Search

Objectives As the predominant approach to acute reperfusion for ST segment elevation myocardial infarction (STEMI) in many countries, fibrinolytic therapy provides a relative risk reduction for death of ∼16% across the range of baseline risk. For patients with low baseline mortality risk, fibrinolytic therapy may therefore provide little benefit, which may be offset by the risk of major bleeding. We aimed to construct a tool to determine if it is possible to identify a low-risk group among fibrinolytic therapy-eligible patients. Design Cross-sectional study. Setting The China Patient-centered Evaluative Assessment of Cardiac Events (PEACE) study includes a nationally representative retrospective sample of patients admitted with acute myocardial infarction (AMI) in 162 hospitals. Participants 3741 patients with STEMI who were fibrinolytic-eligible but did not receive reperfusion therapy. Main outcome measures In-hospital mortality, which was defined as a composite of death occurring within hospitalisation or withdrawal from treatment due to a terminal status at discharge. Results In the study cohort, the in-hospital mortality was 14.7%. In the derivation cohort and the validation cohort, the combination of systolic blood pressure (≥100 mm Hg), age (

This comparative effectiveness study examines current US Centers for Medicare & Medicaid Services 30-day mortality risk models vs novel risk models for acute myocardial infarction, heart failure, and pneumonia hospitalizations., Key Points Question Could present on admission indicators and ungrouped diagnostic codes enhance risk models for acute myocardial infarction, heart failure, and pneumonia mortality measures and improve discrimination of hospital-level performance? Findings In this comparative effectiveness study including all Medicare fee-for-service beneficiaries hospitalized for acute myocardial infarction, heart failure, or pneumonia at acute care hospitals, incorporating present on admission coding and ungrouped historical and index admission International Classification of Diseases, Ninth Revision, Clinical Modification codes was associated with greater discrimination in patient-level and hospital-level 30-day mortality risk models. Meaning Changes incurring no additional cost could enhance the risk adjustment for mortality and increase discrimination of hospital-level performance., Importance Risk adjustment models using claims-based data are central in evaluating health care performance. Although US Centers for Medicare & Medicaid Services (CMS) models apply well-vetted statistical approaches, recent changes in the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) coding system and advances in computational capabilities may provide an opportunity for enhancement. Objective To examine whether changes using already available data would enhance risk models and yield greater discrimination in hospital-level performance measures. Design, Setting, and Participants This comparative effectiveness study used ICD-9-CM codes from all Medicare fee-for-service beneficiary claims for hospitalizations for acute myocardial infarction (AMI), heart failure (HF), or pneumonia among patients 65 years and older from July 1, 2013, through September 30, 2015. Changes to current CMS mortality risk models were applied incrementally to patient-level models, and the best model was tested on hospital performance measures to model 30-day mortality. Analyses were conducted from April 19, 2018, to September 19, 2018. Main Outcomes and Measures The main outcome was all-cause death within 30 days of hospitalization for AMI, HF, or pneumonia, examined using 3 changes to current CMS mortality risk models: (1) incorporating present on admission coding to better exclude potential complications of care, (2) separating index admission diagnoses from those of the 12-month history, and (3) using ungrouped ICD-9-CM codes. Results There were 361 175 hospital admissions (mean [SD] age, 78.6 [8.4] years; 189 225 [52.4%] men) for AMI, 716 790 hospital admissions (mean [SD] age, 81.1 [8.4] years; 326 825 [45.6%] men) for HF, and 988 225 hospital admissions (mean [SD] age, 80.7 [8.6] years; 460 761 [46.6%] men) for pneumonia during the study; mean 30-day mortality rates were 13.8% for AMI, 12.1% for HF, and 16.1% for pneumonia. Each change to the models was associated with incremental gains in C statistics. The best model, incorporating all changes, was associated with significantly improved patient-level C statistics, from 0.720 to 0.826 for AMI, 0.685 to 0.776 for HF, and 0.715 to 0.804 for pneumonia. Compared with current CMS models, the best model produced wider predicted probabilities with better calibration and Brier scores. Hospital risk-standardized mortality rates had wider distributions, with more hospitals identified as good or bad performance outliers. Conclusions and Relevance Incorporating present on admission coding and using ungrouped index and historical ICD-9-CM codes were associated with improved patient-level and hospital-level risk models for mortality compared with the current CMS models for all 3 conditions.

We sought to evaluate concerns about US hospitals gaming readmission measures by deferring admissions for AMI and HF during the 30-day period to avoid readmission penalties. For 2011-2017, we calculated each hospital's daily rates of readmission from post-discharge day 1 to 60 for elderly Medicare

Background— Cardiovascular diseases are rising as a cause of death and disability in China. To improve outcomes for patients with these conditions, the Chinese government, academic researchers, clinicians, and >200 hospitals have created China Patient-Centered Evaluative Assessment of Cardiac Events (China PEACE), a national network for research and performance improvement. The first study from China PEACE, the Retrospective Study of Acute Myocardial Infarction (China PEACE-Retrospective AMI Study), is designed to promote improvements in acute myocardial infarction (AMI) quality of care by generating knowledge about the characteristics, treatments, and outcomes of patients hospitalized with AMI across a representative sample of Chinese hospitals during the past decade. Methods and Results— The China PEACE-Retrospective AMI Study will examine >18 000 patient records from 162 hospitals identified using a 2-stage cluster sampling design within economic–geographic regions. Records were chosen from 2001, 2006, and 2011 to identify temporal trends. Data quality will be monitored by a central coordinating center and will, in particular, address case ascertainment, data abstraction, and data management. Analyses will examine patient characteristics, diagnostic testing patterns, in-hospital treatments, in-hospital outcomes, and variation in results by time and site of care. In addition to publications, data will be shared with participating hospitals and the Chinese government to develop strategies to promote quality improvement. Conclusions— The China PEACE-Retrospective AMI Study is the first to leverage the China PEACE platform to better understand AMI across representative sites of care and during the past decade in China. The China PEACE collaboration among government, academicians, clinicians, and hospitals is poised to translate research about trends and patterns of AMI practices and outcomes into improved care for patients. Clinical Trial Registration— URL: http://www.clinicaltrials.gov . Unique identifier: NCT01624883.

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.

Safety-net hospitals, which include urban hospitals serving large numbers of low-income, uninsured, and otherwise vulnerable populations, have historically faced greater financial strains than hospitals that serve more affluent populations. These strains can affect hospitals’ quality of care, perhaps resulting in worse outcomes that are commonly used as indicators of care quality—mortality and readmission rates. We compared risk-standardized rates of both of these clinical outcomes among fee-for-service Medicare beneficiaries admitted for acute myocardial infarction, heart failure, or pneumonia. These beneficiaries were admitted to urban hospitals within Metropolitan Statistical Areas that contained at least one safety-net and at least one non-safety-net hospital. We found that outcomes varied across the urban areas for both safety-net and non-safety-net hospitals for all three conditions. However, mortality and readmission rates were broadly similar, with non-safety-net hospitals outperforming safety-net...

Background The number of percutaneous coronary interventions (PCI) in China has increased more than 20‐fold over the last decade. Consequently, there is a need for national‐level information to characterize PCI indications and long‐term patient outcomes, including health status, to understand and improve evolving practice patterns. Objectives: This nationwide prospective study of patients receiving PCI is to: (1) measure long‐term clinical outcomes (including death, acute myocardial infarction [AMI], and/or revascularization), patient‐reported outcomes (PROs), cardiovascular risk factor control and adherence to medications for secondary prevention; (2) determine patient‐ and hospital‐level factors associated with care process and outcomes; and (3) assess the appropriateness of PCI procedures. Methods: The China Patient‐centered Evaluative Assessment of Cardiac Events (PEACE) Prospective Study of PCI has enrolled 5,000 consecutive patients during 2012–2014 from 34 diverse hospitals across China undergoing PCI for any indication. We abstracted details of patient's medical history, treatments, and in‐hospital outcomes from medical charts, and conducted baseline, 1‐, 6‐, and 12‐month interviews to characterize patient demographics, risk factors, clinical presentation, healthcare utilization, and health status using validated PRO measures. The primary outcome, a composite measure of death, AMI and/or revascularization, as well as PROs, medication adherence and cardiovascular risk factor control, was assessed throughout the 12‐month follow‐up. Blood and urine samples were collected at baseline and 12 months and stored for future analyses. To validate reports of coronary anatomy, 2,000 angiograms are randomly selected and read by two independent core laboratories. Hospital characteristics regarding their facilities, processes and organizational characteristics are assessed by site surveys. Conclusion: China PEACE Prospective Study of PCI will be the first study to generate novel, high‐quality, comprehensive national data on patients’ socio‐demographic, clinical, treatment, and metabolic/genetic factors, and importantly, their long‐term outcomes following PCI, including health status. This will build the foundation for PCI performance improvement efforts in China. © 2016 The Authors. Catheterization and Cardiovascular Interventions. Published by Wiley Periodicals, Inc.

Background— National attention has increasingly focused on readmission as a target for quality improvement. We present the development and validation of a model approved by the National Quality Forum and used by the Centers for Medicare & Medicaid Services for hospital-level public reporting of risk-standardized readmission rates for patients discharged from the hospital after an acute myocardial infarction. Methods and Results— We developed a hierarchical logistic regression model to calculate hospital risk-standardized 30-day all-cause readmission rates for patients hospitalized with acute myocardial infarction. The model was derived using Medicare claims data for a 2006 cohort and validated using claims and medical record data. The unadjusted readmission rate was 18.9%. The final model included 31 variables and had discrimination ranging from 8% observed 30-day readmission rate in the lowest predictive decile to 32% in the highest decile and a C statistic of 0.63. The 25th and 75th percentiles of the risk-standardized readmission rates across 3890 hospitals were 18.6% and 19.1%, with fifth and 95th percentiles of 18.0% and 19.9%, respectively. The odds of all-cause readmission for a hospital 1 SD above average were 1.35 times that of a hospital 1 SD below average. Hospital-level adjusted readmission rates developed using the claims model were similar to rates produced for the same cohort using a medical record model (correlation, 0.98; median difference, 0.02 percentage points). Conclusions— This claims-based model of hospital risk-standardized readmission rates for patients with acute myocardial infarction produces estimates that are excellent surrogates for those produced from a medical record model.

Objectives: We examined patient accounts of illness and care among primary care patients whose medical services costs were high in order to illuminate factors associated with high cost. Methods: Thirty-three primary care patients with multiple chronic illnesses in an urban clinic serving a resource poor neighbourhood were selected from a range of high medical cost patients. Participants were interviewed with open-ended questions to investigate experiences of illnesses and care; their responses were examined for prominent themes using qualitative analysis methodology. Results: Patients sorted themselves into two categories based on the dominant focus of the roles of the care givers: one termed ‘professional’, in which the focus was on the competence and effectiveness of the care giver; and the second, ‘personal’, in which the focus was on the interpersonal relationship. Discussion: We examine similarities with other recent studies, suggest factors influencing these two different types of relationships such as intensity of involvement in the healthcare system as well as personality characteristics, and explore the challenge for healthcare programme development. We also noted that these two ways of conceptualizing the doctor—patient relationship may have adaptive or maladaptive consequences depending on the match between physician and patient.

Key Points Question What is the source of known disparities in outcomes after hospitalization according to patients’ race and socioeconomic status? Findings This cohort study found differences in outcomes by race and neighborhood income, but hospital performance within and between hospitals by patient race and neighborhood income was generally consistent. Meaning There was no evidence that specific hospitals that treated patients from a range of racial and socioeconomic backgrounds contributed to observed disparities after hospitalization, suggesting a systemic effect may be contributory., This cohort study uses Medicare claims data to compare performance within and between US hospitals concerning the association of race and neighborhood income with patient outcomes after hospitalization for acute myocardial infarction (AMI), heart failure, and pneumonia., 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

To determine whether simulation training of ultrasound (US)-guided central venous catheter (CVC) insertion skills on a partial task trainer improves cannulation and insertion success rates in clinical practice.This prospective, randomized, controlled, single-blind study of first- and second-year residents occurred at a tertiary care teaching hospital from January 2007 to September 2008. The intervention group (n = 90) received a didactic and hands-on, competency-based simulation training course in US-guided CVC insertion, whereas the control group (n = 95) received training through a traditional, bedside apprenticeship model. Success at first cannulation and successful CVC insertion served as the primary outcomes. Secondary outcomes included reduction in technical errors and decreased mechanical complications.Blinded independent raters observed 495 CVC insertions by 115 residents over a 21-month period. Successful first cannulation occurred in 51% of the intervention group versus 37% of the control group (P = .03). CVC insertion success occurred for 78% of the intervention group versus 67% of the control group (P = .02). Simulation training was independently and significantly associated with success at first cannulation (odds ratio: 1.7; 95% confidence interval: 1.1-2.8) and with successful CVC insertion (odds ratio: 1.7; 95% confidence interval: 1.1-2.8)--both independent of US use, patient comorbidities, or resident specialty. No significant differences related to technical errors or mechanical complications existed between the two groups.Simulation training was associated with improved in-hospital performance of CVC insertion. Procedural simulation was associated with improved residents' skills and was more effective than traditional training.

Objective To describe the level of obligation conveyed by deontic terms (words such as “should”, “may”, “must” and “is indicated”) commonly found in clinical practice guidelines. Design Cross-sectional electronic survey. Setting A clinical scenario was developed by the researchers, and recommendations containing 12 deontic terms and phrases were presented to the participants. Participants All 1332 registrants of the 2008 annual conference of the US Agency for Healthcare Research and Quality. Main outcome measures Participants indicated the level of obligation they believed guideline authors intended by using a slider mechanism ranging from “No obligation” (leftmost position recorded as 0) to “Full obligation” (rightmost position recorded as 100.) Results 445/1332 registrants (36%) submitted the on-line survey; 254/445 (57%) reported that they have experience in developing clinical practice guidelines; 133/445 (30%) indicated that they provide healthcare. “Must” conveyed the highest level of obligation (median=100) and least amount of variability (interquartile range=5.) “May” (median=37) and “may consider” (median=33) conveyed the lowest levels of obligation. All other terms conveyed intermediate levels of obligation characterised by wide and overlapping interquartile ranges. Conclusions Members of the health services community believe guideline authors intend variable levels of obligation when using different deontic terms within practice recommendations. Ranking of a subset of terms by intended level of obligation is possible. Matching deontic terminology to the intended recommendation strength can help standardise the use of deontic terminology by guideline developers.

Background: The Centers for Medicare & Medicaid Services (CMS) readmission measure is based on all-cause readmissions to any hospital within 30 days of discharge. Whether a measure based on same-hospital readmission, an outcome that is easier for hospitals and some systems to track, could serve as a proxy for the all-hospital measure is not known. Objectives: Evaluate whether same-hospital readmission rate is a good surrogate for all-hospital readmission rate. Research Design: The study population was derived from the Medicare inpatient, outpatient, and carrier (physician) Standard Analytic Files. Thirty-day risk-standardized readmission rates (RSRRs) for heart failure (HF) for both all-hospital readmission and same-hospital readmission were assessed by using hierarchical logistic regression models. Subjects: The sample consisted of 501,234 hospitalizations in 4674 hospitals with at least 1 hospitalization. Measures: Thirty-day readmission was defined as occurrence of at least 1 hospitalization in any US acute care hospital for any cause within 30 days of discharge after an index hospitalization. Same-hospital readmission was considered if the patient was admitted to the hospital that produced the original discharge within 30 days. Results: Overall, 80.9% of all HF readmissions occurred in the same-hospital, whereas 19.1% of readmissions occurred in a different hospital. The mean difference between all- versus same-hospital RSRR was 4.7 ± 1.0%, ranging from 0.9% to 10.5% across these hospitals with 25th, 50th, and 75th percentiles of 4.1%, 4.7%, and 5.2%, respectively, and was variable across the range of average RSRR. Conclusion: Same-hospital readmission rate is an unreliable and biased indicator of all-hospital readmission rate with limited value as a benchmark for quality of care processes.

Background— The rankings of “America’s Best Hospitals” by U.S. News & World Report are influential, but the performance of ranked hospitals in caring for patients with routine cardiac conditions such as heart failure is not known. Methods and Results— Using hierarchical regression models based on medical administrative data from the period July 1, 2005, to June 30, 2006, we calculated risk-standardized mortality rates and risk-standardized readmission rates for ranked and nonranked hospitals in the treatment of heart failure. The mortality analysis examined 14 813 patients in 50 ranked hospitals and 409 806 patients in 4761 nonranked hospitals. The readmission analysis included 16 641 patients in 50 ranked hospitals and 458 473 patients in 4627 nonranked hospitals. Mean 30-day risk-standardized mortality rates were lower in ranked versus nonranked hospitals (10.1% versus 11.2%, P P =0.40). The 30-day risk-standardized mortality rates varied widely for both ranked and nonranked hospitals, ranging from 7.9% to 12.4% for ranked hospitals and from 7.1% to 17.5% for nonranked hospitals. The 30-day risk-standardized readmission rates also spanned a large range, from 18.7% to 29.3% for ranked hospitals and from 19.2% to 29.8% for nonranked hospitals. Conclusions— Hospitals ranked by U.S. News & World Report as “America’s Best Hospitals” in “Heart & Heart Surgery” are more likely than nonranked hospitals to have a significantly lower than expected 30-day mortality rate, but there was much overlap in performance. For readmission, the rates were similar in ranked and nonranked hospitals.

Background— In 2009, the Centers for Medicare & Medicaid Services is publicly reporting hospital-level risk-standardized 30-day mortality and readmission rates after acute myocardial infarction (AMI) and heart failure (HF). We provide patterns of hospital performance, based on these measures. Methods and Results— We calculated the 30-day mortality and readmission rates for all Medicare fee-for-service beneficiaries ages 65 years or older with a primary diagnosis of AMI or HF, discharged between July 2005 and June 2008. We compared weighted risk-standardized mortality and readmission rates across Hospital Referral Regions and hospital structural characteristics. The median 30-day mortality rate was 16.6% for AMI (range, 10.9% to 24.9%; 25th to 75th percentile, 15.8% to 17.4%; 10th to 90th percentile, 14.7% to 18.4%) and 11.1% for HF (range, 6.6% to 19.8%; 25th to 75th percentile, 10.3% to 12.0%; 10th to 90th percentile, 9.4% to 13.1%). The median 30-day readmission rate was 19.9% for AMI (range, 15.3% to 29.4%; 25th to 75th percentile, 19.5% to 20.4%; 10th to 90th percentile, 18.8% to 21.1%) and 24.4% for HF (range, 15.9% to 34.4%; 25th to 75th percentile, 23.4% to 25.6%; 10th to 90th percentile, 22.3% to 27.0%). We observed geographic differences in performance across the country. Although there were some differences in average performance by hospital characteristics, there were high and low hospital performers among all types of hospitals. Conclusions— In a recent 3-year period, 30-day risk-standardized mortality rates for AMI and HF varied among hospitals and across the country. The readmission rates were particularly high.

Background: The volume of percutaneous coronary intervention (PCI) in China has increased more than 20-fold over the last decade. Consequently, there is a need for national-level information to characterize indications for PCI and its long-term outcomes, including health status improvement, which is the principal goal of PCI in stable patients. Objectives: To conduct a nationwide prospective study of patients receiving PCI and follow them to 1) measure long-term clinical outcomes, patient-reported outcomes (PROs), risk factor control and adherence to medications for secondary prevention; 2) determine patient- and hospital-level factors associated with these outcomes; and 3) assess indications for and appropriateness of the PCI procedures performed. Methods: The China PEACE Prospective Study of PCI, conducted from December 2012 to December 2014, has recruited 5000 consecutive patients undergoing PCI for any indication from 36 representative hospitals across China and followed them for 1-year. The follow-up rate at 12 months was 94%. After obtaining informed consent from each patient, we abstracted details of their medical history, treatments, and in-hospital outcomes from medical charts. We conducted baseline interviews to characterize patient demographics, risk factors, clinical presentation, and healthcare utilization. In addition, we used several validated instruments to measure PROs describing quality of life, symptoms, mood and sleep. The primary outcome, a composite measure of death, myocardial infarction and/or revascularization, was assessed at follow-up interviews conducted at 1-, 6- and 12-months after discharge. In addition, we measured PROs, medication adherence and risk factor control at these interviews. Blood and urine samples were collected at the 1- and 12-month interviews and stored for future analysis. To establish the appropriateness of PCI, the angiograms of 2000 randomly selected patients were reviewed by independent “core” labs in China and the United States. To complement these patient-level data, we surveyed participating hospitals to characterize their facilities, processes and organizational learning culture. Conclusion: This study will generate novel, high-quality, and comprehensive national data characterizing the patient experience after PCI in China.

Background: The incidence of acute myocardial infarction (AMI) is growing rapidly in China, but there is limited information about the patient experience in the post-acute period. Specifically, long-term outcomes and patient-reported outcomes (PROs), including quality of life, symptoms and mood, after AMI, have not been systematically studied in China. Objectives: To conduct a nationwide prospective study following patients after AMI that 1) measures long-term clinical outcomes, PROs, cardiovascular risk factor control and adherence to medications for secondary prevention; and 2) identifies patient characteristics and hospital attributes that are associated with these outcomes. Methods: The China PEACE Prospective Study of AMI has recruited 4000 consecutive patients from 55 hospitals across China and is following them for 1-year. The first patient was enrolled in December 2012, and the last follow-up visit is scheduled for June 2015. After obtaining informed consent from patients, we abstracted details of their medical history, treatment, and in-hospital outcomes from medical charts. We conducted comprehensive baseline interviews characterizing patient demographics, risk factors, clinical presentation, and healthcare utilization. In addition, we used validated PRO instruments to measure quality of life, symptoms, mood, sleep, cognition and sexual activity. Follow-up interviews, measuring PROs, medication adherence and risk factor control were conducted at 1-, 6-, and 12-months after discharge. At these interviews, patients were asked to self-report major health events and to provide supporting materials (e.g., hospital discharge record for a readmission), which were subsequently validated by a National Coordinating Center. Blood and urine samples were obtained at baseline and 12-month follow-up, and stored for further biomarker analysis and genetic studies. To complement these patient-level data, we surveyed participating hospitals to characterize their facilities, processes and organizational learning culture. Together, these data will be used to identify factors associated with various outcomes following AMI. Conclusion: This study is uniquely positioned to generate new information regarding patient experience and determinants of outcomes after AMI in China.

Objective To characterize the absolute risks for older patients of readmission to hospital and death in the year after hospitalization for heart failure, acute myocardial infarction, or pneumonia. Design Retrospective cohort study. Setting 4767 hospitals caring for Medicare fee for service beneficiaries in the United States, 2008-10. Participants More than 3 million Medicare fee for service beneficiaries, aged 65 years or more, surviving hospitalization for heart failure, acute myocardial infarction, or pneumonia. Main outcome measures Daily absolute risks of first readmission to hospital and death for one year after discharge. To illustrate risk trajectories, we identified the time required for risks of readmission to hospital and death to decline 50% from maximum values after discharge; the time required for risks to approach plateau periods of minimal day to day change, defined as 95% reductions in daily changes in risk from maximum daily declines after discharge; and the extent to which risks are higher among patients recently discharged from hospital compared with the general elderly population. Results Within one year of hospital discharge, readmission to hospital and death, respectively, occurred following 67.4% and 35.8% of hospitalizations for heart failure, 49.9% and 25.1% for acute myocardial infarction, and 55.6% and 31.1% for pneumonia. Risk of first readmission had declined 50% by day 38 after hospitalization for heart failure, day 13 after hospitalization for acute myocardial infarction, and day 25 after hospitalization for pneumonia; risk of death declined 50% by day 11, 6, and 10, respectively. Daily change in risk of first readmission to hospital declined 95% by day 45, 38, and 45; daily change in risk of death declined 95% by day 21, 19, and 21. After hospitalization for heart failure, acute myocardial infarction, or pneumonia, the magnitude of the relative risk for hospital admission over the first 90 days was 8, 6, and 6 times greater than that of the general older population; the relative risk of death was 11, 8, and 10 times greater. Conclusions Risk declines slowly for older patients after hospitalization for heart failure, acute myocardial infarction, or pneumonia and is increased for months. Specific risk trajectories vary by discharge diagnosis and outcome. Patients should remain vigilant for deterioration in health for an extended time after discharge. Health providers can use knowledge of absolute risks and their changes over time to better align interventions designed to reduce adverse outcomes after discharge with the highest risk periods for patients.

Objective To examine the association of hospital volume (a marker of quality of care) with hospital readmission rates. Design Retrospective cross-sectional study. Setting 4651US acute care hospitals. Study data 6 916 644 adult discharges, excluding patients receiving psychiatric or medical cancer treatment. Main outcome measures We used Medicare fee-for-service data from 1 July 2011 to 30 June 2012 to calculate observed-to-expected, unplanned, 30 day, standardized readmission rates for hospitals and for specialty cohorts medicine, surgery/gynecology, cardiorespiratory, cardiovascular, and neurology. We assessed the association of hospital volume by quintiles with 30 day, standardized readmission rates, with and without adjustment for hospital characteristics (safety net status, teaching status, geographic region, urban/rural status, nurse to bed ratio, ownership, and cardiac procedure capability. We also examined associations with the composite outcome of 30 day, standardized readmission or mortality rates. Results Mean 30 day, standardized readmission rate among the fifth of hospitals with the lowest volume was 14.7 (standard deviation 5.3) compared with 15.9 (1.7) among the fifth of hospitals with the highest volume (P

Background: The decision to replace or repair mitral valves is often a difficult decision, and outcomes from the patients’ perspective should guide decision-making. We investigated whether the change in health related quality of life (HRQOL) after mitral valve surgery is different after valve repairs compared with replacements.Methods: We prospectively studied 25 patients with mitral valve replacement and 45 patients with valve repairs performed in 1998–99. We measured HRQOL at baseline and at 18 months using the Medical Outcomes Trust Short Form 36-item Health Survey (SF-36) questionnaire. We compared mean HRQOL scores of the groups with age-adjusted U.S. population scores. We used analysis of covariance to determine a change in HRQOL within groups (repair or replacement) and if the change in HRQOL was different between the groups.Results: We found few differences between the groups, with more men and simultaneous coronary artery bypass graft surgery in the valve repair group and more prior operation in the valve replacement group. HRQOL improved after surgery in most domains, and was comparable to age-adjusted U.S. norms in the valve repair group. In the multivariable analysis, mitral valve repair recipients reported higher social functioning compared with patients who received valve replacement (p = 0.04). We did not find other statistically significant differences. However, the adjusted improvements in the component scales of physical functioning (PCS) and mental functioning (MCS) were substantial in the valve repair group (mean changes: PCS = 6.8, p = 0.003; MCS = 8.1, p = 0.014) and less pronounced in the replacement group (mean changes: PCS = 3.6, p = 0.09; MCS = 4.3, fsp = 0.16).Conclusions: While many considerations influence the decision to repair or replace mitral valves, these findings suggest that repair may be better from the health status perspective. Further studies are necessary to validate this finding.

Background— Depression is an established independent prognostic factor for mortality, readmission, and cardiac events after CABG surgery. However, limited data exist on whether depression influences functional outcomes after CABG. Methods and Results— We followed 963 patients who underwent first CABG between February 1999 and February 2001. At baseline and at 6 months after CABG, we interviewed patients to assess depressive symptoms using the Geriatric Depression Scale (GDS) and physical function using the Short Form-36 Physical Component Scale (PCS). The patient’s physical function was considered improved if the PCS score increased ≥5 points at 6 months. Patients with high GDS scores were younger, were more often female, and had worse physical function and higher comorbidity than patients with low GDS scores. Rates of improvement in physical function were 60.1% for a GDS score P =0.002 for the trend). Depressive symptoms remained a significant independent predictor of lack of functional improvement after adjustment for severity of coronary artery disease, angina class, baseline PCS score, and medical history. A GDS score ≥10 was a stronger inverse risk factor for functional improvement after CABG than such traditional measures of disease severity as previous myocardial infarction, heart failure on admission, history of diabetes, and left ventricular ejection fraction. Conclusions— Higher levels of depressive symptoms at the time of CABG are a strong risk factor for lack of functional benefits 6 months after CABG.

Background— Although previous studies have shown functional improvements in patients who undergo coronary artery bypass graft (CABG) surgery, data are conflicting on whether the gains achieved by women are similar to or less than those achieved by men. Methods and Results— We compared physical and psychological functional gains and readmission rates between 777 men and 295 women who underwent first CABG consecutively between February 1999 and February 2001. Physical function and mental health were measured by means of the Short Form 36-Item Health Survey (SF-36). At 6 months, both men and women showed, on average, a significant improvement in physical function and mental health, but men improved significantly more than women. After adjustment for baseline characteristics, the mean score improvement in women was half that of men for physical function (7.3 versus 14.0, P =0.0002) and 25% less than that of men for mental health (−3.0 versus 8.9, P =0.026). The absolute rates of adverse outcomes, such as hospital readmission, worsening functional status, and worsening mental health, were significantly higher in women (32.6%, 25.7%, and 17.5%, respectively) than in men (21.2%, 11.1%, and 12.6%, respectively) and remained significantly different in multivariable analysis. Conclusions— CABG surgery is associated with lower functional gains and higher readmission rates in women compared with men 6 months after operation.

OBJECTIVES This study was designed to examine whether female gender is associated with poorer recovery after coronary artery bypass graft (CABG) surgery. BACKGROUND The risks and benefits associated with CABG surgery in women are not as well established as they are in men, and there are concerns that women may have worse outcomes. The recovery period after CABG (the first four to eight weeks after the surgery) is a vulnerable time, with higher risks of complications and hospital readmission. There is little information on patients' experiences during this phase, particularly among women. METHODS We prospectively followed 1,113 patients (804 men and 309 women) who underwent first CABG consecutively between February 1999 and February 2001. Patients were interviewed at baseline and between six and eight weeks after surgery. Clinical data were abstracted from medical records. RESULTS Compared with men, women were older and more often had unstable angina and congestive heart failure, lower physical function (PF), and more depressive symptoms in the month before surgery. At six to eight weeks after CABG surgery, after adjustment for baseline characteristics, the rate of hospital readmission was 20.5% in women and 11.0% in men (p = 0.005), and the mean number of physical symptoms and side effects was 2.5 in women and 2 in men (p = 0.0009). Whereas, on average, PF remained unchanged in men (an increase in score of 0.3 points, 95% confidence interval [CI], -1.1 to 1.8) and depressive symptoms improved (a decrease of 0.2 depressive symptoms, 95% CI, -0.4 to -0.04), women showed, on average, a 13-point decline in physical function (95% CI, -15.8 to -10.4) and an increase of 0.5 in depressive symptoms (95% CI, 0.1 to 0.9). CONCLUSIONS After CABG surgery, women have a more difficult recovery compared with men, which is not explained by illness severity, presurgery health status, or other patient characteristics.

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

Background: Admissions among ambulatory patients with heart failure (HF) is a key quality metric for Accountable Care Organizations (ACOs). Yet HF patients are at risk for many acute illnesses, HF and non-HF related, and it is unknown whether specific types of admissions explain lower or higher ACO

Background: After hospitalization for heart failure (HF) and acute myocardial infarction (AMI), patients experience increased risk of death and hospital readmission. Defining the trajectory and timing of this period of risk may help guide interventions to improve post-discharge outcomes. Methods: We used 2008-10 Medicare data to identify patients ≥65 years discharged alive after HF or AMI hospitalization. Using hazard rates, we characterized the risks of death and first readmission on each day after discharge to describe (1) the maximum daily risks of death and readmission after discharge; (2) risks of death and readmission 1 year after discharge; (3) the time in days after discharge for the risks of death and readmission to reach their maximum daily rates and 50% of their maximum daily rates to characterize the rapidity of decline in risk. We created separate survival models for death and first readmission. Data were censored after 1 year follow up. The readmission model also censored for death prior to readmission. Results: Of 878,963 HF hospitalizations, 367,542 (41.8%) died and 618,283 (70.3%) were readmitted in 1 year. Of 350,509 AMI hospitalizations, 90,623 (25.9%) died and 177,031(50.5%) were readmitted in 1 year. The Figure shows hazard rates by time after discharge. For HF, daily risk of death was 0.0056 maximally and 0.0011 at 1 year (19% of maximum). Daily risk of readmission was 0.013 maximally and 0.002 at 1 year (16% of maximum). Daily risk of death was highest 1 day after discharge and 50% less 11 days after discharge. Daily risk of readmission was highest 4 days after discharge and 50% less 49 days after discharge. For AMI, daily risk of death was 0.010 maximally and 0.0004 at 1 year (4% of maximum). Daily risk of readmission was 0.015 maximally and 0.0011 at 1 year (7% of maximum). Daily risk of death was highest 1 day after discharge and 50% less 6 days after discharge. Daily risk of readmission was highest 2 days after discharge and 50% less 13 days after discharge. Conclusions: After hospitalization for HF and AMI, risk of death is highest on day 1 after discharge and then declines rapidly. In contrast, risk of readmission peaks later and declines more slowly. This extended period of risk for readmission may justify continued vigilance beyond the 30-day period used by Medicare to evaluate hospital readmission performance.

BACKGROUND The Centers for Medicare & Medicaid Services publicly reports risk-standardized mortality rates (RSMRs) within 30-days of admission and, in 2013, risk-standardized unplanned readmission rates (RSRRs) within 30-days of discharge for patients hospitalized with acute myocardial infarction (AMI), heart failure (HF), and pneumonia. Current publicly reported data do not focus on variation in national results or annual changes. OBJECTIVE Describe U.S. hospital performance on AMI, HF, and pneumonia mortality and updated readmission measures to provide perspective on national performance variation. DESIGN To identify recent changes and variation in national hospital-level mortality and readmission for AMI, HF, and pneumonia, we performed cross-sectional panel analyses of national hospital performance on publicly reported measures. PARTICIPANTS Fee-for-service Medicare and Veterans Health Administration beneficiaries, 65 years or older, hospitalized with principal discharge diagnoses of AMI, HF, or pneumonia between July 2009 and June 2012. RSMRs/RSRRs were calculated using hierarchical logistic models risk-adjusted for age, sex, comorbidities, and patients’ clustering among hospitals. Results Median (range) RSMRs for AMI, HF, and pneumonia were 15.1% (9.4–21.0%), 11.3% (6.4–17.9%), and 11.4% (6.5–24.5%), respectively. Median (range) RSRRs for AMI, HF, and pneumonia were 18.2% (14.4–24.3%), 22.9% (17.1–30.7%), and 17.5% (13.6–24.0%), respectively. Median RSMRs declined for AMI (15.5% in 2009–2010, 15.4% in 2010–2011, 14.7% in 2011–2012) and remained similar for HF (11.5% in 2009–2010, 11.9% in 2010–2011, 11.7% in 2011–2012) and pneumonia (11.8% in 2009–2010, 11.9% in 2010–2011, 11.6% in 2011–2012). Median hospital-level RSRRs declined: AMI (18.5% in 2009–2010, 18.5% in 2010–2011, 17.7% in 2011–2012), HF (23.3% in 2009–2010, 23.1% in 2010–2011, 22.5% in 2011–2012), and pneumonia (17.7% in 2009–2010, 17.6% in 2010–2011, 17.3% in 2011–2012). Conclusions We report the first national unplanned readmission results demonstrating declining rates for all three conditions between 2009–2012. Simultaneously, AMI mortality continued to decline, pneumonia mortality was stable, and HF mortality experienced a small increase. Electronic supplementary material The online version of this article (doi:10.1007/s11606-014-2862-5) contains supplementary material, which is available to authorized users.

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% (r 2 = 0.029), with the correlation most prominent for hospitals with RSMR 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.

Importance To better guide strategies intended to reduce high rates of 30-day readmission after hospitalization for heart failure (HF), acute myocardial infarction (MI), or pneumonia, further information is needed about readmission diagnoses, readmission timing, and the relationship of both to patient age, sex, and race. Objective To examine readmission diagnoses and timing among Medicare beneficiaries readmitted within 30 days after hospitalization for HF, acute MI, or pneumonia. Design, Setting, and Patients We analyzed 2007-2009 Medicare fee-for-service claims data to identify patterns of 30-day readmission by patient demographic characteristics and time after hospitalization for HF, acute MI, or pneumonia. Readmission diagnoses were categorized using an aggregated version of the Centers for Medicare & Medicaid Services' Condition Categories. Readmission timing was determined by day after discharge. Main Outcome Measures We examined the percentage of 30-day readmissions occurring on each day (0-30) after discharge; the most common readmission diagnoses occurring during cumulative periods (days 0-3, 0-7, 0-15, and 0-30) and consecutive periods (days 0-3, 4-7, 8-15, and 16-30) after hospitalization; median time to readmission for common readmission diagnoses; and the relationship between patient demographic characteristics and readmission diagnoses and timing. Results From 2007 through 2009, we identified 329 308 30-day readmissions after 1 330 157 HF hospitalizations (24.8% readmitted), 108 992 30-day readmissions after 548 834 acute MI hospitalizations (19.9% readmitted), and 214 239 30-day readmissions after 1 168 624 pneumonia hospitalizations (18.3% readmitted). The proportion of patients readmitted for the same condition was 35.2% after the index HF hospitalization, 10.0% after the index acute MI hospitalization, and 22.4% after the index pneumonia hospitalization. Of all readmissions within 30 days of hospitalization, the majority occurred within 15 days of hospitalization: 61.0%, HF cohort; 67.6%, acute MI cohort; and 62.6%, pneumonia cohort. The diverse spectrum of readmission diagnoses was largely similar in both cumulative and consecutive periods after discharge. Median time to 30-day readmission was 12 days for patients initially hospitalized for HF, 10 days for patients initially hospitalized for acute MI, and 12 days for patients initially hospitalized for pneumonia and was comparable across common readmission diagnoses. Neither readmission diagnoses nor timing substantively varied by age, sex, or race. Conclusion and Relevance Among Medicare fee-for-service beneficiaries hospitalized for HF, acute MI, or pneumonia, 30-day readmissions were frequent throughout the month after hospitalization and resulted from a similar spectrum of readmission diagnoses regardless of age, sex, race, or time after discharge.

Background: Despite numerous studies of telemonitoring (TM), the use of technology to monitor patients remotely, information about patients' adoption and adherence to using such technologies is scarce. The objective of this study was to determine the patient characteristics associated with: 1) initiating use of TM and 2) adherence to using daily TM over 6 months. Methods: We evaluated all 826 patients enrolled in the TM arm of the Tele-HF multicenter RCT. TM consisted of a telephone-based interactive voice response system whereby patients reported symptoms and weight daily for 6 months. The adherence rate was calculated as the # of weeks the patient used the TM system at least 3 days/week over 6-month study period. Multivariable hierarchical regression was used to identify factors independently associated with initiation of and adherence to TM. Results: The mean ± SD age of patients was 61.1 ± 15.3 years (range 19-90), 44% were women, and 50% were of minority race. Overall, 14% (119/ 826) never initiated use of TM. In the multivariable analysis, younger patients (age < 65) and patients with higher satisfaction with care were more likely to initiate TM (p-values ≤ .03) (Figure). Among the 707 patients who initiated TM, adherence averaged 90% in week 1 and 55% in week 26. Younger patients and those with lower health literacy had lower rates of adherence to using TM over 6 months (p-values ≤ .004). Conclusion: Age, satisfaction with care and health literacy were associated with utilization of a TM system for the management of HF. Understanding more about how patient nonclinical factors impact use of new technologies such as TM, may improve the design and effectiveness of TM strategies.

Background: There is wide variation in regional admission and readmission rates and the association between the two is unknown. We sought to determine this association and whether it differs between heart failure (HF) admissions, more discretionary, and acute myocardial infarction (AMI) admissions, less discretionary. Methods: We used 2006-2008 Medicare ICD-9-CM claims data to determine AMI and HF admissions. Hospital referral region (HRR) admission rates were determined using Medicare denominator files. We estimated hospital level 30-day risk standardized readmission rates using hierarchical logistic models adjusting for age, sex and comorbidities and then aggregated them to HRRs level RSRRs. The correlation (R 2 ) obtained by weighted linear regression characterized the relationship between admission rates and RSRRs for AMI and HF. Results: Among 306 HRRs, the median AMI admission was 9.2 per 1000 enrollees (range 2.8 to 26.5) and the median HF admission rate was 19.6 (range 7.6 to 41.4). Among the 306 HRRs, the median AMI RSRR was 0.196 (range 0.163 to 0.233) and the median HF RSRR was 0.242 (range 0.201 to 0.289). Regional AMI admission rate was weakly correlated with AMI RSRR (R 2 0.05, 95% CI 0.02 - 0.11) and HF RSRR (R 2 0.07, 95% CI 0.02 - 0.13). Regional HF admission rate was modestly correlated with both AMI RSRR (R 2 0.28, 95% CI 0.20 - 0.37) and HF RSRR (R 2 0.32, 95% CI 0.24 - 0.41). Conclusion: The modest association between HF admissions, a more discretionary admission condition, and both AMI and HF readmission rates suggest a systemic propensity to admit and readmit patients. In contrast, the same was not true of AMI, a less discretionary admission condition.

Background Substantial hospital-level variation in the risk of readmission after hospitalization for heart failure (HF) or acute myocardial infarction (AMI) has been reported. Prior studies have documented considerable state-level variation in rates of discharge to skilled nursing facilities (SNFs), but evaluation of hospital-level variation in SNF rates and its relationship to hospital-level readmission rates is limited. Methods Hospital-level 30-day all-cause risk-standardized readmission rates (RSRRs) were calculated using claims data for fee-for-service Medicare patients hospitalized with a principal diagnosis of HF or AMI from 2006-2008. Medicare claims were used to calculate rates of discharge to SNF following HF-specific or AMI-specific admissions in hospitals with ≥25 HF or AMI patients, respectively. Weighted regression was used to quantify the relationship between RSRRs and SNF rates for each condition. Results Mean RSRR following HF admission among 4101 hospitals was 24.7%, and mean RSRR after AMI admission among 2453 hospitals was 19.9%. Hospital-level SNF rates ranged from 0% to 83.8% for HF and from 0% to 77.8% for AMI. No significant relationship between RSRR after HF and SNF rate was found in adjusted regression models ( P =.15). RSRR after AMI increased by 0.03 percentage point for each 1 absolute percentage point increase in SNF rate in adjusted regression models ( P =.001). Overall, HF and AMI SNF rates explained Conclusion SNF rates after HF or AMI hospitalization vary considerably across hospitals, but explain little of the variation in 30-day all-cause readmission rates for these conditions.

To compare the results of minimally invasive parathyroidectomy (MIP) and conventional parathyroid surgery.Primary hyperparathyroidism is a common endocrine disorder often treated by surgical intervention. Outpatient MIP, employing image-directed focused exploration under cervical block anesthesia, has replaced traditional surgical approaches for many patients with primary hyperparathyroidism. This retrospective review of a prospective database compared MIP with conventional parathyroid surgery.One thousand six hundred fifty consecutive patients underwent surgery for primary hyperparathyroidism by a single surgeon between 1990 and 2009 at 2 tertiary care academic hospitals. Conventional bilateral cervical exploration under general anesthesia was performed in 613 patients and MIP was performed in 1037 cases. Cure rates, complication rates, pathologic findings, length of hospital stay, and total hospital costs were compared.Minimally invasive parathyroidectomy is associated with improvements in the cure rate (99.4%) and the complication rate (1.45%) compared to conventional exploration with a cure rate of 97.1% and a complication rate of 3.10%. In addition, the hospital length of stay and total hospital charges were also improved compared to conventional surgery.Minimally invasive parathyroidectomy is a superior technique and should be adopted for the majority of patients with sporadic primary hyperparathyroidism.

Small studies suggest that telemonitoring may improve heart-failure outcomes, but its effect in a large trial has not been established.We randomly assigned 1653 patients who had recently been hospitalized for heart failure to undergo either telemonitoring (826 patients) or usual care (827 patients). Telemonitoring was accomplished by means of a telephone-based interactive voice-response system that collected daily information about symptoms and weight that was reviewed by the patients' clinicians. The primary end point was readmission for any reason or death from any cause within 180 days after enrollment. Secondary end points included hospitalization for heart failure, number of days in the hospital, and number of hospitalizations.The median age of the patients was 61 years; 42.0% were female, and 39.0% were black. The telemonitoring group and the usual-care group did not differ significantly with respect to the primary end point, which occurred in 52.3% and 51.5% of patients, respectively (difference, 0.8 percentage points; 95% confidence interval [CI], -4.0 to 5.6; P=0.75 by the chi-square test). Readmission for any reason occurred in 49.3% of patients in the telemonitoring group and 47.4% of patients in the usual-care group (difference, 1.9 percentage points; 95% CI, -3.0 to 6.7; P=0.45 by the chi-square test). Death occurred in 11.1% of the telemonitoring group and 11.4% of the usual care group (difference, -0.2 percentage points; 95% CI, -3.3 to 2.8; P=0.88 by the chi-square test). There were no significant differences between the two groups with respect to the secondary end points or the time to the primary end point or its components. No adverse events were reported.Among patients recently hospitalized for heart failure, telemonitoring did not improve outcomes. The results indicate the importance of a thorough, independent evaluation of disease-management strategies before their adoption. (Funded by the National Heart, Lung, and Blood Institute; ClinicalTrials.gov number, NCT00303212.).

Background— Patient outcomes provide a critical perspective on quality of care. The Centers for Medicare and Medicaid Services (CMS) is publicly reporting hospital 30-day risk-standardized mortality rates (RSMRs) and risk-standardized readmission rates (RSRRs) for patients hospitalized with acute myocardial infarction (AMI) and heart failure (HF). We provide a national perspective on hospital performance for the 2010 release of these measures. Methods and Results— The hospital RSMRs and RSRRs are calculated from Medicare claims data for fee-for-service Medicare beneficiaries, 65 years or older, hospitalized with AMI or HF between July 1, 2006, and June 30, 2009. The rates are calculated using hierarchical logistic modeling to account for patient clustering, and are risk-adjusted for age, sex, and patient comorbidities. The median RSMR for AMI was 16.0% and for HF was 10.8%. Both measures had a wide range of hospital performance with an absolute 5.2% difference between hospitals in the 5th versus 95th percentile for AMI and 5.0% for HF. The median RSRR for AMI was 19.9% and for HF was 24.5% (3.9% range for 5th to 95th percentile for AMI, 6.7% for HF). Distinct regional patterns were evident for both measures and both conditions. Conclusions— High RSRRs persist for AMI and HF and clinically meaningful variation exists for RSMRs and RSRRs for both conditions. Our results suggest continued opportunities for improvement in patient outcomes for HF and AMI.

BACKGROUND: Pneumonia is a leading cause of hospitalization and death in the elderly, and remains the subject of both local and national quality improvement efforts. OBJECTIVE: To describe patterns of hospital and regional performance in the outcomes of elderly patients with pneumonia. DESIGN: Cross-sectional study using hospital and outpatient Medicare claims between 2006 and 2009. SETTING: A total of 4,813 nonfederal acute care hospitals in the United States and its organized territories. PATIENTS: Hospitalized fee-for-service Medicare beneficiaries age 65 years and older who received a principal diagnosis of pneumonia. INTERVENTION: None. MEASUREMENTS: Hospital and regional level risk-standardized 30-day mortality and readmission rates. RESULTS: Of the 1,118,583 patients included in the mortality analysis 129,444 (11.6%) died within 30 days of hospital admission. The median (Q1, Q3) hospital 30-day risk-standardized mortality rate for patients with pneumonia was 11.1% (10.0%, 12.3%), and despite controlling for differences in case mix, ranged from 6.7% to 20.9%. Among the 1,161,817 patients included in the readmission analysis 212,638 (18.3%) were readmitted within 30 days of hospital discharge. The median (Q1, Q3) 30-day risk-standardized readmission rate was 18.2% (17.2%, 19.2%) and ranged from 13.6% to 26.7%. Risk-standardized mortality rates varied across hospital referral regions from a high of 14.9% to a low of 8.7%. Risk-standardized readmission rates varied across hospital referral regions from a high of 22.2% to a low of 15%. CONCLUSIONS: Risk-standardized 30-day mortality and, to a lesser extent, readmission rates for patients with pneumonia vary substantially across hospitals and regions and may present opportunities for quality improvement, especially at low performing institutions and areas. Journal of Hospital Medicine 2010. © 2010 Society of Hospital Medicine.

BACKGROUND: Readmission following hospital discharge has become an important target of quality improvement. OBJECTIVE: To describe the development, validation, and results of a risk-standardized measure of hospital readmission rates among elderly patients with pneumonia employed in federal quality measurement and efficiency initiatives. DESIGN: A retrospective cohort study using hospital and outpatient Medicare claims from 2005 and 2006. SETTING: A total of 4675 hospitals in the United States. PATIENTS: Medicare beneficiaries aged >65 years with a principal discharge diagnosis of pneumonia. INTERVENTION: None. MEASUREMENTS: Hospital-specific, risk-standardized 30-day readmission rates calculated as the ratio of predicted-to-expected readmissions, multiplied by the national unadjusted rate. Comparison of the areas under the receiver operating curve (ROC) and measurement of correlation coefficient in development and validation samples. RESULTS: The development sample consisted of 226,545 hospitalizations at 4675 hospitals, with an overall unadjusted 30-day readmission rate of 17.4%. The median risk-standardized hospital readmission rate was 17.3%, and the odds of readmission for a hospital one standard deviation above average was 1.4 times that of a hospital one standard deviation below average. Performance of the medical record and administrative models was similar (areas under the ROC curve 0.59 and 0.63, respectively) and the correlation coefficient of estimated state-specific standardized readmission rates from the administrative and medical record models was 0.96. CONCLUSIONS: Rehospitalization within 30 days of treatment for pneumonia is common, and rates vary across hospitals. A risk-standardized measure of hospital readmission rates derived from administrative claims has similar performance characteristics to one based on medical record review. Journal of Hospital Medicine 2010. © 2010 Society of Hospital Medicine