Risk-standardized Readmission Research Articles

Incorporating Medicare Advantage Admissions Into the CMS Hospital-Wide Readmission Measure

Medicare Advantage (MA) enrollment is rapidly expanding, yet Centers for Medicare & Medicaid Services (CMS) claims-based hospital outcome measures, including readmission rates, have historically included only fee-for-service (FFS) beneficiaries. To assess the outcomes of incorporating MA data into the CMS claims-based FFS Hospital-Wide All-Cause Unplanned Readmission (HWR) measure. This cohort study assessed differences in 30-day unadjusted readmission rates and demographic and risk adjustment variables for MA vs FFS admissions. Inpatient FFS and MA administrative claims data were extracted from the Integrated Data Repository for all admissions for Medicare beneficiaries from July 1, 2018, to June 30, 2019. Measure reliability and risk-standardized readmission rates were calculated for the FFS and MA cohort vs the FFS-only cohort, overall and within specialty subgroups (cardiorespiratory, cardiovascular, medicine, surgery, neurology), then changes in hospital performance quintiles were assessed after adding MA admissions. Risk-standardized readmission rates. The cohort included 11 029 470 admissions (4 077 633 [37.0%] MA; 6 044 060 [54.8%] female; mean [SD] age, 77.7 [8.2] years). Unadjusted readmission rates were slightly higher for MA vs FFS admissions (15.7% vs 15.4%), yet comorbidities were generally lower among MA beneficiaries. Test-retest reliability for the FFS and MA cohort was higher than for the FFS-only cohort (0.78 vs 0.73) and signal-to-noise reliability increased in each specialty subgroup. Mean hospital risk-standardized readmission rates were similar for the FFS and MA cohort and FFS-only cohorts (15.5% vs 15.3%); this trend was consistent across the 5 specialty subgroups. After adding MA admissions to the FFS-only HWR measure, 1489 hospitals (33.1%) had their performance quintile ranking changed. As their proportion of MA admissions increased, more hospitals experienced a change in their performance quintile ranking (147 hospitals [16.3%] in the lowest quintile of percentage MA admissions; 408 [45.3%] in the highest). The combined cohort added 63 hospitals eligible for public reporting and more than 4 million admissions to the measure. In this cohort study, adding MA admissions to the HWR measure was associated with improved measure reliability and precision and enabled the inclusion of more hospitals and beneficiaries. After MA admissions were included, 1 in 3 hospitals had their performance quintile changed, with the greatest shifts among hospitals with a high percentage of MA admissions.

Systematic Review and Meta-Analysis of the Financial Impact of 30-Day Readmissions for Selected Medical Conditions: A Focus on Hospital Quality Performance.

The Patient Protection and Affordable Care Act (ACA) established the Hospital Quality Initiative in 2010 to enhance patient safety, reduce hospital readmissions, improve quality, and minimize healthcare costs. In response, this study aims to systematically review the literature and conduct a meta-analysis to estimate the average cost of procedure-specific 30-day risk-standardized unplanned readmissions for Acute Myocardial Infarction (AMI), Heart Failure (HF), Pneumonia, Coronary Artery Bypass Graft (CABG), and Total Hip Arthroplasty and/or Total Knee Arthroplasty (THA/TKA). Eligibility Criteria: This study included English language original research papers from the USA, encompassing various study designs. Exclusion criteria comprise studies lacking empirical evidence on hospital financial performance. A comprehensive search using relevant keywords was conducted across databases from January 1990 to December 2019 (updated in March 2021), covering peer-reviewed articles and gray literature. Risk of Bias: Bias in the included studies was assessed considering study design, adjustment for confounding factors, and potential effect modifiers. The review adhered to PRISMA guidelines. Employing Monte Carlo simulations, a meta-analysis was conducted with 100,000 simulated samples. Results indicated mean 30-day readmission costs: USD 16,037.08 (95% CI, USD 15,196.01-16,870.06) overall, USD 6852.97 (95% CI, USD 6684.44-7021.08) for AMI, USD 9817.42 (95% CI, USD 9575.82-10,060.43) for HF, and USD 21,346.50 (95% CI, USD 20,818.14-21,871.85) for THA/TKA. Despite the financial challenges that hospitals face due to the ACA and the Hospital Readmissions Reduction Program, this meta-analysis contributes valuable insights into the consistent cost trends associated with 30-day readmissions. This systematic review and meta-analysis provide comprehensive insights into the financial implications of 30-day readmissions for specific medical conditions, enhancing our understanding of the nexus between healthcare quality and financial performance.

Hospital admissions and outcomes for systolic and diastolic heart failure in Spain between 2016 and 2019: A population-based study

Background and purposeIn Spain there is a lack of population data that specifically compare hospitalization for systolic and diastolic heart failure (HF). We assessed clinical characteristics, in-hospital mortality and 30-day cardiovascular readmission rates differentiating by HF type. MethodsWe conducted a retrospective observational study of patients discharged with the principal diagnosis of HF from The National Health System’ acute hospital during 2016–2019, distinguishing between systolic and diastolic HF. The source of the data was the Minimum Basic Data Set. The risk-standardized in-hospital mortality ratio and risk-standardized 30-day cardiovascular readmission ratio were calculated using multilevel risk adjustment models. Results190,200 episodes of HF were selected. Of these, 163,727 (86.1%) were classified as diastolic HF and were characterized by older age, higher proportion of women, diabetes mellitus, dementia and renal failure than those with systolic HF. In the multilevel risk adjustment models, diastolic HF was a protective factor for both in-hospital mortality (Odds ratio-OR-: 0.79; 95% confidence interval [CI], 0.75−0.83; p < 0.001) and 30-day cardiovascular readmission versus systolic HF (OR: 0.93; 95%CI: 0.88−0.97; p = 0.002). ConclusionsIn Spain, between 2016 and 2019, hospitalization episodes for HF were mostly due to diastolic HF. According to the multilevel risk adjustment models, diastolic HF compared to systolic HF was a protective factor for both in-hospital mortality and 30-day cardiovascular readmission.

Including socioeconomic status reduces readmission penalties to safety-net hospitals

ObjectiveMedicare’s Hospital Readmissions Reduction Program (HRRP) financially penalizes “excessive” postoperative readmissions. Concerned with creating a double standard for institutions treating a high percentage of economically vulnerable patients, Medicare elected to exclude socioeconomic status (SES) from its risk-adjustment model. However, recent evidence suggests that safety-net hospitals (SNHs) caring for many low-SES patients are disproportionately penalized under the HRRP. We sought to simulate the impact of including SES-sensitive models on HRRP penalties for hospitals performing lower extremity revascularization (LER). MethodsThis is a retrospective, cross-sectional analysis of national data on Medicare patients undergoing open or endovascular LER procedures between 2007 and 2009. We used hierarchical logistic regression to generate hospital risk-standardized 30-day readmission rates under Medicare’s current model (adjusting for age, sex, comorbidities, and procedure type) compared with models that also adjust for SES. We estimated the likelihood of a penalty and penalty size for SNHs compared with non-SNHs under the current Medicare model and these SES-sensitive models. ResultsOur study population comprised 1708 hospitals performing 284,724 LER operations with an overall unadjusted readmission rate of 14.4% (standard deviation: 5.3%). Compared with the Centers for Medicare and Medicaid Services model, adjusting for SES would not change the proportion of SNHs penalized for excess readmissions (55.1% vs 53.4%, P = .101) but would reduce penalty amounts for 38% of SNHs compared with only 17% of non-SNHs, P < .001. ConclusionsFor LER, changing national Medicare policy to including SES in readmission risk-adjustment models would reduce penalty amounts to SNHs, especially for those that are also teaching institutions. Making further strides toward reducing the national disparity between SNHs and non-SHNs on readmissions, performance measures require strategies beyond simply altering the risk-adjustment model to include SES.

Hospitalizaciones y eventos por insuficiencia cardiaca sistólica y diastólica en España entre 2016 y 2019. Un estudio de base poblacional

Background and purposeIn Spain there is a lack of population data that specifically compare hospitalization for systolic and diastolic heart failure (HF). We assessed clinical characteristics, in-hospital mortality and 30-day cardiovascular readmission rates differentiating by HF type. MethodsWe conducted a retrospective observational study of patients discharged with the principal diagnosis of HF from The National Health System’ acute hospital during 2016-2019, distinguishing between systolic and diastolic HF. The source of the data was the Minimum Basic Data Set. The risk-standardized in-hospital mortality ratio and risk-standardized 30-day cardiovascular readmission ratio were calculated using multilevel risk adjustment models. ResultsThe 190,200 episodes of HF were selected. Of these, 163,727 (86.1%) were classified as diastolic HF and were characterized by older age, higher proportion of women, diabetes mellitus, dementia and renal failure than those with systolic HF. In the multilevel risk adjustment models, diastolic HF was a protective factor for both in-hospital mortality (odds ratio [OR]: 0.79; 95% confidence interval [CI]: 0.75-0.83; P<.001) and 30-day cardiovascular readmission versus systolic HF (OR: 0.93; 95% CI: 0.88-0.97; P=.002). ConclusionsIn Spain, between 2016 and 2019, hospitalization episodes for HF were mostly due to diastolic HF. According to the multilevel risk adjustment models, diastolic HF compared to systolic HF was a protective factor for both in-hospital mortality and 30-day cardiovascular readmission.

Hospital Performance Under Alternative Readmission Measures Incorporating Observation Stays.

To determine the extent to which counting observation stays changes hospital performance on 30-day readmission measures. This was a retrospective study of inpatient admissions and observation stays among fee-for-service Medicare enrollees in 2017. We generated 3 specifications of 30-day risk-standardized readmissions measures: the hospital-wide readmission (HWR) measure utilized by the Centers for Medicare and Medicaid Services, which captures inpatient readmissions within 30 days of inpatient discharge; an expanded HWR measure, which captures any unplanned hospitalization (inpatient admission or observation stay) within 30 days of inpatient discharge; an all-hospitalization readmission (AHR) measure, which captures any unplanned hospitalization following any hospital discharge (observation stays are included in both the numerator and denominator of the measure). Estimated excess readmissions for hospitals were compared across the 3 measures. High performers were defined as those with a lower-than-expected number of readmissions whereas low performers had higher-than-expected or excess readmissions. Multivariable logistic regression identified hospital characteristics associated with worse performance under the measures that included observation stays. Our sample had 2586 hospitals with 5,749,779 hospitalizations. Observation stays ranged from 0% to 41.7% of total hospitalizations. Mean (SD) readmission rates were 16.6% (5.4) for the HWR, 18.5% (5.7) for the expanded HWR, and 17.9% (5.7) in the all-hospitalization readmission measure. Approximately 1 in 7 hospitals (14.9%) would switch from being classified as a high performer to a low performer or vice-versa if observation stays were fully included in the calculation of readmission rates. Safety-net hospitals and those with a higher propensity to use observation would perform significantly worse. Fully incorporating observation stays in readmission measures would substantially change performance in value-based programs for safety-net hospitals and hospitals with high rates of observation stays.

Association of short-term hospital-level outcome metrics with 1-year mortality and recurrence for US Medicare beneficiaries with ischemic stroke.

Whether stroke patients treated at hospitals with better short-term outcome metrics have better long-term outcomes is unknown. We investigated whether treatment at US hospitals with better 30-day hospital-level stroke outcome metrics was associated with better 1-year outcomes, including reduced mortality and recurrent stroke, for patients after ischemic stroke. This cohort study included Medicare fee-for-service beneficiaries aged ≥65 years discharged alive from US hospitals with a principal diagnosis of ischemic stroke from 07/01/2015 to 12/31/2018. We categorized patients by the treating hospital's performance on the CMS hospital-specific 30-day risk-standardized all-cause mortality and readmission measures for ischemic stroke from 07/01/2012 to 06/30/2015: Low-Low (both CMS mortality and readmission rates for the hospital were <25th percentile of national rates), High-High (both >75th percentile), and Intermediate (all other hospitals). We balanced characteristics between hospital performance categories using stabilized inverse probability weights (IPW) based on patient demographic and clinical factors. We fit Cox models assessing patient risks of 1-year all-cause mortality and ischemic stroke recurrence across hospital performance categories, weighted by the IPW and accounting for competing risks. There were 595,929 stroke patients (mean age 78.9±8.8 years, 54.4% women) discharged from 2,563 hospitals (134 Low-Low, 2288 Intermediate, 141 High-High). For Low-Low, Intermediate, and High-High hospitals, respectively, 1-year mortality rates were 23.8% (95% confidence interval [CI] 23.3%-24.3%), 25.2% (25.1%-25.3%), and 26.5% (26.1%-26.9%), and recurrence rates were 8.0% (7.6%-8.3%), 7.9% (7.8%-8.0%), and 8.0% (7.7%-8.3%). Compared with patients treated at High-High hospitals, those treated at Low-Low and Intermediate hospitals, respectively, had 15% (hazard ratio 0.85; 95% CI 0.82-0.87) and 9% (0.91; 0.89-0.93) lower risks of 1-year mortality but no difference in recurrence. Ischemic stroke patients treated at hospitals with better CMS short-term outcome metrics had lower risks of post-discharge 1-year mortality, but similar recurrent stroke rates, compared with patients treated at other hospitals.

Primary Percutaneous Coronary Intervention in Patients With Spontaneous Coronary Artery Dissection vs Coronary Artery Disease

BackgroundSpontaneous coronary artery dissection (SCAD) is a rare cause of acute myocardial infarction. Revascularization in SCAD remains very challenging and therefore is not recommended as the initial management strategy in stable SCAD without high-risk features. ObjectivesThe aim of this study was to compare in-hospital mortality and 30-day readmission rates between patients with SCAD with ST-segment elevation myocardial infarction (STEMI) treated with primary percutaneous coronary intervention (PPCI) and patients with STEMI without SCAD undergoing PPCI. MethodsThis study was conducted using the administrative minimum dataset of the Spanish National Health System (2016-2020). Risk-standardized in-hospital mortality ratios and readmission ratios were calculated, and results were adjusted using propensity score (PS) analyses. ResultsA total of 65,957 episodes of PPCI were identified after exclusions. The crude in-hospital mortality rate was 4.8%. Of these, 315 (0.5%) were SCAD PPCI and 65,642 were non-SCAD PPCI. SCAD PPCI patients were younger and more frequently women than non-SCAD PPCI patients. Crude mortality (5.7% vs 4.8%), risk-standardized in-hospital mortality ratio (5.3% vs 5.3%), and PS-adjusted (315 pairs) mortality (5.7% vs 5.7%) were similar in SCAD PPCI and non-SCAD PPCI patients. In addition, crude (3% vs 3.3%) and PS-adjusted (297 pairs) 30-day readmission rates (3% vs 4%) were also similar in both groups. ConclusionsPPCI, when indicated in patients with STEMI and SCAD, has similar in-hospital mortality and 30-day readmission rates compared with PPCI for atherothrombotic STEMI. These findings support the value of PPCI in selected patients with SCAD.

Relationship Between In-Hospital Adverse Events and Hospital Performance on 30-Day All-cause Mortality and Readmission for Patients With Heart Failure.

Hospitals with high mortality and readmission rates for patients with heart failure (HF) might also perform poorly in other quality concepts. We sought to evaluate the association between hospital performance on mortality and readmission with hospital performance rates of safety adverse events. This cross-sectional study linked the 2009 to 2019 patient-level adverse events data from the Medicare Patient Safety Monitoring System, a randomly selected medical records-abstracted patient safety database, to the 2005 to 2016 hospital-level HF-specific 30-day all-cause mortality and readmissions data from the United States Centers for Medicare & Medicaid Services. Hospitals were classified to one of 3 performance categories based on their risk-standardized 30-day all-cause mortality and readmission rates: better (both in <25th percentile), worse (both >75th percentile), and average (otherwise). Our main outcome was the occurrence (yes/no) of one or more adverse events during hospitalization. A mixed-effect model was fit to assess the relationship between a patient's risk of having adverse events and hospital performance categories, adjusted for patient and hospital characteristics. The study included 39 597 patients with HF from 3108 hospitals, of which 252 hospitals (8.1%) and 215 (6.9%) were in the better and worse categories, respectively. The rate of patients with one or more adverse events during a hospitalization was 12.5% (95% CI, 12.1-12.8). Compared with patients admitted to better hospitals, patients admitted to worse hospitals had a higher risk of one or more hospital-acquired adverse events (adjusted risk ratio, 1.24 [95% CI, 1.06-1.44]). Patients admitted with HF to hospitals with high 30-day all-cause mortality and readmission rates had a higher risk of in-hospital adverse events. There may be common quality issues among these 3 measure concepts in these hospitals that produce poor performance for patients with HF.

Achieving Equity in Hospital Performance Assessments Using Composite Race-Specific Measures of Risk-Standardized Readmission and Mortality Rates for Heart Failure.

The contemporary measures of hospital performance for heart failure hospitalization and 30-day risk-standardized readmission rate (RSRR) and risk-standardized mortality rate (RSMR) are estimated using the same risk adjustment model and overall event rate for all patients. Thus, these measures are mainly driven by the care quality and outcomes for the majority racial and ethnic group, and may not adequately represent the hospital performance for patients of Black and other races. Fee-for-service Medicare beneficiaries from January 2014 to December 2019 hospitalized with heart failure were identified. Hospital-level 30-day RSRR and RSMR were estimated using the traditional race-agnostic models and the race-specific approach. The composite race-specific performance metric was calculated as the average of the RSRR/RMSR measures derived separately for each race and ethnicity group. Correlation and concordance in hospital performance for all patients and patients of Black and other races were assessed using the composite race-specific and race-agnostic metrics. The study included 1 903 232 patients (75.7% White [n=1 439 958]; 14.5% Black [n=276 684]; and 9.8% other races [n=186 590]) with heart failure from 1860 hospitals. There was a modest correlation between hospital-level 30-day performance metrics for patients of White versus Black race (Pearson correlation coefficient: RSRR=0.42; RSMR=0.26). Compared with the race-agnostic RSRR and RSMR, composite race-specific metrics for all patients demonstrated stronger correlation with RSRR (correlation coefficient: 0.60 versus 0.74) and RSMR (correlation coefficient: 0.44 versus 0.51) for Black patients. Concordance in hospital performance for all patients and patients of Black race was also higher with race-specific (versus race-agnostic) metrics (RSRR=64% versus 53% concordantly high-performing; 61% versus 51% concordantly low-performing). Race-specific RSRR and RSMR metrics (versus race-agnostic) led to reclassification in performance ranking of 35.8% and 39.2% of hospitals, respectively, with better 30-day and 1-year outcomes for patients of all race groups at hospitals reclassified as high-performing. Among patients hospitalized with heart failure, race-specific 30-day RSMR and RSRR are more equitable in representing hospital performance for patients of Black and other races.

Associations Between Long-Term Air Pollutant Exposure and 30-Day All-Cause Hospital Readmissions in US Patients With Stroke.

Long-term exposure to air pollutants is associated with increased stroke incidence, morbidity, and mortality; however, research on the association of pollutant exposure with poststroke hospital readmissions is lacking. We assessed associations between average annual carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), particulate matter 2.5, and sulfur dioxide (SO2) exposure and 30-day all-cause hospital readmission in US fee-for-service Medicare beneficiaries age ≥65 years hospitalized for ischemic stroke in 2014 to 2015. We fit Cox models to assess 30-day readmissions as a function of these pollutants, adjusted for patient and hospital characteristics and ambient temperature. Analyses were then stratified by treating hospital performance on the Centers for Medicare and Medicaid Services risk-standardized 30-day poststroke all-cause readmission measure to determine if the results were independent of performance: low (Centers for Medicare and Medicaid Services rate for hospital <25th percentile of national rate), high (>75th percentile), and intermediate (all others). Of 448 148 patients with stroke, 12.5% were readmitted within 30 days. Except for tropospheric NO2 (no national standard), average 2-year CO, O3, particulate matter 2.5, and SO2 values were below national limits. Each one SD increase in average annual CO, NO2, particulate matter 2.5, and SO2 exposure was associated with an adjusted 1.1% (95% CI, 0.4-1.9%), 3.6% (95% CI, 2.9%-4.4%), 1.2% (95% CI, 0.2%-2.3%), and 2.0% (95% CI, 1.1%-3.0%) increased risk of 30-day readmission, respectively, and O3 with a 0.7% (95% CI, 0.0%-1.5%) decrease. Associations between long-term air pollutant exposure and increased readmissions persisted across hospital performance categories. Long-term air pollutant exposure below national limits was associated with increased 30-day readmissions after stroke, regardless of hospital performance category. Whether air quality improvements lead to reductions in poststroke readmissions requires further research.

Abstract 157: Association Of Hospital Performance With 1-Year Mortality And Recurrence After Ischemic Stroke Among US Medicare Beneficiaries

Background: Whether stroke patients treated at hospitals with better short-term quality performance metrics have better long-term outcomes is unknown. We determined if ischemic stroke patients treated at US hospitals with better past performance on the Centers for Medicare &amp; Medicaid Services (CMS) 30-day mortality and readmission outcome measures for stroke had better 1-year outcomes compared to those treated at other hospitals. Methods: We included all Medicare fee-for-service beneficiaries aged ≥65 years discharged alive from US hospitals with a principal diagnosis of ischemic stroke from 07/01/2015 to 12/31/2018. We categorized patients by the treating hospital’s performance on the CMS hospital-specific 30-day risk-standardized all-cause mortality and readmission rate measures for stroke from 07/01/2012 to 06/30/2015: Low-Low (both CMS mortality and readmission rates for the hospital were &lt;25 th percentile of national rates), High-High (both &gt;75 th percentile), and Intermediate (all others). We balanced characteristics between hospital performance categories using stabilized inverse probability weights (IPW) based on patient demographic and clinical factors. We fit Cox models to assess patient risks of 1-year mortality and recurrent stroke across hospital performance categories, weighted by the IPW and accounting for competing risks. Results: There were 595,929 stroke patients (mean age 78.9y, 54.4% women, 82.2% White) discharged from 134 Low-Low, 2288 Intermediate, and 141 High-High hospitals. For patients treated at Low-Low, Intermediate, and High-High hospitals, respectively, 1-year mortality rates were 23.8% (95% CI 23.3-24.3%), 25.2% (25.1-25.3%), and 26.5% (26.1-26.9%), and recurrence rates were 8.0% (7.6-8.3%), 7.9% (7.8-8.0%), and 8.0% (7.7-8.3%). Compared with patients at High-High hospitals, those at Low-Low and Intermediate hospitals, respectively, had 15% (hazard ratio 0.85; 95% CI 0.82-0.87) and 9% (0.91; 0.89-0.93) lower risks of 1-year mortality but no difference in 1-year recurrence. Conclusions: Ischemic stroke patients treated at better-performing hospitals had lower risks of post-discharge 1-year mortality but similar risks of recurrent stroke compared with patients treated at other hospitals.

Abstract WMP98: Associations Between Long-term Co, No 2 , O 3 , Pm 2.5 , And So 2 Exposure And 30-day All-cause Hospital Readmission Among Stroke Patients In The Us: 2014-2015

Objective: There are known associations between long-term air pollution exposure and greater stroke incidence, morbidity, and mortality; however, there is little research on the association of pollutant exposure with poststroke hospital readmission. Methods: We assessed associations of average annual CO, NO 2 , O 3 , PM 2.5 , and SO 2 exposure with 30-day all-cause hospital readmission in US fee-for-service Medicare beneficiaries age ≥65 years hospitalized for ischemic stroke in 2014-2015. We fit Cox models to assess 30-day readmission as a function of these pollutants, adjusted for patient and hospital factors and temperature. We repeated the models stratified by performance of the treating hospital on the Centers for Medicare &amp; Medicaid Services (CMS) risk-standardized 30-day all-cause readmission for stroke measure to determine if the results were independent of performance: Low (CMS rate for hospital &lt;25th percentile of national rate), High (&gt;75 th percentile), and Middle (all others). Results: There were 448148 patients discharged with stroke in 2014-2015 of whom 12.5% were readmitted. Average 2-year CO, O 3 , PM 2.5 , and SO 2 values during the study were below national standards. In adjusted analyses, each 1 standard deviation increase in average annual NO 2 and SO 2 exposure was associated with a 3.6% (95% CI 2.9%-4.4%) and a 2.0% (95% CI 1.1%-3.0%) increased readmission risk within 30-days, respectively ( Table ). Associations between long-term air pollution exposure and increased readmissions persisted across performance categories. Conclusion: Long-term air pollution exposure was associated with increased 30-day readmissions after stroke at pollutant levels below national standards across hospital performance categories. Additional research is needed to determine whether improvements in air quality lead to reductions in poststroke hospital readmissions.

Development of a 30-Day Readmission Risk Calculator for the Inpatient Rehabilitation Setting.

Readmission to acute care from the inpatient rehabilitation facility (IRF) setting is potentially preventable and an important target of quality improvement and cost savings. The objective of this study was to develop a risk calculator to predict 30-day all-cause readmissions from the IRF setting. Retrospective database analysis using the Uniform Data System for Medical Rehabilitation (UDSMR) from 2015 through2019. In total, 956 US inpatient rehabilitation facilities and 1,849,768 IRF discharges comprising patients from 14 impairment groups. Logistic regression models were developed to calculate risk-standardized 30-day all-cause hospital readmission rates for patients admitted to an IRF. Models for each impairment group were assessed using 12 common clinical and demographic variables and all but 4 models included various special variables. Models were assessed for discrimination (c-statistics), calibration (calibration plots), and internal validation (bootstrapping). A readmission risk scoring system was created for each impairment group population and was graphically validated. The mean age of the cohort was 68.7 (15.2) years, 50.7% were women, and 78.3% were Caucasian. Medicare was the primary payer for 73.1% of the study population. The final models for each impairment group included between 4 and 13 total predictor variables. Model c-statistics ranged from 0.65 to 0.70. There was good calibration represented for most models up to a readmission risk of 30%. Internal validation of the models using bootstrap samples revealed little bias. Point systems for determining risk of 30-day readmission were developed for each impairment group. Multivariable risk factor algorithms based upon administrative data were developed to assess 30-day readmission risk for patients admitted from IRF. This report represents the development of a readmission risk calculator for the IRF setting, which could be instrumental in identifying high risk populations for readmission and targeting resources towards a diverse group of IRF impairment groups.

Ninety-Day Risk-Standardized Home Time as a Performance Metric for Cardiac Surgery Hospitals in the United States.

Assessing hospital performance for cardiac surgery necessitates consistent and valid care quality metrics. The association of hospital-level risk-standardized home time for cardiac surgeries with other performance metrics such as mortality rate, readmission rate, and annual surgical volume has not been evaluated previously. The study included Medicare beneficiaries who underwent isolated or concomitant coronary artery bypass graft, aortic valve, or mitral valve surgery from January 1, 2013, to October 1, 2019. Hospital-level performance metrics of annual surgical volume, 90-day risk-standardized mortality rate, 90-day risk-standardized readmission rate, and 90-day risk-standardized home time were estimated starting from the day of surgery using generalized linear mixed models with a random intercept for the hospital. Correlations between the performance metrics were assessed using the Pearson correlation coefficient. Patient-level clinical outcomes were also compared across hospital quartiles by 90-day risk-standardized home time. Last, the temporal stability of performance metrics for each hospital during the study years was also assessed. Overall, 919 698 patients (age 74.2±5.8 years, 32% women) were included from 1179 hospitals. Median 90-day risk-standardized home time was 71.2 days (25th-75th percentile, 66.5-75.6), 90-day risk-standardized readmission rate was 26.0% (19.5%-35.7%), and 90-day risk-standardized mortality rate was 6.0% (4.0%-8.8%). Across 90-day home time quartiles, a graded decline was observed in the rates of in-hospital, 90-day, and 1-year mortality, and 90-day and 1-year readmission. Ninety-day home time had a significant positive correlation with annual surgical volume (r=0.31; P<0.001) and inverse correlation with 90-day risk-standardized readmission rate (r=-0.40; P <0.001) and 90-day risk-standardized mortality rate (r=-0.60; P <0.001). Use of 90-day home time as a performance metric resulted in a meaningful reclassification in performance ranking of 22.8% hospitals compared with annual surgical volume, 11.6% compared with 90-day risk-standardized mortality rate, and 19.9% compared with 90-day risk-standardized readmission rate. Across the 7 years of the study period, 90-day home time demonstrated the most temporal stability of the hospital performance metrics. Ninety-day risk-standardized home time is a feasible, comprehensive, patient-centered metric to assess hospital-level performance in cardiac surgery with greater temporal stability than mortality and readmission measures.

Spontaneous coronary artery dissection in Spain: a study using the minimum data set of the Spanish National Health System

Introduction and objectivesSpontaneous coronary artery dissection (SCAD) is a rare cause of acute myocardial infarction (AMI). We sought to compare the results on in-hospital mortality and 30-day readmission rates among patients with AMI-SCAD vs AMI due to other causes (AMI-non-SCAD). MethodsRisk-standardized in-hospital mortality (rIMR) and risk-standardized 30-day readmission ratios (rRAR) were calculated using the minimum dataset of the Spanish National Health System (2016-2019). ResultsA total of 806 episodes of AMI-SCAD were compared with 119 425 episodes of AMI–non-SCAD. Patients with AMI-SCAD were younger and more frequently female than those with AMI–non-SCAD. Crude in-hospital mortality was lower (3% vs 7.6%; P<.001) and rIMR higher (7.6±1.7% vs 7.4±1.7%; P=.019) in AMI-SCAD. However, after propensity score adjustment (806 pairs), the mortality rate was similar in the 2 groups (AdjOR, 1.15; 95%CI, 0.61-2,2; P=.653). Crude 30-day readmission rates were also similar in the 2 groups (4.6% vs 5%, P=.67) whereas rRAR were lower (4.7±1% vs 4.8%±1%; P=.015) in patients with AMI-SCAD. Again, after propensity score adjustment (715 pairs) readmission rates were similar in the 2 groups (AdjOR, 1.14; 95%CI, 0.67–1.98; P=.603). ConclusionsIn-hospital mortality and readmission rates are similar in patients with AMI-SCAD and AMI–non-SCAD when adjusted for the differences in baseline characteristics. These findings underscore the need to optimize the management, treatment, and clinical follow-up of patients with SCAD.

Analysis of Hospital-Level Readmission Rates and Variation in Adverse Events Among Patients With Pneumonia in the United States

It is known that hospitalized patients who experience adverse events are at greater risk of readmission; however, it is unknown whether patients admitted to hospitals with higher risk-standardized readmission rates had a higher risk of in-hospital adverse events. To evaluate whether patients with pneumonia admitted to hospitals with higher risk-standardized readmission rates had a higher risk of adverse events. This cross-sectional study linked patient-level adverse events data from the Medicare Patient Safety Monitoring System (MPSMS), a randomly selected medical record abstracted database, to the hospital-level pneumonia-specific all-cause readmissions data from the Centers for Medicare & Medicaid Services. Patients with pneumonia discharged from July 1, 2010, through December 31, 2019, in the MPSMS data were included. Hospital performance on readmissions was determined by the risk-standardized 30-day all-cause readmission rate. Mixed-effects models were used to examine the association between adverse events and hospital performance on readmissions, adjusted for patient and hospital characteristics. Analysis was completed from October 2019 through July 2020 for data from 2010 to 2017 and from March through April 2022 for data from 2018 to 2019. Patients hospitalized for pneumonia. Adverse events were measured by the rate of occurrence of hospital-acquired events and the number of events per 1000 discharges. The sample included 46 047 patients with pneumonia, with a median (IQR) age of 71 (58-82) years, with 23 943 (52.0%) women, 5305 (11.5%) Black individuals, 37 763 (82.0%) White individuals, and 2979 (6.5%) individuals identifying as another race, across 2590 hospitals. The median hospital-specific risk-standardized readmission rate was 17.0% (95% CI, 16.3%-17.7%), the occurrence rate of adverse events was 2.6% (95% CI, 2.54%-2.65%), and the number of adverse events per 1000 discharges was 157.3 (95% CI, 152.3-162.5). An increase by 1 IQR in the readmission rate was associated with a relative 13% higher patient risk of adverse events (adjusted odds ratio, 1.13; 95% CI, 1.08-1.17) and 5.0 (95% CI, 2.8-7.2) more adverse events per 1000 discharges at the patient and hospital levels, respectively. Patients with pneumonia admitted to hospitals with high all-cause readmission rates were more likely to develop adverse events during the index hospitalization. This finding strengthens the evidence that readmission rates reflect the quality of hospital care for pneumonia.

Disección coronaria espontánea en España: un estudio sobre bases administrativas realizado a partir del Conjunto Mínimo Básico de Datos español

Introduction and objectivesSpontaneous coronary artery dissection (SCAD) is a rare cause of acute myocardial infarction (AMI). We sought to compare the results on in-hospital mortality and 30-day readmission rates among patients with AMI-SCAD vs AMI due to other causes (AMI-non-SCAD). MethodsRisk-standardized in-hospital mortality (rIMR) and risk-standardized 30-day readmission ratios (rRAR) were calculated using the minimum dataset of the Spanish National Health System (2016-2019). ResultsA total of 806 episodes of AMI-SCAD were compared with 119 425 episodes of AMI–non-SCAD. Patients with AMI-SCAD were younger and more frequently female than those with AMI–non-SCAD. Crude in-hospital mortality was lower (3% vs 7.6%; P<.001) and rIMR higher (7.6±1.7% vs 7.4±1.7%; P=.019) in AMI-SCAD. However, after propensity score adjustment (806 pairs), the mortality rate was similar in the 2 groups (AdjOR, 1.15; 95%CI, 0.61-2,2; P=.653). Crude 30-day readmission rates were also similar in the 2 groups (4.6% vs 5%, P=.67) whereas rRAR were lower (4.7±1% vs 4.8%±1%; P=.015) in patients with AMI-SCAD. Again, after propensity score adjustment (715 pairs) readmission rates were similar in the 2 groups (AdjOR, 1.14; 95%CI, 0.67–1.98; P=.603). ConclusionsIn-hospital mortality and readmission rates are similar in patients with AMI-SCAD and AMI–non-SCAD when adjusted for the differences in baseline characteristics. These findings underscore the need to optimize the management, treatment, and clinical follow-up of patients with SCAD.

Preventing re-admission: Are general practitioners the solution?

In the United States the Hospital Readmissions Reduction Program (HRRP) is a Medicare value-based purchasing program that encourages hospitals to improve communication and care coordination to better engage patients and caregivers in discharge plans and, in turn, reduce avoidable readmissions [ [1] Centers for Medicare and Medicaid Services. Value based programs. Hospital Readmissions Reduction Program (HRRP). https://www. cms.gov/Medicare/Quality-Initiatives-Patient-AssessmentInstruments/Value-Based-Programs/HRRP/Hospital-ReadmissionReduction-Program. Accessed February 21, 2022. Google Scholar ]. The program supports the national goal of improving health care for Americans by linking payment to the quality of hospital care. The Centers for Medicare & Medicaid Service (CMS) includes the following six condition or procedure-specific 30-day risk-standardized unplanned readmission measures in the program: Acute Myocardial Infarction, Chronic Obstructive Pulmonary Disease, Heart Failure, Pneumonia, Coronary Artery Bypass Graft Surgery, Elective Primary Hip and/or Total Knee Arthroplasty. In this issue of the Journal, John et al attempts through a prospective observational cohort study to address the issue of unplanned hospital readmission by using post discharge consultation with either general practitioners (GPs), specialist physicians or none. This study is part of phase 1 of the TARGET-READ study (Transition cAre inteRvention targeted to hiGh risk patiEnts To Reduce rEADmissions; clincialtrials.org NCTO3496896) [ [2] John G. Payrard L. Donzé J. Associations between post-discharge medical consultations and 30-day unplanned hospital readmission: A prospective observational cohort study. Eur J Intern Med. 2022; 99: 57-62https://doi.org/10.1016/j.ejim.2022.01.013 Abstract Full Text Full Text PDF Scopus (1) Google Scholar ]. Associations between post-discharge medical consultations and 30-day unplanned hospital readmission: A prospective observational cohort studyEuropean Journal of Internal MedicineVol. 99PreviewEarly readmission after hospital discharge is frequent, partly preventable, and puts a heavy burden on healthcare systems [1,2]. Many risk factors—like adverse drug events [3], physician workload [4], patients’ comorbidities [5]—and the internationally validated HOSPITAL score for 30-day potentially avoidable readmission [6] can be assessed directly during the hospital stay. However, physiological stresses experienced during hospitalization extend beyond discharge, resulting in a period of increased vulnerability [7]. Full-Text PDF Open Access

Association of readmission penalty amount with subsequent 30-day risk standardized readmission and mortality rates among patients hospitalized with heart failure: An analysis of get with the guidelines – heart failure participating centers

The Hospital Readmissions Reduction Program penalizes hospitals with excess 30-day risk-standardized readmission rates (RSRR) for heart failure (HF). The association of financial penalty amount with subsequent short-term clinical outcomes is unknown. Patients admitted to American Heart Association Get With The Guidelines-HF registry participating centers from October 1, 2012 through December 1, 2015 who had Medicare-linked data were included. October 2012 hospital-specific penalty amounts were calculated based on diagnosis-related group payments and excess readmission ratios. Adjusted Cox models were created to evaluate the association of penalty amount categories (non-penalized: 0%; low-penalized: >0%-<0.50%; mid-penalized ≥0.50%-<0.99%; high-penalized ≥0.99%) with subsequent 30-day RSRR and risk-standardized mortality rates (RSMR). Trends in post-discharge 30-day RSRR and RSMR from 2012 to 2015 were analyzed across hospitals stratified by penalty amount categories. The present study included 61,329 patients who were admitted across 262 hospitals. Compared with patients admitted to non-penalized hospitals (36.3%), those admitted to increasingly penalized hospitals were more likely to have higher 30-day RSRR (low-penalized [43.9%]: HR, 1.10 [95% CI, 1.04-1.16]; mid-penalized [12.0%]: HR, 1.07 [95% CI, 0.99-1.16]; high-penalized [7.9%]: HR, 1.23 [95% CI, 1.12-1.35]) but not 30-day RSMR. Over time, 30-day RSRR and RSMR did not meaningfully change across penalized versus non-penalized hospitals. Financial penalties based on 30-day RSRR are not associated with declines in 30-day RSRR or RSMR from 2012 to 2015 among patients hospitalized with HF. Financially penalizing hospitals based on current Hospital Readmissions Reduction Program metrics may not incentivize improvements in short-term clinical outcomes for HF.