ABSTRACT
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.
Subject(s)
Hospitals , Cross-Sectional Studies , Humans , United States , Hospitals/standards , Hospitals/statistics & numerical data , Centers for Medicare and Medicaid Services, U.S. , Quality Indicators, Health Care/statistics & numerical data , Quality of Health Care/standards , Quality of Health Care/statistics & numerical dataABSTRACT
This study compares the race and ethnicity of reproductive-age females between states that implemented restrictive abortion policies after the Dobbs v Jackson Women's Health Organization decision and states that did not.
Subject(s)
Ethnicity , Female , Humans , United States , Pregnancy , Adult , Abortion, Induced/legislation & jurisprudence , Abortion, Induced/statistics & numerical data , Racial Groups , Adolescent , Young Adult , Abortion, Legal/legislation & jurisprudence , State GovernmentABSTRACT
We explored the association between the use of a hospital-based food pantry and subsequent emergency department (ED) utilization among Medicaid patients with diabetes in a large safety-net health system. Leveraging 2015-2019 electronic health record data, we used a staggered difference-in-differences approach to measure changes in ED use before vs after food pantry use. Food pantry use was associated with a 7.3 percentage point decrease per patient per quarter (95% confidence interval, -13.8 to -0.8) in the probability of subsequent ED utilization ( P = .03). Addressing food insecurity through hospital-based food pantries may be one mechanism for reducing ED use among low-income patients with diabetes.
Subject(s)
Diabetes Mellitus , Emergency Service, Hospital , Medicaid , Humans , United States , Emergency Service, Hospital/statistics & numerical data , Female , Male , Diabetes Mellitus/therapy , Middle Aged , Adult , Food Assistance , Food Insecurity , Safety-net ProvidersABSTRACT
The Centers for Medicare and Medicaid Services has been reporting hospital star ratings since 2016. Some stakeholders have criticized the star ratings methodology for not adjusting for social risk factors. We examined the relationship between 2021 star rating scores and hospitals' proportion of Medicare patients dually eligible for Medicaid. We found that, on average, hospitals caring for a greater proportion of dually eligible patients had lower star ratings, but there was significant overlap in performance among hospitals when we stratified them by quintile of dually eligible patients. Hospitals in the highest quintile (those with the greatest proportion of dually eligible patients) had the best mean mortality scores (0.28) but the worst readmission (-0.44) and patient experience (-0.78) scores. We assigned star ratings after stratifying the readmission measure group by proportion of dually eligible patients and found that a total of 142 hospitals gained a star and 161 hospitals lost a star, of which 126 (89 percent) and 1 (<1 percent) were in the highest quintile, respectively. Adjusting public reporting tools such as star ratings for social risk factors is ultimately a policy decision, and views on the appropriateness of accounting for factors such as proportion of dually eligible patients are mixed, depending on the organization and stakeholder.
Subject(s)
Medicaid , Medicare , Aged , Humans , United States , HospitalsABSTRACT
OBJECTIVE: To propose and evaluate a novel approach for measuring hospital-level disparities according to the effect of a continuous, polysocial risk factor on those outcomes. STUDY SETTING: Our cohort consisted of Medicare Fee-for-Service (FFS) patients 65 years and older admitted to acute care hospitals for one of six common conditions or procedures. Medicare administrative claims data for six hospital readmission measures including hospitalizations from July 2015 to June 2018 were used. STUDY DESIGN: We adapted existing methodologies that were developed to report hospital-level disparities using dichotomous social risk factors (SRFs). The existing methods report disparities within and across hospitals; we developed and tested modified approaches for both methods using the Agency for Healthcare Research and Quality Socioeconomic Status Index. We applied the adapted methodologies to six 30-day hospital readmission measures included in the Centers for Medicare & Medicaid Services Hospital Readmissions Reduction Program measures. We compared the within- and across-hospital results for each to those obtained from using the original methods and dichotomizing the AHRQ SES Index into "low" and "high" scores. DATA COLLECTION: We used Medicare FFS administrative claims data linked to U.S. Census data. PRINCIPAL FINDINGS: For all six readmission measures we find that, when compared with the existing methods, the methods for continuous SRFs provide disparity results for more facilities though across a narrower range of values. Measures of disparity based on this approach are moderately to highly correlated with those based on a dichotomous version of the same risk factor, while reflecting a fuller spectrum of risk. This approach represents an opportunity for detection of provider-level results that more closely align with underlying social risk. CONCLUSION: We have demonstrated the feasibility and utility of estimating hospital disparities of care using a continuous, polysocial risk factor. This approach expands the potential for reporting hospital-level disparities while better accounting for the multifactorial nature of social risk on hospital outcomes.
Subject(s)
Hospitalization , Medicare , Humans , Aged , United States , Patient Readmission , Hospitals , Risk FactorsABSTRACT
Objectives: Modern sport safeguarding strategies include published global rights declarations that enshrine athletes' entitlements at the policy level. It is unclear how these documents translate to athletes' lived experiences. The study aimed to determine athletes' knowledge, attitudes and beliefs about their human rights in sports settings. Setting: Web-based survey. Participants: 1159 athletes from 70 countries completed a validated web-based survey. Over half of participants (60.1%) were between 18 and 29 years, currently competing (67.1%), not members of players' unions (54.6%), elite (60.0%) and participating in individual (55.8%) non-contact (75.6%) Olympic (77.9%) sports. Gender distribution was equal. Primary and secondary outcome measures: Participant demographics (eg, gender, age) and athletes' knowledge, attitudes and beliefs about their human rights in sports settings. Results: Most (78.5%) were unaware of any athletes' rights declarations. Gender influenced participants' confidence in acting on their rights in sport significantly. Males were more likely to accept pressure from coaches and teammates than females, but age affected how likely males were to accept this pressure. Paralympic athletes were less likely to agree that violence is acceptable in sports, compared with Olympic. Player union membership increased confidence in freely expressing one's opinion in sports settings. Athletes' rights-related awareness, knowledge and beliefs were disconnected. Conclusions: Awareness raising is not enough to prevent human rights violations in sports. The cultural climate of the entire ecosystem must be targeted, using systems-level strategies to shift stakeholders' biases, beliefs and behaviours. This approach takes the onus of addressing abuse off athletes' shoulders and places accountability on sports organisations.
ABSTRACT
Importance: Low-income older adults who are dually eligible (DE) for Medicare and Medicaid often experience worse outcomes following hospitalization. Among other federal policies aimed at improving health for DE patients, Medicare has recently begun reporting disparities in within-hospital readmissions. The degree to which disparities for DE patients are owing to differences in community-level factors or, conversely, are amenable to hospital quality improvement, remains heavily debated. Objective: To examine the extent to which within-hospital disparities in 30-day readmission rates for DE patients are ameliorated by state- and community-level factors. Design Setting and Participants: In this retrospective cohort study, Centers for Medicare & Medicaid Services (CMS) Disparity Methods were used to calculate within-hospital disparities in 30-day risk-adjusted readmission rates for DE vs non-DE patients in US hospitals participating in Medicare. All analyses were performed in February and March 2019. The study included Medicare patients (aged ≥65 years) hospitalized for acute myocardial infarction (AMI), heart failure (HF), or pneumonia in 2014 to 2017. Main Outcomes and Measures: Within-hospital disparities, as measured by the rate difference (RD) in 30-day readmission between DE vs non-DE patients following admission for AMI, HF, or pneumonia; variance across hospitals; and correlation of hospital RDs with and without adjustment for state Medicaid eligibility policies and community-level factors. Results: The final sample included 475 444 patients admitted for AMI, 898 395 for HF, and 1 214 282 for pneumonia, of whom 13.2%, 17.4%, and 23.0% were DE patients, respectively. Dually eligible patients had higher 30-day readmission rates relative to non-DE patients (RD >0) in 99.0% (AMI), 99.4% (HF), and 97.5% (pneumonia) of US hospitals. Across hospitals, the mean (IQR) RD between DE vs non-DE was 1.00% (0.87%-1.10%) for AMI, 0.82% (0.73%-0.96%) for HF, and 0.53% (0.37%-0.71%) for pneumonia. The mean (IQR) RD after adjustment for community-level factors was 0.87% (0.73%-0.97%) for AMI, 0.67% (0.57%-0.80%) for HF, and 0.42% (0.29%-0.57%) for pneumonia. Relative hospital rankings of corresponding within-hospital disparities before and after community-level adjustment were highly correlated (Pearson coefficient, 0.98). Conclusions and Relevance: In this cohort study, within-hospital disparities in 30-day readmission for DE patients were modestly associated with differences in state Medicaid policies and community-level factors. This suggests that remaining variation in these disparities should be the focus of hospital efforts to improve the quality of care transitions at discharge for DE patients in efforts to advance equity.
Subject(s)
Heart Failure , Myocardial Infarction , Pneumonia , Aged , Cohort Studies , Heart Failure/epidemiology , Humans , Medicaid , Medicare , Myocardial Infarction/epidemiology , Patient Readmission , Pneumonia/epidemiology , Retrospective Studies , United States/epidemiologyABSTRACT
A recognised imbalance of power exists between athletes and sporting institutions. Recent cases of systemic athlete abuse demonstrate the relationship between power disparities and harassment and abuse in sport. Embedding human rights principles into sporting institutions is a critical step towards preventing harassment and abuse in sport. In 2017, the World Players Association (WPA) launched the Universal Declaration of Player Rights. A year later, the International Olympic Committee (IOC) developed their Athletes' Rights and Responsibilities Declaration. These two documents codify benchmarks 'for international sporting organisations to meet their obligations to protect, respect and guarantee the fundamental rights of players'. This paper is the first project exploring athletes' knowledge, understanding and awareness of rights in the sports context. This study presents the development and validation of a survey investigating athletes' knowledge of these declarations, associated attitudes/beliefs and understanding of how these rights can be enacted in practice. The survey includes 10 statements of athlete rights based on the WPA and IOC declarations. Face validation was assessed by distributing the survey to 10 athletes and conducting qualitative interviews with a subgroup of four athletes. The survey was reworked into 13 statements, and the tool was validated with 611 responses through confirmatory factor analysis. Key findings include a weak correlation between athletes' knowledge and their attitudes/beliefs, and challenges with the interpretation of words such as 'pressure,' 'violence,' 'harassment' and 'intimidation.' This validation puts forward the first survey instrument to directly test athletes' knowledge, attitudes and beliefs about rights in sport.