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Background Vasospastic angina (VSA) and spontaneous coronary artery dissection (SCAD) are challenging causes of non-atherosclerotic acute coronary syndromes (ACS). Here, we report a unique ACS case with coexisting VSA and SCAD, highlighting specific strategies in diagnosis and management of these poorly studied conditions. Case summary A woman in her mid-60s with a history of suspected microvascular angina and no atherosclerosis in a previously performed coronary computed tomography angiography presented with worsening chest pain. Invasive coronary angiography revealed a focal SCAD with a resulting high-degree stenosis of the right coronary artery. Shortly after successful percutaneous coronary intervention with stent implantation and stopping her previous vasodilator therapy with nitroglycerine and molsidomine, the patient developed recurrent anterior non-ST-segment elevation myocardial infarction. Surprisingly, repeat coronary angiography revealed severe multifocal coronary artery spasms that were successfully treated with intracoronary nitroglycerine. Vasospastic angina was subsequently managed with diltiazem, molsidomine, and nitrates. Discussion Our report underscores the challenges in diagnosing and managing SCAD and VSA in ACS. The possible interplay between SCAD and VSA highlights the need for careful vasodilator therapy management, as seen in our patient, where therapy discontinuation led to severe multifocal VSA. This emphasizes the need for a comprehensive approach for optimal outcomes in complex ACS cases. [ABSTRACT FROM AUTHOR]

Key Points: Question: Do hospitals achieve equitable readmission rates (ie, fewer readmissions with narrow gaps in readmission rates between populations)? What characterizes hospitals with equitable readmissions? Findings: Of eligible hospitals, 17% had equitable readmissions by insurance, and 30% had equitable readmissions by race. Hospitals with and without equitable readmissions were characteristically different. Achieving equitable readmissions did not consistently correlate with quality, cost, or value. Many hospitals were not eligible for a disparities assessment due to insufficient numbers of dual-eligible and Black patients. Meaning: A minority of hospitals achieve equitable readmissions. Equity-focused outcome measures assess new dimensions of hospital performance distinct from traditional accountability measures. Importance: Equity is an essential domain of health care quality. The Centers for Medicare & Medicaid Services (CMS) developed 2 Disparity Methods that together assess equity in clinical outcomes. Objectives: To define a measure of equitable readmissions; identify hospitals with equitable readmissions by insurance (dual eligible vs non–dual eligible) or patient race (Black vs White); and compare hospitals with and without equitable readmissions by hospital characteristics and performance on accountability measures (quality, cost, and value). Design, Setting, and Participants: Cross-sectional study of US hospitals eligible for the CMS Hospital-Wide Readmission measure using Medicare data from July 2018 through June 2019. Main Outcomes and Measures: We created a definition of equitable readmissions using CMS Disparity Methods, which evaluate hospitals on 2 methods: outcomes for populations at risk for disparities (across-hospital method); and disparities in care within hospitals' patient populations (within-a-single-hospital method). Exposures: Hospital patient demographics; hospital characteristics; and 3 measures of hospital performance—quality, cost, and value (quality relative to cost). Results: Of 4638 hospitals, 74% served a sufficient number of dual-eligible patients, and 42% served a sufficient number of Black patients to apply CMS Disparity Methods by insurance and race. Of eligible hospitals, 17% had equitable readmission rates by insurance and 30% by race. Hospitals with equitable readmissions by insurance or race cared for a lower percentage of Black patients (insurance, 1.9% [IQR, 0.2%-8.8%] vs 3.3% [IQR, 0.7%-10.8%], P <.01; race, 7.6% [IQR, 3.2%-16.6%] vs 9.3% [IQR, 4.0%-19.0%], P =.01), and differed from nonequitable hospitals in multiple domains (teaching status, geography, size; P <.01). In examining equity by insurance, hospitals with low costs were more likely to have equitable readmissions (odds ratio, 1.57 [95% CI, 1.38-1.77), and there was no relationship between quality and value, and equity. In examining equity by race, hospitals with high overall quality were more likely to have equitable readmissions (odds ratio, 1.14 [95% CI, 1.03-1.26]), and there was no relationship between cost and value, and equity. Conclusion and Relevance: A minority of hospitals achieved equitable readmissions. Notably, hospitals with equitable readmissions were characteristically different from those without. For example, hospitals with equitable readmissions served fewer Black patients, reinforcing the role of structural racism in hospital-level inequities. Implementation of an equitable readmission measure must consider unequal distribution of at-risk patients among hospitals. This cross-sectional study of US hospitals compared hospital and patient characteristics to evaluate equitable rates of readmission by insurance (dual eligible [Medicare and Medicaid] vs non–dual eligible) and race (Black vs White). [ABSTRACT FROM AUTHOR]

Copyright of Praxis (16618157) is the property of Aerzteverlag medinfo AG and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The article offers information on acute pulmonary embolism (PE) in patients with SARS-CoV-2 infection is integral to the clinical management of these patients. Topics include the incidence of acute PE in patients undergoing has computed tomography pulmonary angiography (CTPA), and the emergency department (ED) across six hospitals in New York City during the height of the COVID-19 pandemic has compared to a nonpandemic period.

Background: The environment in which a patient lives influences their health outcomes. However, the degree to which community factors are associated with readmissions is uncertain. Objective: To estimate the influence of community factors on the Centers for Medicare & Medicaid Services risk-standardized hospital-wide readmission measure (HWR)–a quality performance measure in the U.S. Research design: We assessed 71 community variables in 6 domains related to health outcomes: clinical care; health behaviors; social and economic factors; the physical environment; demographics; and social capital. Subjects: Medicare fee-for-service patients eligible for the HWR measure between July 2014-June 2015 (n = 6,790,723). Patients were linked to community variables using their 5-digit zip code of residence. Methods: We used a random forest algorithm to rank variables for their importance in predicting HWR scores. Variables were entered into 6 domain-specific multivariable regression models in order of decreasing importance. Variables with P-values <0.10 were retained for a final model, after eliminating any that were collinear. Results: Among 71 community variables, 19 were retained in the 6 domain models and in the final model. Domains which explained the most to least variance in HWR were: physical environment (R2 = 15%); clinical care (R2 = 12%); demographics (R2 = 11%); social and economic environment (R2 = 7%); health behaviors (R2 = 9%); and social capital (R2 = 8%). In the final model, the 19 variables explained more than a quarter of the variance in readmission rates (R2 = 27%). Conclusions: Readmissions for a wide range of clinical conditions are influenced by factors relating to the communities in which patients reside. These findings can be used to target efforts to keep patients out of the hospital. [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]

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. [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]

Background: Concern has been raised about consequences of including patients with left ventricular assist device (LVAD) or heart transplantation in readmission and mortality measures. Methods: We calculated unadjusted and hospital-specific 30-day risk-standardized mortality (RSMR) and readmission (RSRR) rates for all Medicare fee-for-service beneficiaries with a primary diagnosis of AMI or HF discharged between July 2010 and June 2013. Hospitals were compared before and after excluding LVAD and heart transplantation patients. LVAD indication was measured. Results: In the AMI mortality (n = 506,543) and readmission (n = 526,309) cohorts, 1,166 and 1,016 patients received an LVAD while 3 and 2 had a heart transplantation, respectively. In the HF mortality (n = 1,015,335) and readmission (n = 1,254,124) cohorts, 789 and 931 received an LVAD, while 212 and 202 received a heart transplantation, respectively. Less than 2% of hospitals had either ≥6 patients who received an LVAD or, independently, had ≥1 heart transplantation. The AMI mortality and readmission cohorts used 1.8% and 2.8% of LVADs for semi-permanent/permanent indications, versus 73.8% and 78.0% for HF patients, respectively. The rest were for temporary/external indications. In the AMI cohort, RSMR for hospitals without LVAD patients versus hospitals with ≥6 LVADs was 14.8% and 14.3%, and RSRR was 17.8% and 18.3%, respectively; the HF cohort RSMR was 11.9% and 9.7% and RSRR was 22.6% and 23.4%, respectively. In the AMI cohort, RSMR for hospitals without versus with heart transplantation patients was 14.7% and 13.9% and RSRR was 17.8% and 17.7%, respectively; in the HF cohort, RSMR was 11.9% and 11.0%, and RSRR was 22.6% and 22.6%, respectively. Estimations changed ≤0.1% after excluding LVAD or heart transplantation patients. Conclusion: Hospitals caring for ≥6 patients with LVAD or ≥1 heart transplantation typically had a trend toward lower RSMRs but higher RSRRs. Rates were insignificantly changed when these patients were excluded. LVADs were primarily for acute-care in the AMI cohort and chronic support in the HF cohort. LVAD and heart transplantation patients are a distinct group with differential care requirements and outcomes, thus should be considered separately from the rest of the HF cohort. [ABSTRACT FROM AUTHOR]

Rationale: National efforts to compare hospital outcomes for patients with pneumonia may be biased by hospital differences in diagnosis and coding of aspiration pneumonia, a condition that has traditionally been excluded from pneumonia outcome measures.Objectives: To evaluate the rationale and impact of including patients with aspiration pneumonia in hospital mortality and readmission measures.Methods: Using Medicare fee-for-service claims for patients 65 years and older from July 2012 to June 2015, we characterized the proportion of hospitals' patients with pneumonia diagnosed with aspiration pneumonia, calculated hospital-specific risk-standardized rates of 30-day mortality and readmission for patients with pneumonia, analyzed the association between aspiration pneumonia coding frequency and these rates, and recalculated these rates including patients with aspiration pneumonia.Results: A total of 1,101,892 patients from 4,263 hospitals were included in the mortality measure analysis, including 192,814 with aspiration pneumonia. The median proportion of hospitals' patients with pneumonia diagnosed with aspiration pneumonia was 13.6% (10th-90th percentile, 4.2-26%). Hospitals with a higher proportion of patients with aspiration pneumonia had lower risk-standardized mortality rates in the traditional pneumonia measure (12.0% in the lowest coding and 11.0% in the highest coding quintiles) and were far more likely to be categorized as performing better than the national mortality rate; expanding the measure to include patients with aspiration pneumonia attenuated the association between aspiration pneumonia coding rate and hospital mortality. These findings were less pronounced for hospital readmission rates.Conclusions: Expanding the pneumonia cohorts to include patients with a principal diagnosis of aspiration pneumonia can overcome bias related to variation in hospital coding. [ABSTRACT FROM AUTHOR]

Background: Publicly reported hospital risk-standardized mortality rates (RSMRs) for acute myocardial infarction (AMI) are calculated for Medicare beneficiaries. Outcomes for older patients with AMI may not reflect general outcomes.Objective: To examine the relationship between hospital 30-day RSMRs for older patients (aged ≥65 years) and those for younger patients (aged 18 to 64 years) and all patients (aged ≥18 years) with AMI.Design: Retrospective cohort study.Setting: 986 hospitals in the ACTION (Acute Coronary Treatment and Intervention Outcomes Network) Registry-Get With the Guidelines.Participants: Adults hospitalized for AMI from 1 October 2010 to 30 September 2014.Measurements: Hospital 30-day RSMRs were calculated for older, younger, and all patients using an electronic health record measure of AMI mortality endorsed by the National Quality Forum. Hospitals were ranked by their 30-day RSMRs for these 3 age groups, and agreement in rankings was plotted. The correlation in hospital AMI achievement scores for each age group was also calculated using the Hospital Value-Based Purchasing (HVBP) Program method computed with the electronic health record measure.Results: 267 763 and 276 031 AMI hospitalizations among older and younger patients, respectively, were identified. Median hospital 30-day RSMRs were 9.4%, 3.0%, and 6.2% for older, younger, and all patients, respectively. Most top- and bottom-performing hospitals for older patients were neither top nor bottom performers for younger patients. In contrast, most top and bottom performers for older patients were also top and bottom performers for all patients. Similarly, HVBP achievement scores for older patients correlated weakly with those for younger patients (R = 0.30) and strongly with those for all patients (R = 0.92).Limitation: Minority of U.S. hospitals.Conclusion: Hospital mortality rankings for older patients with AMI inconsistently reflect rankings for younger patients. Incorporation of younger patients into assessment of hospital outcomes would permit further examination of the presence and effect of age-related quality differences.Primary Funding Source: American College of Cardiology. [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]

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

Importance: Little contemporary information is available about comparative performance between Veterans Affairs (VA) and non-VA hospitals, particularly related to mortality and readmission rates, 2 important outcomes of care.Objective: To assess and compare mortality and readmission rates among men in VA and non-VA hospitals.Design, Setting, and Participants: Cross-sectional analysis involving male Medicare fee-for-service beneficiaries aged 65 years or older hospitalized between 2010 and 2013 in VA and non-VA acute care hospitals for acute myocardial infarction (AMI), heart failure (HF), or pneumonia using the Medicare Standard Analytic Files and Enrollment Database together with VA administrative claims data. To avoid confounding geographic effects with health care system effects, we studied VA and non-VA hospitals within the same metropolitan statistical area (MSA).Exposures: Hospitalization in a VA or non-VA hospital in MSAs that contained at least 1 VA and non-VA hospital.Main Outcomes and Measures: For each condition, 30-day risk-standardized mortality rates and risk-standardized readmission rates for VA and non-VA hospitals. Mean aggregated within-MSA differences in mortality and readmission rates were also assessed.Results: We studied 104 VA and 1513 non-VA hospitals, with each condition-outcome analysis cohort for VA and non-VA hospitals containing at least 7900 patients (men; ≥65 years), in 92 MSAs. Mortality rates were lower in VA hospitals than non-VA hospitals for AMI (13.5% vs 13.7%, P = .02; -0.2 percentage-point difference) and HF (11.4% vs 11.9%, P = .008; -0.5 percentage-point difference), but higher for pneumonia (12.6% vs 12.2%, P = .045; 0.4 percentage-point difference). In contrast, readmission rates were higher in VA hospitals for all 3 conditions (AMI, 17.8% vs 17.2%, 0.6 percentage-point difference; HF, 24.7% vs 23.5%, 1.2 percentage-point difference; pneumonia, 19.4% vs 18.7%, 0.7 percentage-point difference, all P < .001). In within-MSA comparisons, VA hospitals had lower mortality rates for AMI (percentage-point difference, -0.22; 95% CI, -0.40 to -0.04) and HF (-0.63; 95% CI, -0.95 to -0.31), and mortality rates for pneumonia were not significantly different (-0.03; 95% CI, -0.46 to 0.40); however, VA hospitals had higher readmission rates for AMI (0.62; 95% CI, 0.48 to 0.75), HF (0.97; 95% CI, 0.59 to 1.34), or pneumonia (0.66; 95% CI, 0.41 to 0.91).Conclusions and Relevance: Among older men with AMI, HF, or pneumonia, hospitalization at VA hospitals, compared with hospitalization at non-VA hospitals, was associated with lower 30-day risk-standardized all-cause mortality rates for AMI and HF, and higher 30-day risk-standardized all-cause readmission rates for all 3 conditions, both nationally and within similar geographic areas, although absolute differences between these outcomes at VA and non-VA hospitals were small. [ABSTRACT FROM AUTHOR]

Copyright of Praxis (16618157) is the property of Aerzteverlag medinfo AG and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

: Isuru Ranasinghe and colleagues compare readmissions after hospitalization for heart failure, acute myocardial infarction, or pneumonia in adults aged 18 to 64 years with readmissions in those aged 65 and older. Please see later in the article for the Editors' Summary [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 discusses the results of a study which used a system developed by the U.S. Centers for Medicare & Medicaid Services to examine the national performance in door-in to door-out (DIDO) time. The study examined the association of the national median DIDO time with patient and hospital characteristics. The study concluded that rarely does the DIDO time met the recommended 30 minutes among patients requiring transfer to another facility for percutaneous coronary intervention.

Cardiac embolism is an important etiology of cerebrovascular ischaemic events (CIE). Echocardiography is routinely performed in patients with CIE despite guidelines recommending restriction of echocardiography to patients with clinically suspected cardioembolism. The aim of this study was to examine the therapeutic impact and prognostic role of echocardiographic findings in an unselected population suffering from CIE. Between November 2006 and November 2007, 319 patients with CIE underwent evaluation by transthoracic echocardiography (TTE) and in addition by transesophageal echocardiography (TEE) if deemed mandatory ( n = 49). The combined clinical end-point included death or recurrent CIE, occurring during a follow-up period of 3 and 12 months, respectively. After 3 months of follow-up, the combined end-point was noted in 30 (9%) and after 12 months in 43 (13%) patients. In multivariate analysis, atrial fibrillation (AF) (HR 2.12, 95% CI 1.38-3.25; P < 0.001) and coronary artery disease (CAD: HR 1.85, 95% CI 1.21-2.81; P = 0.004) were predictors of events occurring during short-term follow-up. After 1 year of follow-up, AF (HR 1.67, 95% CI 1.19-2.32; P = 0.003) and CAD (HR 1.5, 95% CI 1.09-2.06; P = 0.01) were associated with the combined end-point. Echocardiographic parameters assessed at study entry were not independently related to an adverse outcome. Whereas AF and CAD appear to increase the risk of events after suffering from CIE, echocardiographic findings were not independently associated with the combined end-point of recurrent CIE or death. [ABSTRACT FROM AUTHOR]

Background: Although a gradual increase in heart rate (HR) during dobutamine stress testing (DST) is desired, few data exists regarding whether this is similarly achieved in patients of widely varying body mass index (BMI). Whether difference in BMI contributes to variation in the hemodynamic and symptomatic response to dobutamine is also unknown. Methods: From prospectively acquired data of 2776 consecutive patients who underwent DST according to standard weight-based clinical protocol, we classified patients into 4 groups of BMI (kg/m 2): <25 (normal), 25 to 29.9 (overweight), 30 to 39.9 (obese), and ≥40 (severely obese) and compared the rate of increase of HR, mean blood pressure, and development of symptoms for the groups. Results: Age was 68 + 12 years, 52% were men, BMI was 29.8 + 6.6 kg/m2 (range 14.5-81.4), 198 (7%) had BMI ≥40, and target HR was achieved in 2433 (88%). The rate of increase in HR was similar for each group of BMI after adjustment for age, gender, baseline HR, negative chronotropic use, and atropine administration. The percentage of patients in each group who achieved target HR was similar and the percentage of target HR achieved at each stage of dobutamine was essentially equivalent. Blood pressure responses and development of symptoms were similar in the 4 groups of BMI. Independent predictors of failure to achieve target HR included age, diabetes mellitus, treatment with negative chronotropic medications, and baseline HR; BMI was not a predictor (odds ratio [OR] 0.98, P = .086). Conclusion: The current weight-based protocol of dobutamine dosing for DST results in similar increases in HR and blood pressure for patients of widely varying BMI. [ABSTRACT FROM PUBLISHER]

The article reviews the statistical models and patient predictors of readmission after heart failure(HF). It discusses that readmission after HF hospitalization is the altering focus for physicians and policy manufacturers and that the statistical models are demanded to evaluate patient risk and to equate hospital operation. It infers that the performed systematic review is used to report the models which are planned to compare hospital rates of readmission and to anticipate the patient's risk of readmission.

The article discusses about the performance of Veterans Affairs medical centers and the utilization of recommended ambulatory care services. According to the article, the Veterans Affairs medical centers are said to have presented better preventive and chronic disease care when compared to other health care organizations. A research was conducted to determine its accuracy using the nationally representative 2000 and 2004 surveys of the Behavior Risk Factor Surveillance System. It was concluded in the research that even though there is an arising emphasis on the quality of care and enhanced performance over US health care system, those who are receiving care from VAMC remains as those who are more inclined to obtain recommended ambulatory care.