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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]

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]

A letter to the editor is presented in response to an article by David Chin and colleagues on the role of hospitals in readmission outcomes.

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]

The author discusses the accuracy and reliability of clinical outcomes in order to measure the performance of the health care organizations in the U.S. He states that the validity of the outcome measures captures the end result of a healthcare, which also has financial consequences. He further highlights that the measures are need to be credible, meaningful, and trustworthy in order to elevate practice and instill pubic confidence.

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.

Programs from the Centers for Medicare and Medicaid Services simultaneously promote strategies to lower hospital admissions and readmissions. However, there is concern that hospitals in communities that successfully reduce admissions may be penalized, as patients that are ultimately hospitalized may be sicker and at higher risk of readmission. We therefore examined the relationship between changes from 2010 to 2013 in admission rates and thirty-day readmission rates for elderly Medicare beneficiaries. We found that communities with the greatest decline in admission rates also had the greatest decline in thirty-day readmission rates, even though hospitalized patients did grow sicker as admission rates declined. The relationship between changing admission and readmission rates persisted in models that measured observed readmission rates, risk-standardized readmission rates, and the combined rate of readmission and death. Our findings suggest that communities can reduce admission rates and readmission rates in parallel, and that federal policy incentivizing reductions in both outcomes does not create contradictory incentives. [ABSTRACT FROM AUTHOR]

There is an active public debate about whether patients' socioeconomic status should be included in the readmission measures used to determine penalties in Medicare's Hospital Readmissions Reduction Program (HRRP). Using the current Centers for Medicare and Medicaid Services methodology, we compared risk-standardized readmission rates for hospitals caring for high and low proportions of patients of low socioeconomic status (as defined by their Medicaid status or neighborhood income). We then calculated risk-standardized readmission rates after additionally adjusting for patients' socioeconomic status. Our results demonstrate that hospitals caring for large proportions of patients of low socioeconomic status have readmission rates similar to those of other hospitals. Moreover, readmission rates calculated with and without adjustment for patients' socioeconomic status are highly correlated. Readmission rates of hospitals caring for patients of low socioeconomic status changed by approximately 0.1 percent with adjustment for patients' socioeconomic status, and only 3-4 percent fewer such hospitals reached the threshold for payment penalty in Medicare's HRRP. Overall, adjustment for socioeconomic status does not change hospital results in meaningful ways. [ABSTRACT FROM AUTHOR]

A letter to the editor is presented in response to the article "Accounting For Patients' Socioeconomic Status Does Not Change Hospital Readmission Rates," by Susannah Bernheim in the August 2016 issue.