk-standardized inpatient mortality (P=0.12)., Conclusions: Use of intravenous inotropic agents during hospitalization for heart failure varies significantly among US hospitals even after accounting for patient and hospital factors.

Background: Public reporting on hospital quality has been widely adopted for common medical conditions. Adding a measure of inpatient survival after cardiac arrest is being considered. It is unknown whether this measure would be redundant, given evidence that hospital organization and culture can have hospital-wide effects on quality. Therefore, we sought to evaluate the correlation between inpatient survival after cardiac arrest and 30-day risk-standardized mortality rates for common medical conditions., Methods and Results: Using data between 2007 and 2010 from a national in-hospital cardiac arrest registry, we calculated risk-standardized in-hospital survival rates for cardiac arrest at each hospital. We obtained risk-standardized 30-day mortality rates for acute myocardial infarction, heart failure, and pneumonia from Hospital Compare for the same period. The relationship between a hospital's performance on cardiac arrest and these other medical conditions was assessed using weighted Pearson correlation coefficients. Among 26 270 patients with in-hospital cardiac arrest at 130 hospitals, survival rates varied across hospitals, with a median risk-standardized hospital survival rate of 22.1% and an interquartile range of 19.7% to 24.2%. There were no significant correlations between a hospital's outcomes for its cardiac arrest patients and its patients admitted for acute myocardial infarction (correlation, -0.12; P=0.16), heart failure (correlation, -0.05; P=0.57), or pneumonia (correlation, -0.15; P=0.10)., Conclusions: Hospitals that performed better on publicly reported outcomes for 3 common medical conditions did not necessarily have better cardiac arrest survival rates. Public reporting on cardiac arrest outcomes could provide new information about hospital quality.

Importance: With growing national focus on reducing readmissions, there is a need to comprehensively assess the quality of transitional care, including discharge practices, patient perspectives, and patient understanding., Objective: To conduct a multifaceted evaluation of transitional care from a patient-centered perspective., Design: Prospective observational cohort study, May 2009 through April 2010., Setting: Urban, academic medical center., Participants: Patients 65 years and older discharged home after hospitalization for acute coronary syndrome, heart failure, or pneumonia., Main Outcomes and Measures: Discharge practices, including presence of follow-up appointment and patient-friendly discharge instructions; patient understanding of diagnosis and follow-up appointment; and patient perceptions of and satisfaction with discharge care., Results: The 395 enrolled patients (66.7% of those eligible) had a mean age of 77.2 years. Although 349 patients (95.6%) reported understanding the reason they had been in the hospital, only 218 patients (59.6%) were able to accurately describe their diagnosis in postdischarge interviews. Discharge instructions routinely included symptoms to watch out for (98.4%), activity instructions (97.3%), and diet advice (89.7%) in lay language; however, 99 written reasons for hospitalization (26.3%) did not use language likely to be intelligible to patients. Of the 123 patients (32.6%) discharged with a scheduled primary care or cardiology appointment, 54 (43.9%) accurately recalled details of either appointment. During postdischarge interviews, 118 patients (30.0%) reported receiving less than 1 day’s advance notice of discharge, and 246 (66.1%) reported that staff asked whether they would have the support they needed at home before discharge., Conclusions and Relevance: Patient perceptions of discharge care quality and self-rated understanding were high, and written discharge instructions were generally comprehensive although not consistently clear. However, follow-up appointments and advance discharge planning were deficient, and patient understanding of key aspects of postdischarge care was poor. Patient perceptions and written documentation do not adequately reflect patient understanding of discharge care.

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

Background: Despite increasing attention on reducing relatively costly hospital practices while maintaining the quality of care, few studies have examined how hospitals use the intensive care unit (ICU), a high-cost setting, for patients admitted with heart failure (HF). We characterized hospital patterns of ICU admission for patients with HF and determined their association with the use of ICU-level therapies and patient outcomes., Methods and Results: We identified 166 224 HF discharges from 341 hospitals in the 2009-2010 Premier Perspective database. We excluded hospitals with <25 HF admissions, patients <18 years old, and transfers. We defined ICU as including medical ICU, coronary ICU, and surgical ICU. We calculated the percent of patients admitted directly to an ICU. We compared hospitals in the top quartile (high ICU admission) with the remaining quartiles. The median percentage of ICU admission was 10% (interquartile range, 6%-16%; range, 0%-88%). In top-quartile hospitals, treatments requiring an ICU were used less often; the percentage of ICU days receiving mechanical ventilation was 6% for the top quartile versus 15% for the others; noninvasive positive pressure ventilation, 8% versus 19%; vasopressors and/or inotropes, 9% versus 16%; vasodilators, 6% versus 12%; and any of these interventions, 26% versus 51%. Overall HF in-hospital risk-standardized mortality was similar (3.4% versus 3.5%; P=0.2)., Conclusions: ICU admission rates for HF varied markedly across hospitals and lacked association with in-hospital risk-standardized mortality. Greater ICU use correlated with fewer patients receiving ICU interventions. Judicious ICU use could reduce resource consumption without diminishing patient outcomes.

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.

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., (Copyright © 2012 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

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

Background: The increase in hospitalist-provided inpatient care may be accompanied by an expectation of improvement on patient outcomes. To date, the association between utilization of hospitalists and the publicly reported patient outcomes is unknown., Objective: Assess the relationship between hospitalist utilization and performance on 6 publicly reported patient outcomes., Design: Cross-sectional study., Participants: Representatives of 598 hospitals in the United States with direct knowledge of inpatient service models., Intervention: Survey of hospital personnel with knowledge of hospitalist use and hospitalist programs., Measurements: Six publicly reported quality outcome measures across 3 medical conditions: acute myocardial infarction (AMI), congestive heart failure (HF), and pneumonia. Using multivariable regression models, we assessed the relationship between presence of hospitalists and performance on each outcome measure; we further assessed the relationship between the percentage of patients admitted by hospitalists and each outcome measure., Results: Of 598 respondents, 429 (72%) reported the use of hospitalist services. In the comparison of hospitals with and without hospitalists, there was no statistically significant difference on any of the mortality or readmissions measures with the exception of the risk-stratified readmission rate for heart failure. For hospitals that used hospitalists, there was no significant change in any of the outcome measures with increasing percentage of patients admitted by hospitalists., Conclusions: The presence of hospitalists is not an independent predictor of performance on publicly reported mortality and readmissions measures for AMI, HF, or pneumonia. It is likely that broader system or organizational interventions are required to improve performance on patient outcomes., (Copyright © 2012 Society of Hospital Medicine.)

Background: Risk-standardized measures of hospital outcomes reported by the Centers for Medicare and Medicaid Services include Medicare fee-for-service (FFS) patients and exclude Medicare Advantage (MA) patients due to data availability. MA penetration varies greatly nationwide and seems to be associated with increased FFS population risk. Whether variation in MA penetration affects the performance on the Centers for Medicare and Medicaid Service measures is unknown., Objective: To determine whether the MA penetration rate is associated with outcomes measures based on FFS patients., Research Design: In this retrospective study, 2008 MA penetration was estimated at the Hospital Referral Region (HRR) level. Risk-standardized mortality rates and risk-standardized readmission rates for heart failure, acute myocardial infarction, and pneumonia from 2006 to 2008 were estimated among HRRs, along with several markers of FFS population risk. Weighted linear regression was used to test the association between each of these variables and MA penetration among HRRs., Results: Among 304 HRRs, MA penetration varied greatly (median, 17.0%; range, 2.1%-56.6%). Although MA penetration was significantly (P<0.05) associated with 5 of the 6 markers of FFS population risk, MA penetration was insignificantly (P≥0.05) associated with 5 of 6 hospital outcome measures., Conclusion: Risk-standardized mortality rates and risk-standardized readmission rates for heart failure, acute myocardial infarction, and pneumonia do not seem to differ systematically with MA penetration, lending support to the widespread use of these measures even in areas of high MA penetration.

Background: Despite recent improvements in survival after acute myocardial infarction (AMI), U.S. hospitals vary 2-fold in their 30-day risk-standardized mortality rates (RSMRs). Nevertheless, information is limited on hospital-level factors that may be associated with RSMRs., Objective: To identify hospital strategies that were associated with lower RSMRs., Design: Cross-sectional survey of 537 hospitals (91% response rate) and weighted multivariate regression by using data from the Centers for Medicare & Medicaid Services to determine the associations between hospital strategies and hospital RSMRs., Setting: Acute care hospitals with an annualized AMI volume of at least 25 patients., Participants: Patients hospitalized with AMI between 1 January 2008 and 31 December 2009., Measurements: Hospital performance improvement strategies, characteristics, and 30-day RSMRs., Results: In multivariate analysis, several hospital strategies were significantly associated with lower RSMRs and in aggregate were associated with clinically important differences in RSMRs. These strategies included holding monthly meetings to review AMI cases between hospital clinicians and staff who transported patients to the hospital (RSMR lower by 0.70 percentage points), having cardiologists always on site (lower by 0.54 percentage points), fostering an organizational environment in which clinicians are encouraged to solve problems creatively (lower by 0.84 percentage points), not cross-training nurses from intensive care units for the cardiac catheterization laboratory (lower by 0.44 percentage points), and having physician and nurse champions rather than nurse champions alone (lower by 0.88 percentage points). Fewer than 10% of hospitals reported using at least 4 of these 5 strategies., Limitation: The cross-sectional design demonstrates statistical associations but cannot establish causal relationships., Conclusion: Several strategies, which are currently implemented by relatively few hospitals, are associated with significantly lower 30-day RSMRs for patients with AMI., Primary Funding Source: The Agency for Healthcare Research and Quality, the United Health Foundation, and the Commonwealth Fund.

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.

Public reporting of patient outcomes following hospitalisation in Australia is limited compared with other countries. This will change, given recent commitments by state and federal governments to an Australian reporting program as part of health reform. There are numerous challenges in the design and implementation of such a program, including strategic decisions, statistical methods, and preventing risk aversion and perverse behaviour. Experience in other countries is likely to provide valuable lessons and tools for Australia as it seeks to build its reporting capacity.