Measuring Equity in Readmission as a Distinct Assessment of Hospital Performance.

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.

Pre-COVID-19 hospital quality and hospital response to COVID-19: examining associations between risk-adjusted mortality for patients hospitalised with COVID-19 and pre-COVID-19 hospital quality.

OBJECTIVES: The extent to which care quality influenced outcomes for patients hospitalised with COVID-19 is unknown. Our objective was to determine if prepandemic hospital quality is associated with mortality among Medicare patients hospitalised with COVID-19. DESIGN: This is a retrospective observational study. We calculated hospital-level risk-standardised in-hospital and 30-day mortality rates (risk-standardised mortality rates, RSMRs) for patients hospitalised with COVID-19, and correlation coefficients between RSMRs and pre-COVID-19 hospital quality, overall and stratified by hospital characteristics. SETTING: Short-term acute care hospitals and critical access hospitals in the USA. PARTICIPANTS: Hospitalised Medicare beneficiaries (Fee-For-Service and Medicare Advantage) age 65 and older hospitalised with COVID-19, discharged between 1 April 2020 and 30 September 2021. INTERVENTION/EXPOSURE: Pre-COVID-19 hospital quality. OUTCOMES: Risk-standardised COVID-19 in-hospital and 30-day mortality rates (RSMRs). RESULTS: In-hospital (n=4256) RSMRs for Medicare patients hospitalised with COVID-19 (April 2020-September 2021) ranged from 4.5% to 59.9% (median 18.2%; IQR 14.7%-23.7%); 30-day RSMRs ranged from 12.9% to 56.2% (IQR 24.6%-30.6%). COVID-19 RSMRs were negatively correlated with star rating summary scores (in-hospital correlation coefficient -0.41, p<0.0001; 30 days -0.38, p<0.0001). Correlations with in-hospital RSMRs were strongest for patient experience (-0.39, p<0.0001) and timely and effective care (-0.30, p<0.0001) group scores; 30-day RSMRs were strongest for patient experience (-0.34, p<0.0001) and mortality (-0.33, p<0.0001) groups. Patients admitted to 1-star hospitals had higher odds of mortality (in-hospital OR 1.87, 95% CI 1.83 to 1.91; 30-day OR 1.46, 95% CI 1.43 to 1.48) compared with 5-star hospitals. If all hospitals performed like an average 5-star hospital, we estimate 38 000 fewer COVID-19-related deaths would have occurred between April 2020 and September 2021. CONCLUSIONS: Hospitals with better prepandemic quality may have care structures and processes that allowed for better care delivery and outcomes during the COVID-19 pandemic. Understanding the relationship between pre-COVID-19 hospital quality and COVID-19 outcomes will allow policy-makers and hospitals better prepare for future public health emergencies.

Procedure Volume and Outcomes With WATCHMAN Left Atrial Appendage Occlusion.

BACKGROUND: Procedure volumes are associated with outcomes for many cardiovascular procedures, leading to guidelines on minimum volume thresholds for certain procedures; however, the volume-outcome relationship with left atrial appendage occlusion is poorly understood. As such, we sought to determine the relationship between hospital and physician volume and WATCHMAN left atrial appendage occlusion procedural success overall and with the new generation WATCHMAN FLX device. METHODS: We performed an analysis of WATCHMAN procedures (January 2019 to October 2021) from the National Cardiovascular Data Registry LAAO Registry. Three-level hierarchical generalized linear models were used to assess the adjusted relationship between procedure volume and procedural success (device released with peridevice leak <5 mm, no in-hospital major adverse events). RESULTS: Among 87 480 patients (76.2±8.0 years; 58.8% men; mean CHA2DS2-VASc score, 4.8±1.5) from 693 hospitals, the procedural success rate was 94.2%. With hospital volume Q4 (greatest volume) as the reference, the likelihood of procedural success was significantly less among Q1 (odds ratio [OR], 0.66 [CI, 0.57-0.77]) and Q2 (OR, 0.78 [CI, 0.69-0.90]) but not Q3 (OR, 0.95 [CI, 0.84-1.07]). With physician volume Q4 (greatest volume) as the reference, the likelihood of procedural success was significantly less among Q1 (OR, 0.72 [CI, 0.63-0.82]), Q2 (OR, 0.79 [CI, 0.71-0.89]), and Q3 (OR, 0.88 [CI, 0.79-0.97]). Among WATCHMAN FLX procedures, there was attenuation of the volume-outcome relationships, with statistically significant but modest absolute differences of only ≈1% across volume quartiles. CONCLUSIONS: In this contemporary national analysis, greater hospital and physician WATCHMAN volumes were associated with increased procedure success. The WATCHMAN FLX transition was associated with increased procedural success and less heterogeneity in outcomes across volume quartiles. These findings indicate the importance of understanding the volume-outcome relationship for individual left atrial appendage occlusion devices.

Procedural volume and outcomes with atrial fibrillation ablation: A report from the NCDR AFib Ablation Registry.

BACKGROUND: The association of hospital and physician procedure volume with outcome has not been well evaluated for atrial fibrillation (AF) ablation in contemporary practice. OBJECTIVE: This study aimed to determine the association between hospital and physician AF ablation volume and procedural success (isolation of all pulmonary veins) and major adverse events (MAEs). METHODS: Procedures reported to the National Cardiovascular Data Registry AFib Ablation Registry between July 2019 and June 2022 were included. Hospital and physician procedural volumes were annualized and stratified into quartiles to compare outcomes. Three-level hierarchical (patient, hospital, and physician) models were used to assess the procedural volume-outcome relationship. RESULTS: A total of 70,296 first-time AF ablations at 186 US hospitals were included. Overall, procedural success and MAE rates were 98.5% and 1.0%, respectively. With hospital volume (Q4) as a reference, the likelihood of procedural success was lower for Q1 (odds ratio [OR], 0.44; 95% CI, 0.29-0.68), Q2 (OR, 0.50; 95% CI, 0.33-0.75), and Q3 (OR, 0.60; 95% CI, 0.40-0.89); the results were similarly significant for physician volume. With MAE for hospitals, there was an inverse procedural volume relationship for Q1 (OR, 1.78; 95% CI, 1.26-2.52) but not for Q2 (OR, 1.06; 95% CI, 0.77-1.46) or Q3 (OR, 1.19; 95% CI, 0.89-1.58) and similarly for physicians in Q1 and Q2 but not in Q3. An adjusted MAE ≤1% was predicted by an annual volume of approximately 190 for hospitals and 60 for physicians. CONCLUSION: In this national cohort, hospital and physician AF ablation procedural volumes were directly related to acute procedural success and inversely related to rates of MAE.

Calculation of Overall Hospital Quality Star Ratings With and Without Inclusion of the Peer Grouping Step.

Importance: The Centers for Medicare & Medicaid Services (CMS) Overall Star Rating is widely used by patients and consumers, and there is continued stakeholder curiosity surrounding the inclusion of a peer grouping step, implemented to the 2021 Overall Star Rating methods. Objective: To calculate hospital star rating scores with and without the peer grouping step, with the former approach stratifying hospitals into 3-, 4-, and 5-measure group peer groups based on the number of measure groups with at least 3 reported measures. Design, Setting, and Participants: This cross-sectional study used Care Compare website data from January 2023 for 3076 hospitals that received a star rating in 2023. Data were analyzed from April 2023 to December 2023. Exposure: Peer grouping vs no peer grouping. Main Outcomes and Measures: The primary outcome was the distribution of star ratings, with 1 star being the lowest-performing hospitals and 5 stars, the highest. Analyses additionally identified the number of hospitals with a higher, lower, or identical star rating with the use of the peer grouping step compared with its nonuse, stratified by certain hospital characteristics. Results: Among 3076 hospitals that received a star rating in 2023, most were nonspecialty (1994 hospitals [64.8%]), nonteaching (1807 hospitals [58.7%]), non-safety net (2326 hospitals [75.6%]), non-critical access (2826 hospitals [91.9%]) hospitals with fewer than 200 beds (1822 hospitals [59.2%]) and located in an urban geographic designations (1935 hospitals [62.9%]). The presence of the peer grouping step resulted in 585 hospitals (19.0%) being assigned a different star rating than if the peer grouping step was absent, including considerably more hospitals receiving a higher star rating (517 hospitals) rather than a lower (68 hospitals) star rating. Hospital characteristics associated with a higher star rating included urbanicity (351 hospitals [67.9%]), non-safety net status (414 hospitals [80.1%]), and fewer than 200 beds (287 hospitals [55.6%]). Collectively, the presence of the peer grouping step supports a like-to-like comparison among hospitals and supports the ability of patients to assess overall hospital quality. Conclusions and Relevance: In this cross-sectional study, inclusion of the peer grouping in the CMS star rating method resulted in modest changes in hospital star ratings compared with application of the method without peer grouping. Given improvement in face validity and the close association between the current peer grouping approach and stakeholder needs for peer-comparison, the current CMS Overall Star Rating method allows for durable comparisons in hospital performance.