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Objectives The extent to which care quality influenced outcomes for patients hospitalised with COVID-19 is unknown. Our objective was to determine if prepandemic hospital quality is associated with mortality among Medicare patients hospitalised with COVID-19.Design This is a retrospective observational study. We calculated hospital-level risk-standardised in-hospital and 30-day mortality rates (risk-standardised mortality rates, RSMRs) for patients hospitalised with COVID-19, and correlation coefficients between RSMRs and pre-COVID-19 hospital quality, overall and stratified by hospital characteristics.Setting Short-term acute care hospitals and critical access hospitals in the USA.Participants Hospitalised Medicare beneficiaries (Fee-For-Service and Medicare Advantage) age 65 and older hospitalised with COVID-19, discharged between 1 April 2020 and 30 September 2021.Intervention/exposure Pre-COVID-19 hospital quality.Outcomes Risk-standardised COVID-19 in-hospital and 30-day mortality rates (RSMRs).Results In-hospital (n=4256) RSMRs for Medicare patients hospitalised with COVID-19 (April 2020–September 2021) ranged from 4.5% to 59.9% (median 18.2%; IQR 14.7%–23.7%); 30-day RSMRs ranged from 12.9% to 56.2% (IQR 24.6%–30.6%). COVID-19 RSMRs were negatively correlated with star rating summary scores (in-hospital correlation coefficient −0.41, p

Abstract Diagnosis codes are used to study SARS-CoV2 infections and COVID-19 hospitalizations in administrative and electronic health record (EHR) data. Using EHR data (April 2020–March 2021) at the Yale-New Haven Health System and the three hospital systems of the Mayo Clinic, computable phenotype definitions based on ICD-10 diagnosis of COVID-19 (U07.1) were evaluated against positive SARS-CoV-2 PCR or antigen tests. We included 69,423 patients at Yale and 75,748 at Mayo Clinic with either a diagnosis code or a positive SARS-CoV-2 test. The precision and recall of a COVID-19 diagnosis for a positive test were 68.8% and 83.3%, respectively, at Yale, with higher precision (95%) and lower recall (63.5%) at Mayo Clinic, varying between 59.2% in Rochester to 97.3% in Arizona. For hospitalizations with a principal COVID-19 diagnosis, 94.8% at Yale and 80.5% at Mayo Clinic had an associated positive laboratory test, with secondary diagnosis of COVID-19 identifying additional patients. These patients had a twofold higher inhospital mortality than based on principal diagnosis. Standardization of coding practices is needed before the use of diagnosis codes in clinical research and epidemiological surveillance of COVID-19.

Background: Cardioprotective antihyperglycemic agents, SGLT2 inhibitors (SGLT2i) and GLP-1 receptor agonists (GLP1RA), improve outcomes of patients with type 2 diabetes, but adoption has been limited. Differences across individuals have been noted but area-level variation is unknown. Objectives: Given healthcare access and sociodemographic differences, we evaluated whether SGLT2i and GLP-1RA utilization varies across US counties. Methods: We linked 2019 Medicare Part D national prescription data with county-level demographic measures from the Agency for Health Quality and Research. We compared the number of beneficiaries receiving prescriptions for any cardioprotective antihyperglycemic to the number receiving metformin prescriptions across US counties. In multivariable linear regression with SGLT2i-to-metformin and GLP1RA-to-metformin prescriptions as outcomes, we evaluated county factors associated with use of cardioprotective agents while adjusting for sociodemographic measures, region, and cardiometabolic risk factor prevalence. Results: In 3066 US counties, there were a median 2,416 (IQR, 1681–3190) metformin-receiving beneficiaries per 100,000 population. A median 6.2% of beneficiaries receiving metformin received SGLT2i therapy, varying across counties (IQR, 3.4%–9.2%). A median 9.4% (IQR, 5.0%–13.0%) of beneficiaries receiving metformin received GLP-1RA. In adjusted analyses, higher percentage of Black population was associated with lower use at the county level of people on SGLT2i or GLP-1RA relative to metformin (a SD higher proportion of Black individuals with 0.4% [95% CI, -0.6% to -0.1%] and 0.5% [-0.8% to -0.2%] lower SGLT2i and GLP-1RA prescribing relative to metformin, respectively; P

Abstract Background The electronic health record (EHR) holds the prospect of providing more complete and timely access to clinical information for biomedical research, quality assessments, and quality improvement compared to other data sources, such as administrative claims. In this study, we sought to assess the completeness and timeliness of structured diagnoses in the EHR compared to computed diagnoses for hypertension (HTN), hyperlipidemia (HLD), and diabetes mellitus (DM). Methods We determined the amount of time for a structured diagnosis to be recorded in the EHR from when an equivalent diagnosis could be computed from other structured data elements, such as vital signs and laboratory results. We used EHR data for encounters from January 1, 2012 through February 10, 2019 from an academic health system. Diagnoses for HTN, HLD, and DM were computed for patients with at least two observations above threshold separated by at least 30 days, where the thresholds were outpatient blood pressure of ≥ 140/90 mmHg, any low-density lipoprotein ≥ 130 mg/dl, or any hemoglobin A1c ≥ 6.5%, respectively. The primary measure was the length of time between the computed diagnosis and the time at which a structured diagnosis could be identified within the EHR history or problem list. Results We found that 39.8% of those with HTN, 21.6% with HLD, and 5.2% with DM did not receive a corresponding structured diagnosis recorded in the EHR. For those who received a structured diagnosis, a mean of 389, 198, and 166 days elapsed before the patient had the corresponding diagnosis of HTN, HLD, or DM, respectively, recorded in the EHR. Conclusions We found a marked temporal delay between when a diagnosis can be computed or inferred and when an equivalent structured diagnosis is recorded within the EHR. These findings demonstrate the continued need for additional study of the EHR to avoid bias when using observational data and reinforce the need for computational approaches to identify clinical phenotypes.

Abstract Background To estimate, prior to finalization of claims, the national monthly numbers of admissions and rates of 30-day readmissions and post-discharge observation-stays for Medicare fee-for-service beneficiaries hospitalized with acute myocardial infarction (AMI), heart failure (HF), or pneumonia. Methods The centers for Medicare & Medicaid Services (CMS) Integrated Data Repository, including the Medicare beneficiary enrollment database, was accessed in June 2015, February 2017, and February 2018. We evaluated patterns of delay in Medicare claims accrual, and used incomplete, non-final claims data to develop and validate models for real-time estimation of admissions, readmissions, and observation stays. Results These real-time reporting models accurately estimate, within 2 months from admission, the monthly numbers of admissions, 30-day readmission and observation-stay rates for patients with AMI, HF, or pneumonia. Conclusions This work will allow CMS to track the impact of policy decisions in real time and enable hospitals to better monitor their performance nationally.

Background Despite its clinical significance, the risk of severe infection requiring hospitalization among outpatients with severe acute respiratory syndrome coronavirus 2 infection who receive angiotensin‐converting enzyme (ACE) inhibitors and angiotensin receptor blockers (ARBs) remains uncertain. Methods and Results In a propensity score–matched outpatient cohort (January–May 2020) of 2263 Medicare Advantage and commercially insured individuals with hypertension and a positive outpatient SARS‐CoV‐2, we determined the association of ACE inhibitors and ARBs with COVID‐19 hospitalization. In a concurrent inpatient cohort of 7933 hospitalized with COVID‐19, we tested their association with in‐hospital mortality. The robustness of the observations was assessed in a contemporary cohort (May–August). In the outpatient study, neither ACE inhibitors (hazard ratio [HR], 0.77; 0.53–1.13, P=0.18) nor ARBs (HR, 0.88; 0.61–1.26, P=0.48) were associated with hospitalization risk. ACE inhibitors were associated with lower hospitalization risk in the older Medicare group (HR, 0.61; 0.41–0.93, P=0.02), but not the younger commercially insured group (HR, 2.14; 0.82–5.60, P=0.12; P‐interaction 0.09). Neither ACE inhibitors nor ARBs were associated with lower hospitalization risk in either population in the validation cohort. In the primary inpatient study cohort, neither ACE inhibitors (HR, 0.97; 0.81–1.16; P=0.74) nor ARBs (HR, 1.15; 0.95–1.38, P=0.15) were associated with in‐hospital mortality. These observations were consistent in the validation cohort. Conclusions ACE inhibitors and ARBs were not associated with COVID‐19 hospitalization or mortality. Despite early evidence for a potential association between ACE inhibitors and severe COVID‐19 prevention in older individuals, the inconsistency of this observation in recent data argues against a role for prophylaxis.

Objectives To develop a model of in-hospital mortality using medical record front page (MRFP) data and assess its validity in case-mix standardisation by comparison with a model developed using the complete medical record data.Design A nationally representative retrospective study.Setting Representative hospitals in China, covering 161 hospitals in modelling cohort and 156 hospitals in validation cohort.Participants Representative patients admitted for acute myocardial infarction. 8370 patients in modelling cohort and 9704 patients in validation cohort.Primary outcome measures In-hospital mortality, which was defined explicitly as death that occurred during hospitalisation, and the hospital-level risk standardised mortality rate (RSMR).Results A total of 14 variables were included in the model predicting in-hospital mortality based on MRFP data, with the area under receiver operating characteristic curve of 0.78 among modelling cohort and 0.79 among validation cohort. The median of absolute difference between the hospital RSMR predicted by hierarchical generalised linear models established based on MRFP data and complete medical record data, which was built as ‘reference model’, was 0.08% (10th and 90th percentiles: −1.8% and 1.6%). In the regression model comparing the RSMR between two models, the slope and intercept of the regression equation is 0.90 and 0.007 in modelling cohort, while 0.85 and 0.010 in validation cohort, which indicated that the evaluation capability from two models were very similar.Conclusions The models based on MRFP data showed good discrimination and calibration capability, as well as similar risk prediction effect in comparison with the model based on complete medical record data, which proved that MRFP data could be suitable for risk adjustment in hospital performance measurement.

Abstract Background Since clinical management of heart failure relies on weights that are self-reported by the patient, errors in reporting will negatively impact the ability of health care professionals to offer timely and effective preventive care. Errors might often result from rounding, or more generally from individual preferences for numbers ending in certain digits, such as 0 or 5. We apply fraud detection methods to assess preferences for numbers ending in these digits in order to inform medical decision making. Methods The Telemonitoring to Improve Heart Failure Outcomes trial tested an approach to telemonitoring that used existing technology; intervention patients (n = 826) were asked to measure their weight daily using a digital scale and to relay measurements using their telephone keypads. First, we estimated the number of weights subject to end-digit preference by dividing the weights by five and comparing the resultant distribution with the uniform distribution. Then, we assessed the characteristics of patients reporting an excess number of weights ending in 0 or 5, adjusting for chance reporting of these values. Results Of the 114,867 weight readings reported during the trial, 18.6% were affected by end-digit preference, and the likelihood of these errors occurring increased with the number of days that had elapsed since trial enrolment (odds ratio per day: 1.002, p

ObjectivesTo describe trends in the availability of biomarker testing in Chinese hospitals and how practice complies with established standards for the diagnosis of acute myocardial infarction (AMI).BackgroundCardiac biomarker testing is standard in high-income countries, but little is known about the availability and use of cardiac biomarker testing in low- and middle-income countries (LMICs) such as China.MethodsBased on a nationally representative sample of Chinese hospitals in 2001, 2006 and 2011, we describe the temporal trends and regional differences in the hospital capability and rates of use of cardiac biomarker testing, as well as the variation in use across hospitals with testing capability, for patients labeled with the diagnosis of AMI.ResultsWe sampled 175 hospitals (162 participated in the study) and 18,631 AMI admissions. 14,370 patients were included in analysis of biomarker use. The proportion of hospitals with biomarker testing capability was 57.4% in 2001 (25.0% troponin and 32.4% creatine kinase MB fraction (CK-MB) only) and 96.3% (81.4% troponin and 14.9% CK-MB only) in 2011. The proportion of hospitals with troponin testing capability in 2011 was significantly higher in urban compared with rural hospitals (96.8% vs. 71.4%, p< 0.001). In 2011, only 55.9% of hospitals with troponin testing capability (71 out of 127 hospitals) used the assay for more than 80% of their patients with AMI. Among hospitals with either biomarker testing capability, there was marked variation in use in both rural (from 7.1% to 100.0% of patients) and urban hospitals (from 57.9% to 100.0% of patients). In 2011, 36.1% of the patients with AMI did not have troponin tested and 4.9% did not have either biomarker measured.ConclusionsThe recommended biomarker tests for AMI diagnosis are not universally available and the testing is not consistently applied when it is available in China.Trial registrationClinicalTrials.gov NCT01624883.

BACKGROUND: Procedure volumes are associated with outcomes for many cardiovascular procedures, leading to guidelines on minimum volume thresholds for certain procedures; however, the volume-outcome relationship with left atrial appendage occlusion is poorly understood. As such, we sought to determine the relationship between hospital and physician volume and WATCHMAN left atrial appendage occlusion procedural success overall and with the new generation WATCHMAN FLX device. METHODS: We performed an analysis of WATCHMAN procedures (January 2019 to October 2021) from the National Cardiovascular Data Registry LAAO Registry. Three-level hierarchical generalized linear models were used to assess the adjusted relationship between procedure volume and procedural success (device released with peridevice leak <5 mm, no in-hospital major adverse events). RESULTS: Among 87480 patients (76.2±8.0 years; 58.8% men; mean CHA2DS2-VASc score, 4.8±1.5) from 693 hospitals, the procedural success rate was 94.2%. With hospital volume Q4 (greatest volume) as the reference, the likelihood of procedural success was significantly less among Q1 (odds ratio [OR], 0.66 [CI, 0.57–0.77]) and Q2 (OR, 0.78 [CI, 0.69– 0.90]) but not Q3 (OR, 0.95 [CI, 0.84–1.07]). With physician volume Q4 (greatest volume) as the reference, the likelihood of procedural success was significantly less among Q1 (OR, 0.72 [CI, 0.63–0.82]), Q2 (OR, 0.79 [CI, 0.71–0.89]), and Q3 (OR, 0.88 [CI, 0.79–0.97]). Among WATCHMAN FLX procedures, there was attenuation of the volume-outcome relationships, with statistically significant but modest absolute differences of only ≈1% across volume quartiles. CONCLUSIONS: In this contemporary national analysis, greater hospital and physician WATCHMAN volumes were associated with increased procedure success. The WATCHMAN FLX transition was associated with increased procedural success and less heterogeneity in outcomes across volume quartiles. These findings indicate the importance of understanding the volume-outcome relationship for individual left atrial appendage occlusion devices. [ABSTRACT FROM AUTHOR]

A randomized large scale trial was conducted among 1653 patients with recent history of hospitalization for heart failure to undergo either telemonitoring or usual care to determine possible effect of telemonitoring for improvement of heart-failure outcomes. Telemonitoring which failed to show any outcome improvements among patients recently hospitalized for heart failure indicated the significance of a thorough, independent evaluation of disease-management strategies before their adoption.

The COVID-19 pandemic has disproportionately affected Hispanic or Latino, non-Hispanic Black (Black), non-Hispanic American Indian or Alaska Native (AI/AN), and non-Hispanic Native Hawaiian or Other Pacific Islander (NH/PI) populations in the United States. These populations have experienced higher rates of infection and mortality compared with the non-Hispanic White (White) population (1-5) and greater excess mortality (i.e., the percentage increase in the number of persons who have died relative to the expected number of deaths for a given place and time) (6). A limitation of existing research on excess mortality among racial/ethnic minority groups has been the lack of adjustment for age and population change over time. This study assessed excess mortality incidence rates (IRs) (e.g., the number of excess deaths per 100,000 person-years) in the United States during December 29, 2019-January 2, 2021, by race/ethnicity and age group using data from the National Vital Statistics System. Among all assessed racial/ethnic groups (non-Hispanic Asian [Asian], AI/AN, Black, Hispanic, NH/PI, and White populations), excess mortality IRs were higher among persons aged ≥65 years (426.4 to 1033.5 excess deaths per 100,000 person-years) than among those aged 25-64 years (30.2 to 221.1) and those aged <25 years (-2.9 to 14.1). Among persons aged <65 years, Black and AI/AN populations had the highest excess mortality IRs. Among adults aged ≥65 years, Black and Hispanic persons experienced the highest excess mortality IRs of >1,000 excess deaths per 100,000 person-years. These findings could help guide more tailored public health messaging and mitigation efforts to reduce disparities in mortality associated with the COVID-19 pandemic in the United States,* by identifying the racial/ethnic groups and age groups with the highest excess mortality rates. [ABSTRACT FROM AUTHOR]

Background: Coronary artery bypass graft (CABG) surgery is a focus of bundled and alternate payment models that capture outcomes up to 90 days postsurgery. While clinical registry risk models perform well, measures encompassing mortality beyond 30 days do not currently exist. We aimed to develop a risk-adjusted hospital-level 90-day all-cause mortality measure intended for assessing hospital performance in payment models of CABG surgery using administrative data.Methods: Building upon Centers for Medicare and Medicaid Services hospital-level 30-day all-cause CABG mortality measure specifications, we extended the mortality timeframe to 90 days after surgery and developed a new hierarchical logistic regression model to calculate hospital risk-standardized 90-day all-cause mortality rates for patients hospitalized for isolated CABG. The model was derived from Medicare claims data for a 3-year cohort between July 2014 to June 2017. The data set was randomly split into 50:50 development and validation samples. The model performance was evaluated with C statistics, overfitting indices, and calibration plot. The empirical validity of the measure result at the hospital level was evaluated against the Society of Thoracic Surgeons composite star rating.Results: Among 137 819 CABG procedures performed in 1183 hospitals, the unadjusted mortality rate within 30 and 90 days were 3.1% and 4.7%, respectively. The final model included 27 variables. Hospital-level 90-day risk-standardized mortality rates ranged between 2.04% and 11.26%, with a median of 4.67%. C statistics in the development and validation samples were 0.766 and 0.772, respectively. We identified a strong positive correlation between 30- and 90-day risk-standardized mortality rates, with a regression slope of 1.09. Risk-standardized mortality rates also showed a stepwise trend of lower 90-day mortality with higher Society of Thoracic Surgeons composite star ratings.Conclusions: We present a measure of hospital-level 90-day risk-standardized mortality rates following isolated CABG. This measure complements Centers for Medicare and Medicaid Services' existing 30-day CABG mortality measure by providing greater insight into the postacute recovery period. It offers a balancing measure to ensure efforts to reduce costs associated with CABG recovery and rehabilitation do not result in unintended consequences. [ABSTRACT FROM AUTHOR]

Background: Given the inclusion of orthopaedic quality measures in the Centers for Medicare & Medicaid Services national hospital payment programs, the present study sought to assess whether the public reporting of total hip arthroplasty (THA) and total knee arthroplasty (TKA) risk-standardized readmission rates (RSRRs) and complication rates (RSCRs) was temporally associated with a decrease in the rates of these outcomes among Medicare beneficiaries.Methods: Annual trends in national observed and hospital-level RSRRs and RSCRs were evaluated for patients who underwent hospital-based inpatient hip and/or knee replacement procedures from fiscal year 2010 to fiscal year 2016. Hospital-level rates were calculated with use of the same measures and methodology that were utilized in public reporting. Annual trends in the distribution of hospital-level outcomes were then examined with use of density plots.Results: Complication and readmission rates and variation declined steadily from fiscal year 2010 to fiscal year 2016. Reductions of 33% and 25% were noted in hospital-level RSCRs and RSRRs, respectively. The interquartile range decreased by 18% (relative reduction) for RSCRs and by 34% (relative reduction) for RSRRs. The frequency of risk variables in the complication and readmission models did not systematically change over time, suggesting no evidence of widespread bias or up-coding.Conclusions: This study showed that hospital-level complication and readmission rates following THA and TKA and the variation in hospital-level performance declined during a period coinciding with the start of public reporting and financial incentives associated with measurement. The consistently decreasing trend in rates of and variation in outcomes suggests steady improvements and greater consistency among hospitals in clinical outcomes for THA and TKA patients in the 2016 fiscal year compared with the 2010 fiscal year. The interactions between public reporting, payment, and hospital coding practices are complex and require further study.Level Of Evidence: Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence. [ABSTRACT FROM AUTHOR]

The learning health system is a conceptual model for continuous learning and knowledge generation rooted in the daily practice of medicine. While companies such as Google and Amazon use dynamic learning systems that learn iteratively through every customer interaction, this efficiency has not materialized on a comparable scale in health systems. An ideal learning health system would learn from every patient interaction to benefit the care for the next patient. Notable advances include the greater use of data generated in the course of clinical care, Common Data Models, and advanced analytics. However, many remaining barriers limit the most effective use of large and growing health care data assets. In this review, we explore the accomplishments, opportunities, and barriers to realizing the learning health system. [ABSTRACT FROM AUTHOR]

Objective To determine whether informed consent for surgical procedures performed in US hospitals meet a minimum standard of quality, we developed and tested a quality measure of informed consent documents. Design Retrospective observational study of informed consent documents. Setting 25 US hospitals, diverse in size and geographical region. Cohort Among Medicare fee-for- service patients undergoing elective procedures in participating hospitals, we assessed the informed consent documents associated with these procedures. We aimed to review 100 qualifying procedures per hospital; the selected sample was representative of the procedure types performed at each hospital. Primary outcome The outcome was hospital quality of informed consent documents, assessed by two independent raters using an eight-item instrument previously developed for this measure and scored on a scale of 0–20, with 20 representing the highest quality. The outcome was reported as the mean hospital document score and the proportion of documents meeting a quality threshold of 10. Reliability of the hospital score was determined based on subsets of randomly selected documents; face validity was assessed using stakeholder feedback. Results Among 2480 informed consent documents from 25 hospitals, mean hospital scores ranged from 0.6 (95% CI 0.3 to 0.9) to 10.8 (95% CI 10.0 to 11.6). Most hospitals had at least one document score at least 10 out of 20 points, but only two hospitals had >50% of their documents score above a 10-point threshold. The Spearman correlation of the measures score was 0.92. Stakeholders reported that the measure was important, though some felt it did not go far enough to assess informed consent quality. Conclusion All hospitals performed poorly on a measure of informed consent document quality, though there was some variation across hospitals. Measuring the quality of hospital’s informed consent documents can serve as a first step in driving attention to gaps in quality. [ABSTRACT FROM AUTHOR]

Objective To develop a nationally applicable tool for assessing the quality of informed consent documents for elective procedures. Design Mixed qualitative-quantitative approach. Setting Convened seven meetings with stakeholders to obtain input and feedback on the tool. Participants Team of physician investigators, measure development experts, and a working group of nine patients and patient advocates (caregivers, advocates for vulnerable populations and patient safety experts) from different regions of the country. Interventions With stakeholder input, we identified elements of high-quality informed consent documents, aggregated into three domains: content, presentation and timing. Based on this comprehensive taxonomy of key elements, we convened the working group to offer input on the development of an abstraction tool to assess the quality of informed consent documents in three phases: (1) selecting the highest-priority elements to be operationalised as items in the tool; (2) iteratively refining and testing the tool using a sample of qualifying informed consent documents from eight hospitals; and (3) developing a scoring approach for the tool. Finally, we tested the reliability of the tool in a subsample of 250 informed consent documents from 25 additional hospitals. Outcomes Abstraction tool to evaluate the quality of informed consent documents. Results We identified 53 elements of informed consent quality; of these, 15 were selected as highest priority for inclusion in the abstraction tool and 8 were feasible to measure. After seven cycles of iterative development and testing of survey items, and development and refinement of a training manual, two trained raters achieved high item-level agreement, ranging from 92% to 100%. Conclusions We identified key quality elements of an informed consent document and operationalised the highest-priority elements to define a minimum standard for informed consent documents. This tool is a starting point that can enable hospitals and other providers to evaluate and improve the quality of informed consent. [ABSTRACT FROM AUTHOR]

Rationale: Characterization of the dynamic nature of posthospital risk in chronic obstructive pulmonary disease (COPD) is needed to provide counseling and plan clinical services.Objectives: To analyze risk of readmission and death after discharge for COPD among Medicare beneficiaries aged 65 years and older and to determine the association between ventilator support and risk trajectory.Methods: We computed daily absolute risks of hospital readmission and death for 1 year after discharge for COPD, stratified by ventilator support. We determined the time required for risks to decline by 50% from maximum daily values after discharge and for daily risks to plateau. We compared risks with those found in the general elderly population.Measurements and Main Results: Among 2,340,637 hospitalizations, the readmission rate at 1 year was 64.2%, including 63.5%, 66.0%, and 64.1% among those receiving invasive, noninvasive, and no ventilation, respectively. Among 1,283,069 hospitalizations, mortality at 1 year was 26.2%, including 45.7%, 41.8%, and 24.4% among those same respective groups. Daily risk of readmission declined by 50% within 28, 39, and 43 days and plateaued at 46, 54, and 61 days among those receiving invasive, noninvasive, and no ventilation, respectively. Risk of death declined by 50% by 3, 4, and 17 days and plateaued by 21, 18, and 24 days in the same respective groups. Risks of hospitalization and death were significantly higher after discharge for COPD than among the general Medicare population.Conclusions: Discharge from the hospital is associated with prolonged risks of readmission and death that vary with need for ventilator support. Interventions limited to the first month after discharge may be insufficient to improve longitudinal outcomes. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Objective To compare trends in readmission rates among safety net and non-safety net hospitals under the US Hospital Readmission Reduction Program (HRRP). Design A retrospective time series analysis using Medicare administrative claims data from January 2008 to June 2015. Setting We examined 3254 US hospitals eligible for penalties under the HRRP, categorised as safety net or non-safety net hospitals based on the hospital's proportion of patients with low socioeconomic status. Participants Admissions for Medicare fee-for-service patients, age ≥65 years, discharged alive, who had a valid five-digit zip code and did not have a principal discharge diagnosis of cancer or psychiatric illness were included, for a total of 52 516 213 index admissions. Primary and secondary outcome measures Mean hospital-level, all-condition, 30-day risk-adjusted standardised unplanned readmission rate, measured quarterly, along with quarterly rate of change, and an interrupted time series examining: April-June 2010, after HRRP was passed, and October-December 2012, after HRRP penalties were implemented. Results 58.0% (SD 15.3) of safety net hospitals and 17.1% (SD 10.4) of non-safety net hospitals' patients were in the lowest quartile of socioeconomic status. The mean safety net hospital standardised readmission rate declined from 17.0% (SD 3.7) to 13.6% (SD 3.6), whereas the mean non-safety net hospital declined from 15.4% (SD 3.0) to 12.7% (SD 2.5). The absolute difference in rates between safety net and non-safety net hospitals declined from 1.6% (95% CI 1.3 to 1.9) to 0.9% (0.7 to 1.2). The quarterly decline in standardised readmission rates was 0.03 percentage points (95% CI 0.03 to 0.02, p<0.001) greater among safety net hospitals over the entire study period, and no differential change among safety net and non-safety net hospitals was found after either HRRP was passed or penalties enacted. Conclusions Since HRRP was passed and penalties implemented, readmission rates for safety net hospitals have decreased more rapidly than those for non-safety net hospitals. [ABSTRACT FROM AUTHOR]

Background: Since clinical management of heart failure relies on weights that are self-reported by the patient, errors in reporting will negatively impact the ability of health care professionals to offer timely and effective preventive care. Errors might often result from rounding, or more generally from individual preferences for numbers ending in certain digits, such as 0 or 5. We apply fraud detection methods to assess preferences for numbers ending in these digits in order to inform medical decision making.Methods: The Telemonitoring to Improve Heart Failure Outcomes trial tested an approach to telemonitoring that used existing technology; intervention patients (n = 826) were asked to measure their weight daily using a digital scale and to relay measurements using their telephone keypads. First, we estimated the number of weights subject to end-digit preference by dividing the weights by five and comparing the resultant distribution with the uniform distribution. Then, we assessed the characteristics of patients reporting an excess number of weights ending in 0 or 5, adjusting for chance reporting of these values.Results: Of the 114,867 weight readings reported during the trial, 18.6% were affected by end-digit preference, and the likelihood of these errors occurring increased with the number of days that had elapsed since trial enrolment (odds ratio per day: 1.002, p < 0.001). At least 105 patients demonstrated end-digit preference (14.9% of those who submitted data); although statistical significance was limited, a pattern emerged that, compared with other patients, they tended to be younger, male, high school graduates and on more medications. Patients with end-digit preference reported greater variability in weight, and they generated an average 2.9 alerts to the telemonitoring system over the six-month trial period (95% CI, 2.3 to 3.5), compared with 2.3 for other patients (95% CI, 2.2 to 2.5).Conclusions: As well as overshadowing clinically meaningful changes in weight, end-digit preference can lead to false alerts to telemonitoring systems, which may be associated with unnecessary treatment and alert fatigue. In this trial, end-digit preference was common and became increasingly so over time. By applying fraud detection methods to electronic medical data, it is possible to produce clinically significant information that can inform the design of initiatives to improve the accuracy of reporting.Trial Registration: ClinicalTrials.gov registration number NCT00303212 March 2006. [ABSTRACT FROM AUTHOR]

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 therapyeligible 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 (<60 years old) and gender (male) identified one-fifth of the cohort with an average mortality rate of <3.0%. Half of this low risk group--those with non-anterior AMI--had an average in-hospital death risk of 1.5%. Conclusions: Nearly, one in five patients with STEMI who are eligible for fibrinolytic therapy are at a low risk for in-hospital death. Three simple factors available at the time of presentation can identify these individuals and support decision-making about the use of fibrinolytic therapy. [ABSTRACT FROM AUTHOR]

BACKGROUND & AIMS: Colonoscopy is a common procedure, yet little is known about variations in colonoscopy quality among outpatient facilities. We developed an outcome measure to profile outpatient facilities by estimating risk-standardized rates of unplanned hospital visits within 7 days of colonoscopy. METHODS: We used a 20% sample of 2010 Medicare outpatient colonoscopy claims (331,880 colonoscopies performed at 8140 facilities) from patients ≥65 years or older, and developed a patient-level logistic regression model to estimate the risk of unplanned hospital visits (ie, emergency department visits, observation stays, and inpatient admissions) within 7 days of colonoscopy. We then used the patient-level risk model variables and hierarchical logistic regression to estimate facility rates of risk-standardized unplanned hospital visits using data from the Healthcare Cost and Utilization Project (325,811 colonoscopies at 992 facilities), from 4 states containing 100% of colonoscopies per facility. RESULTS: Outpatient colonoscopies were followed by 5412 unplanned hospital visits within 7 days (16.3/1000 colonoscopies). Hemorrhage, abdominal pain, and perforation were the most common causes of unplanned hospital visits. Fifteen variables were independently associated with unplanned hospital visits (c = 0.67). A history of fluid and electrolyte imbalance (odds ratio [OR] = 1.43; 95% confidence interval [CI]: 1.29-1.58), psychiatric disorders (OR = 1.34; 95% CI: 1.22-1.46), and, in the absence of prior arrhythmia, increasing age past 65 years (aged >85 years vs 65-69 years: OR = 1.87; 95% CI: 1.54-2.28) were most strongly associated. The facility risk-standardized unplanned hospital visits calculated using Healthcare Cost and Utilization Project data showed significant variation (median 12.3/ 1000; 5th-95th percentile, 10.5-14.6/1000). Median riskstandardized unplanned hospital visits were comparable between ambulatory surgery centers and hospital outpatient departments (each was 10.2/1000), and ranged from 16.1/1000 in the Northeast to 17.2/1000 in the Midwest. CONCLUSIONS: We calculated a risk-adjusted measure of outpatient colonoscopy quality, which shows important variation in quality among outpatient facilities. This measure can make transparent the extent to which patients require followup hospital care, help inform patient choices, and assist in quality-improvement efforts. [ABSTRACT FROM AUTHOR]

Background: China is experiencing increasing burden of acute myocardial infarction (AMI) in the face of limited medical resources. Hospital length of stay (LOS) is an important indicator of resource utilization. Methods: We used data from the Retrospective AMI Study within the China Patient-centered Evaluative Assessment of Cardiac Events, a nationally representative sample of patients hospitalized for AMI during 2001, 2006, and 2011. Hospital-level variation in risk-standardized LOS (RS-LOS) for AMI, accounting for differences in case mix and year, was examined with two-level generalized linear mixed models. A generalized estimating equation model was used to evaluate hospital characteristics associated with LOS. Absolute differences in RS-LOS and 95% confidence intervals were reported. Results: The weighted median and mean LOS were 13 and 14.6 days, respectively, in 2001 (n = 1,901), 11 and 12.6 days in 2006 (n = 3,553), and 11 and 11.9 days in 2011 (n = 7,252). There was substantial hospital level variation in RS-LOS across the 160 hospitals, ranging from 9.2 to 18.1 days. Hospitals in the Central regions had on average 1.6 days (p = 0.02) shorter RS-LOS than those in the Eastern regions. All other hospital characteristics relating to capacity for AMI treatment were not associated with LOS. Conclusions: Despite a marked decline over the past decade, the mean LOS for AMI in China in 2011 remained long compared with international standards. Inter-hospital variation is substantial even after adjusting for case mix. Further improvement of AMI care in Chinese hospitals is critical tofurther shorten LOS and reduce unnecessary hospital variation. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Little is known about the variation in complication rates among U.S. hospitals that perform elective total hip arthroplasty (THA) and total knee arthroplasty (TKA) procedures. The purpose of this study was to use National Quality Forum (NQF)-endorsed hospital-level risk-standardized complication rates to describe variations in, and disparities related to, hospital quality for elective primary THA and TKA procedures performed in U.S. hospitals. Methods: We conducted a cross-sectional analysis of national Medicare Fee-for-Service data. The study cohort included 878,098 Medicare fee-for-service beneficiaries, sixty-five years or older, who underwent elective THA or TKA from 2008 to 2010 at 3479 hospitals. Both medical and surgical complications were included in the composite measure. Hospitalspecific complication rates were calculated from Medicare claims with use of hierarchical logistic regression to account for patient clustering and were risk-adjusted for age, sex, and patient comorbidities. We determined whether hospitals with higher proportions of Medicaid patients and black patients had higher risk-standardized complication rates. Results: The crude rate of measured complications was 3.6%. The most common complications were pneumonia (0.86%), pulmonary embolism (0.75%), and periprosthetic joint infection or wound infection (0.67%). The median risk-standardized complication rate was 3.6% (range, 1.8% to 9.0%). Among hospitals with at least twenty-five THA and TKA patients in the study cohort, 103 (3.6%) were better and seventy-five (2.6%) were worse than expected. Hospitals with the highest proportion of Medicaid patients had slightly higher but similar risk-standardized complication rates (median, 3.6%; range, 2.0% to 7.1%) compared with hospitals in the lowest decile (3.4%; 1.7% to 6.2%). Findingswere similar for the analysis involving the proportion of black patients. Conclusions: There was more than a fourfold difference in risk-standardized complication rates across U.S. hospitals in which elective THA and TKA are performed. Although hospitals with higher proportions of Medicaid and black patients had rates similar to those of hospitals with lower proportions, there is a continued need to monitor for disparities in outcomes. These findings suggest there are opportunities for quality improvement among hospitals in which elective THA and TKA procedures are performed. [ABSTRACT FROM AUTHOR]

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). [ABSTRACT FROM AUTHOR]

Objectives To determine whether high performing hospitals with low 30 day risk standardized readmission rates have a lower proportion of readmissions from specific diagnoses and time periods after admission or instead have a similar distribution of readmission diagnoses and timing to lower performing institutions. Design Retrospective cohort study. Setting Medicare beneficiaries in the United States. Participants Patients aged 65 and older who were readmitted within 30 days after hospital admission for heart failure, acute myocardial infarction, or pneumonia in 2007-09. Main outcome measures Readmission diagnoses were classified with a modified version of the Centers for Medicare and Medicaid Services' condition categories, and readmission timing was classified by day (0-30) after hospital discharge. Hospital 30 day risk standardized readmission rates over the three years of study were calculated with public reporting methods of the US federal government, and hospitals were categorized with bootstrap analysis as having high, average, or low readmission performance for each index condition. High and low performing hospitals had ≥95% probability of having an interval estimate respectively less than or greater than the national 30 day readmission rate over the three year period of study. All remaining hospitals were considered average performers. Results For readmissions in the 30 days after the index admission, there were 320 003 after 1 291 211 admissions for heart failure (4041 hospitals), 102 536 after 517 827 admissions for acute myocardial infarction (2378 hospitals), and 208 438 after 1 135 932 admissions for pneumonia (4283 hospitals). The distribution of readmissions by diagnosis was similar across categories of hospital performance for all three conditions. High performing hospitals had fewer readmissions for all common diagnoses. Median time to readmission was similar by hospital performance for heart failure and acute myocardial infarction, though was 1.4 days longer among high versus low performing hospitals for pneumonia (P<0.001). Findings were unchanged after adjustment for other hospital characteristics potentially associated with readmission patterns. Conclusions High performing hospitals have proportionately fewer 30 day readmissions without differences in readmission diagnoses and timing, suggesting the possible benefit of strategies that lower risk of readmission globally rather than for specific diagnoses or time periods after hospital stay. [ABSTRACT FROM AUTHOR]

The article examines the association between hospital readmission and mortality rates for cardiac patients who were presented with clinical case of acute myocardial infarction, heart failure and pneumonia. It highlights the impact of quality of medical care provided by health care centers in resolving the risk associated with cardiac patients. The Centers for Medicare & Medicaid Services in the U.S. on the basis of a cohort analysis revealed that differences in performance of hospitals and diagnostic parameters implied by hospital were of immense use in determination of readmission rate and mortality rate of cardiac patients.

The article focuses on a study regarding the evaluation of readmission and timing among Medicare beneficiaries who are readmitted for heart failure (HF), acute myocardial infarction (MI) and pneumonia. It mentions that hospital readmissions report poor health care facility and states that the U.S. Centers for Medicare and Medicaid Services (CMS) has started public reporting of outcomes for improving the hospital care quality. The study reveals that 30-day readmissions were frequent throughout the month after rehospitalization for HF, MI and pneumonia. It also presents statistics which depict the readmission of patients.

The article offers information on the qualitative study that investigates the high cost paying patients for illness and care for the illumination of factors associated with high cost. It discusses two categories of patients and the interpersonal relationship between them which includes professional that focuses on the competence and effectiveness of the care giver and personal that focuses on the interpersonal relationship.

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. [ABSTRACT FROM AUTHOR]

The article focuses on a study which described the national trends in all-cause readmissions rates after heart failure (HF) hospitalization among Medicare beneficiaries. The study found that national mean and risk-standardized all-cause readmission rates (RSRR) distributions among Medicare beneficiaries discharged after hospitalization. It concluded that there was no improvement in hospital readmission care among Medicare beneficiaries.

The article discusses a study on the use of hierarchical regression models in assessing the rates of risk-standardized mortality and readmission of patients with heart failure in hospitals identified in the "America's Best Hospitals" ranking by the periodical "U.S. News & World Report" and in those non-ranked facilities. The study noted there was a reduced mean rate of in-hospital mortality in ranked hospitals, compared to non-ranked ones. It is said that ranked hospitals have not shown enough evidence of superiority for readmission.

The article focuses on a study which was designed to characterize the attitudes, experiences and training expectations of general surgery residents in the U.S. The study included a survey of all general surgery residents and was conducted after the American Board of Surgery In-Training Examination. Most of the study subjects claimed that they are satisfied with training and supportive peer relationships. However, there are residents who reported unmet needs and apprehensions related to training and careers. Study authors concluded that the attitude, experiences and training expectations of general surgery residents reflect high levels of satisfaction.

Background: Limits on resident work hours are intended to reduce fatigue-related errors, but may raise risk by increasing transfers of responsibility for patients. Objective: To examine changes in outcomes for internal medicine patients after the implementation of work-hour regulations. Design: Retrospective cohort study. Setting: Urban, academic medical center. Patients: 14 260 consecutive patients discharged from the teaching (housestaff) service and 6664 consecutive patients discharged from the nonteaching (hospitalist) service between 1 July 2002 and 30 June 2004. Measurements: Outcomes included intensive care unit utilization, length of stay, discharge disposition, 30-day readmission rate to the study institution, pharmacist interventions to prevent error, drug—drug interactions and in-hospital death. Results: The teaching service had net improvements in 3 outcomes. Relative to changes experienced by the nonteaching service, the rate of intensive care unit utilization decreased by 2.1% (95% CI, -3.3% to -0.7%; P = 0.002), the rate of discharge to home or rehabilitation facility versus elsewhere improved by 5.3% (CI, 2.6% to 7.6%; P < 0.001), and pharmacist interventions to prevent error were reduced by 1.92 interventions per 100 patient-days (CI, -2.74 to -1.03 interventions per 100 patient-days; P < 0.001). Teaching and nonteaching services had similar changes over time in length of stay, 30-day readmission rate, and adverse drug-drug interactions. In-hospital death was uncommon in both groups, and change over time was similar in the 2 groups. Limitations: The study was a retrospective, nonrandomized design that assessed a limited number of outcomes. Teaching and non-teaching cohorts may not have been affected similarly by secular trends in patient care. Conclusions: After the implementation of work-hour regulations, 3 of 7 outcomes improved for patients in the teaching service relative to those in the nonteaching service. The authors found no evidence of adverse unintended consequences after the institution of workhour regulations. [ABSTRACT FROM AUTHOR]

Background: The incidence of acute myocardial infarction (AMI) is growing rapidly in China, but there is limited information about the patient experience in the postacute 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. [ABSTRACT FROM AUTHOR]

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.). [ABSTRACT FROM AUTHOR]

The article discusses a study on the impact of an inpatient diabetes (DM) management team (IDMT) with glucometrics in an academic tertiary care center. The average length of stay (LOS) of patients referred to the team was 13.5 days. The aim of glucometrics is to assess the quality of hospital blood glucose (BG) control using each patient-day as the unit of analysis. It concludes that IDMT reduces hyperglycemia in hospitalized patients without increasing risk of hypoglycemia.