Enrollment in High-Deductible Health Plans and Incident Diabetes Complications.

Importance: Preventing diabetes complications requires monitoring and control of hyperglycemia and cardiovascular risk factors. Switching to high-deductible health plans (HDHPs) has been shown to hinder aspects of diabetes care; however, the association of HDHP enrollment with microvascular and macrovascular diabetes complications is unknown. Objective: To examine the association between an employer-required switch to an HDHP and incident complications of diabetes. Design, Setting, and Participants: This retrospective cohort study used deidentified administrative claims data for US adults with diabetes enrolled in employer-sponsored health plans between January 1, 2010, and December 31, 2019. Data analysis was performed from May 26, 2022, to January 2, 2024. Exposures: Adults with a baseline year of non-HDHP enrollment who had to switch to an HDHP because their employer offered no non-HDHP alternative in that year were compared with adults who were continuously enrolled in a non-HDHP. Main Outcomes and Measures: Mixed-effects logistic regression models examined the association between switching to an HDHP and, individually, the odds of myocardial infarction, stroke, hospitalization for heart failure, lower-extremity complication, end-stage kidney disease, proliferative retinopathy, treatment for retinopathy, and blindness. Models were adjusted for demographics, comorbidities, and medications, with inverse propensity score weighting used to account for potential selection bias. Results: The study included 42 326 adults who switched to an HDHP (mean [SD] age, 52 [10] years; 19 752 [46.7%] female) and 202 729 adults who did not switch (mean [SD] age, 53 [10] years; 89 828 [44.3%] female). Those who switched to an HDHP had greater odds of experiencing all diabetes complications (odds ratio [OR], 1.11; 95% CI, 1.06-1.16 for myocardial infarction; OR, 1.15; 95% CI, 1.09-1.21 for stroke; OR, 1.35; 95% CI, 1.30-1.41 for hospitalization for heart failure; OR, 2.53; 95% CI, 2.38-2.70 for end-stage kidney disease; OR, 2.23; 95% CI, 2.17-2.29 for lower-extremity complication; OR, 1.17; 95% CI, 1.13-1.21 for proliferative retinopathy; OR, 2.35; 95% CI, 2.18-2.54 for blindness; and OR, 2.28; 95% CI, 2.15-2.41 for retinopathy treatment). Conclusions and Relevance: This study found that an employer-driven switch to an HDHP was associated with increased odds of experiencing all diabetes complications. These findings reinforce the potential harm associated with HDHPs for people with diabetes and the importance of affordable and accessible chronic disease management, which is hindered by high out-of-pocket costs incurred by HDHPs.

Disparities in Acute and Chronic Complications of Diabetes Along the U.S. Rural-Urban Continuum.

OBJECTIVE: To determine the relative hazards of acute and chronic diabetes complications among people with diabetes across the U.S. rural-urban continuum. RESEARCH DESIGN AND METHODS: This retrospective cohort study used the OptumLabs Data Warehouse, a deidentified data set of U.S. commercial and Medicare Advantage beneficiaries, to follow 2,901,563 adults (age ≥18 years) with diabetes between 1 January 2012 and 31 December 2021. We compared adjusted hazard ratios (HRs) of diabetes complications in remote areas (population <2,500), small towns (population 2,500-50,000), and cities (population >50,000). RESULTS: Compared with residents of cities, residents of remote areas had greater hazards of myocardial infarction (HR 1.06 [95% CI 1.02-1.10]) and revascularization (HR 1.04 [1.02-1.06]) but lower hazards of hyperglycemia (HR 0.90 [0.83-0.98]) and stroke (HR 0.91 [0.88-0.95]). Compared with cities, residents of small towns had greater hazards of hyperglycemia (HR 1.06 [1.02-1.10]), hypoglycemia (HR 1.15 [1.12-1.18]), end-stage kidney disease (HR 1.04 [1.03-1.06]), myocardial infarction (HR 1.10 [1.08-1.12]), heart failure (HR 1.05 [1.03-1.06]), amputation (HR 1.05 [1.02-1.09]), other lower-extremity complications (HR 1.02 [1.01-1.03]), and revascularization (HR 1.05 [1.04-1.06]) but a smaller hazard of stroke (HR 0.95 [0.94-0.97]). Compared with small towns, residents of remote areas had lower hazards of hyperglycemia (HR 0.85 [0.78-0.93]), hypoglycemia (HR 0.92 [0.87-0.97]), and heart failure (HR 0.94 [0.91-0.97]). Hazards of retinopathy and atrial fibrillation/flutter did not vary geographically. CONCLUSIONS: Adults in small towns are disproportionately impacted by complications of diabetes. Future studies should probe for the reasons underlying these disparities.

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.

Why Are There So Few Women Medical School Deans? Debunking the Myth That Shorter Tenures Drive Disparities.

PURPOSE: Gender disparities among the senior echelons of academic medicine are striking and persistent. The role of medical school dean has been particularly immune to gender diversity, and limited prior research identified women's shorter decanal tenures as a potential driver. The authors assessed gender differences in tenure length of deanships in the current era to elucidate this finding. METHOD: From October 2020 to June 2021, the authors collected information about medical school deanships that were held from January 1, 2006, to June 30, 2020. All schools were members of the Association of American Medical Colleges (AAMC). The authors collected data from online public records and augmented their findings via direct outreach to medical schools. They used time-to-event analyses before and after adjustment for interim vs permanent status of the initial appointment, school ownership (public/private), and school size to assess for gender differences in length of deanship tenure during the study period. The unit of analysis was deanships, and the primary outcome was length of deanships measured in years. RESULTS: Authors included data on 528 deanships. Women held 91 (17%) of these terms. Men held the majority of permanent deanships (n = 352 [85%]). A greater percentage of the deanships held by women were interim only (n = 27 [30%]) compared with men (n = 85 [20%]). In unadjusted and adjusted analyses, there were no significant gender differences in length of deanship tenures. CONCLUSIONS: Analysis of appointments of AAMC-member medical school deans from 2006 to 2020 revealed that women have remained in their deanships as long as their male counterparts. The myth about women deans' shorter longevity should no longer be promulgated. Academic medicine should consider novel solutions to addressing women's persistent underrepresentation in the dean role, including employing the gender proportionality principle used in the business and legal communities.

Excess Mortality and Years of Potential Life Lost Among the Black Population in the US, 1999-2020.

Importance: Amid efforts in the US to promote health equity, there is a need to assess recent progress in reducing excess deaths and years of potential life lost among the Black population compared with the White population. Objective: To evaluate trends in excess mortality and years of potential life lost among the Black population compared with the White population. Design, setting, and participants: Serial cross-sectional study using US national data from the Centers for Disease Control and Prevention from 1999 through 2020. We included data from non-Hispanic White and non-Hispanic Black populations across all age groups. Exposures: Race as documented in the death certificates. Main outcomes and measures: Excess age-adjusted all-cause mortality, cause-specific mortality, age-specific mortality, and years of potential life lost rates (per 100 000 individuals) among the Black population compared with the White population. Results: From 1999 to 2011, the age-adjusted excess mortality rate declined from 404 to 211 excess deaths per 100 000 individuals among Black males (P for trend <.001). However, the rate plateaued from 2011 through 2019 (P for trend = .98) and increased in 2020 to 395-rates not seen since 2000. Among Black females, the rate declined from 224 excess deaths per 100 000 individuals in 1999 to 87 in 2015 (P for trend <.001). There was no significant change between 2016 and 2019 (P for trend = .71) and in 2020 rates increased to 192-levels not seen since 2005. The trends in rates of excess years of potential life lost followed a similar pattern. From 1999 to 2020, the disproportionately higher mortality rates in Black males and females resulted in 997 623 and 628 464 excess deaths, respectively, representing a loss of more than 80 million years of life. Heart disease had the highest excess mortality rates, and the excess years of potential life lost rates were largest among infants and middle-aged adults. Conclusions and relevance: Over a recent 22-year period, the Black population in the US experienced more than 1.63 million excess deaths and more than 80 million excess years of life lost when compared with the White population. After a period of progress in reducing disparities, improvements stalled, and differences between the Black population and the White population worsened in 2020.

Adjustment for Social Risk Factors in a Measure of Clinician Quality Assessing Acute Admissions for Patients With Multiple Chronic Conditions.

Importance: Adjusting quality measures used in pay-for-performance programs for social risk factors remains controversial. Objective: To illustrate a structured, transparent approach to decision-making about adjustment for social risk factors for a measure of clinician quality that assesses acute admissions for patients with multiple chronic conditions (MCCs). Design, Setting, and Participants: This retrospective cohort study used 2017 and 2018 Medicare administrative claims and enrollment data, 2013 to 2017 American Community Survey data, and 2018 and 2019 Area Health Resource Files. Patients were Medicare fee-for-service beneficiaries 65 years or older with at least 2 of 9 chronic conditions (acute myocardial infarction, Alzheimer disease/dementia, atrial fibrillation, chronic kidney disease, chronic obstructive pulmonary disease or asthma, depression, diabetes, heart failure, and stroke/transient ischemic attack). Patients were attributed to clinicians in the Merit-Based Incentive Payment System (MIPS; primary health care professionals or specialists) using a visit-based attribution algorithm. Analyses were conducted between September 30, 2017, and August 30, 2020. Exposures: Social risk factors included low Agency for Healthcare Research and Quality Socioeconomic Status Index, low physician-specialist density, and Medicare-Medicaid dual eligibility. Main Outcomes and Measures: Number of acute unplanned hospital admissions per 100 person-years at risk for admission. Measure scores were calculated for MIPS clinicians with at least 18 patients with MCCs assigned to them. Results: There were 4 659 922 patients with MCCs (mean [SD] age, 79.0 [8.0] years; 42.5% male) assigned to 58 435 MIPS clinicians. The median (IQR) risk-standardized measure score was 38.9 (34.9-43.6) per 100 person-years. Social risk factors of low Agency for Healthcare Research and Quality Socioeconomic Status Index, low physician-specialist density, and Medicare-Medicaid dual eligibility were significantly associated with the risk of hospitalization in the univariate models (relative risk [RR], 1.14 [95% CI, 1.13-1.14], RR, 1.05 [95% CI, 1.04-1.06], and RR, 1.44 [95% CI, 1.43-1.45], respectively), but the association was attenuated in adjusted models (RR, 1.11 [95% CI 1.11-1.12] for dual eligibility). Across MIPS clinicians caring for variable proportions of dual-eligible patients with MCCs (quartile 1, 0%-3.1%; quartile 2, >3.1%-9.5%; quartile 3, >9.5%-24.5%, and quartile 4, >24.5%-100%), median measure scores per quartile were 37.4, 38.6, 40.0, and 39.8 per 100 person-years, respectively. Balancing conceptual considerations, empirical findings, programmatic structure, and stakeholder input, the Centers for Medicare & Medicaid Services decided to adjust the final model for the 2 area-level social risk factors but not dual Medicare-Medicaid eligibility. Conclusions and Relevance: This cohort study demonstrated that adjustment for social risk factors in outcome measures requires weighing high-stake, competing concerns. A structured approach that includes evaluation of conceptual and contextual factors, as well as empirical findings, with active engagement of stakeholders can be used to make decisions about social risk factor adjustment.

Assessing Hospital Quality Scores By Proportion Of Patients Dually Eligible For Medicare And Medicaid.

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.

Evaluation of High-Deductible Health Plans and Acute Glycemic Complications Among Adults With Diabetes.

Importance: Optimal diabetes care requires regular monitoring and care to maintain glycemic control. How high-deductible health plans (HDHPs), which reduce overall spending but may impede care by increasing out-of-pocket expenses, are associated with risks of severe hypoglycemia and hyperglycemia is unknown. Objective: To examine the association between an employer-forced switch to HDHP and severe hypoglycemia and hyperglycemia. Design, Setting, and Participants: This retrospective cohort study used deidentified administrative claims data for privately insured adults with diabetes from a single insurance carrier with multiple plans across the US between January 1, 2010, and December 31, 2018. Analyses were conducted between May 15, 2020, and November 3, 2022. Exposures: Patients with 1 baseline year of enrollment in a non-HDHP whose employers subsequently forced a switch to an HDHP were compared with patients who did not switch. Main Outcomes and Measures: Mixed-effects logistic regression models were used to examine the association between switching to an HDHP and the odds of severe hypoglycemia and hyperglycemia (ascertained using diagnosis codes in emergency department [ED] visits and hospitalizations), adjusting for patient age, sex, race and ethnicity, region, income, comorbidities, glucose-lowering medications, baseline ED and hospital visits for hypoglycemia and hyperglycemia, and baseline deductible amount, and applying inverse propensity score weighting to account for potential treatment selection bias. Results: The study population was composed of 42 326 patients who switched to an HDHP (mean [SD] age: 52 [10] years, 19 752 [46.7%] women, 7375 [17.4%] Black, 5740 [13.6%] Hispanic, 26 572 [62.8%] non-Hispanic White) and 202 729 patients who did not switch (mean [SD] age, 53 [10] years, 89 828 [44.3%] women, 29 551 [14.6%] Black, 26 689 [13.2%] Hispanic, 130 843 [64.5%] non-Hispanic White). When comparing all study years, switching to an HDHP was not associated with increased odds of experiencing at least 1 hypoglycemia-related ED visit or hospitalization (OR, 1.01 [95% CI, 0.95-1.06]; P = .85), but each year of HDHP enrollment did increase these odds by 2% (OR, 1.02 [95% CI, 1.00-1.04]; P = .04). In contrast, switching to an HDHP did significantly increase the odds of experiencing at least 1 hyperglycemia-related ED visit or hospitalization (OR, 1.25 [95% CI, 1.11-1.42]; P < .001), with each year of HDHP enrollment increasing the odds by 5% (OR, 1.05 [95% CI, 1.01-1.09]; P = .02). Conclusions and Relevance: In this cohort study, employer-forced switching to an HDHP was associated with increased odds of potentially preventable acute diabetes complications, potentially because of delayed or deferred care. These findings suggest that employers should be more judicious in their health plan offerings, and health plans and policy makers should consider allowing preventive and high-value services to be exempt from deductible requirements.

Measuring health disparities using a continuous social risk factor.

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.

Trends in Racial and Ethnic Disparities in Barriers to Timely Medical Care Among Adults in the US, 1999 to 2018.

Importance: Racial and ethnic disparities in delayed medical care for reasons that are not directly associated with the cost of care remain understudied. Objective: To describe trends in racial and ethnic disparities in barriers to timely medical care among adults during a recent 20-year period. Design, Setting, and Participants: This was a serial cross-sectional study of 590 603 noninstitutionalized adults in the US using data from the National Health Interview Survey from 1999 to 2018. Data analyses were performed from December 2021 through August 2022. Exposures: Self-reported race, ethnicity, household income, and sex. Main Outcomes and Measures: Temporal trends in disparities regarding 5 specific barriers to timely medical care: inability to get through by telephone, no appointment available soon enough, long waiting times, inconvenient office or clinic hours, and lack of transportation. Results: The study cohort comprised 590 603 adult respondents (mean [SE] age, 46.00 [0.07] years; 329 638 [51.9%] female; 27 447 [4.7%] Asian, 83 929 [11.8%] Black, 98 692 [13.8%] Hispanic/Latino, and 380 535 [69.7%] White). In 1999, the proportion of each race and ethnicity group reporting any of the 5 barriers to timely medical care was 7.3% among the Asian group; 6.9%, Black; 7.9%, Hispanic/Latino; and 7.0%, White (P > .05 for each difference compared with White individuals). From 1999 to 2018, this proportion increased across all 4 race and ethnicity groups (by 5.7, 8.0, 8.1, and 5.9 percentage points [pp] among Asian, Black, Hispanic/Latino, and White individuals, respectively; P < .001 for each), slightly increasing the disparities between groups. In 2018, compared with White individuals, the proportion reporting any barrier was 2.1 and 3.1 pp higher among Black and Hispanic/Latino individuals (P = .03 and P = .001, respectively). There was no significant difference in prevalence between Asian and White individuals. There was a significant increase in the difference in prevalence between Black individuals and White individuals who reported delaying care because of long waiting times at the clinic or medical office and because of a lack of transportation (1.5 pp and 1.8 pp; P = .03 and P = .01, respectively). In addition, the difference in prevalence between Hispanic/Latino and White individuals who reported delaying care because of long waiting times increased significantly (2.6 pp; P < .001). Conclusions and Relevance: The findings of this serial cross-sectional study of data from the National Health Interview Survey suggest that barriers to timely medical care in the US increased for all population groups from 1999 to 2018, with associated increases in disparities among race and ethnicity groups. Interventions beyond those currently implemented are needed to improve access to medical care and to eliminate disparities among race and ethnicity groups.

Factors Associated With Disparities in Hospital Readmission Rates Among US Adults Dually Eligible for Medicare and Medicaid.

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.

Temporal Trends in Racial and Ethnic Disparities in Multimorbidity Prevalence in the United States, 1999-2018.

BACKGROUND: Disparities in multimorbidity prevalence indicate health inequalities, as the risk of morbidity does not intrinsically differ by race/ethnicity. This study aimed to determine if multimorbidity differences by race/ethnicity are decreasing over time. METHODS: Serial cross-sectional analysis of the National Health Interview Survey, 1999-2018. Included individuals were ≥18 years old and categorized by self-reported race, ethnicity, age, and income. The main outcomes were temporal trends in multimorbidity prevalence based on the self-reported presence of ≥2 of 9 common chronic conditions. FINDINGS: The study sample included 596,355 individuals (4.7% Asian, 11.8% Black, 13.8% Latino/Hispanic, and 69.7% White). In 1999, the estimated prevalence of multimorbidity was 5.9% among Asian, 17.4% among Black, 10.7% among Latino/Hispanic, and 13.5% among White individuals. Prevalence increased for all racial/ethnic groups during the study period (P ≤ .001 for each), with no significant change in the differences between them. In 2018, compared with White individuals, multimorbidity was more prevalent among Black individuals (+2.5 percentage points) and less prevalent among Asian and Latino/Hispanic individuals (-6.6 and -2.1 percentage points, respectively). Among those aged ≥30 years, Black individuals had multimorbidity prevalence equivalent to that of Latino/Hispanic and White individuals aged 5 years older, and Asian individuals aged 10 years older. CONCLUSIONS: From 1999 to 2018, a period of increasing multimorbidity prevalence for all the groups studied, there was no significant progress in eliminating disparities between Black individuals and White individuals. Public health interventions that prevent the onset of chronic conditions in early life may be needed to eliminate these disparities.

Evaluation of Temporal Trends in Racial and Ethnic Disparities in Sleep Duration Among US Adults, 2004-2018.

Importance: Historically marginalized racial and ethnic groups are generally more likely to experience sleep deficiencies. It is unclear how these sleep duration disparities have changed during recent years. Objective: To evaluate 15-year trends in racial and ethnic differences in self-reported sleep duration among adults in the US. Design, Setting, and Participants: This serial cross-sectional study used US population-based National Health Interview Survey data collected from 2004 to 2018. A total of 429 195 noninstitutionalized adults were included in the analysis, which was performed from July 26, 2021, to February 10, 2022. Exposures: Self-reported race, ethnicity, household income, and sex. Main Outcomes and Measures: Temporal trends and racial and ethnic differences in short (<7 hours in 24 hours) and long (>9 hours in 24 hours) sleep duration and racial and ethnic differences in the association between sleep duration and age. Results: The study sample consisted of 429 195 individuals (median [IQR] age, 46 [31-60] years; 51.7% women), of whom 5.1% identified as Asian, 11.8% identified as Black, 14.7% identified as Hispanic or Latino, and 68.5% identified as White. In 2004, the adjusted estimated prevalence of short and long sleep duration were 31.4% and 2.5%, respectively, among Asian individuals; 35.3% and 6.4%, respectively, among Black individuals; 27.0% and 4.6%, respectively, among Hispanic or Latino individuals; and 27.8% and 3.5%, respectively, among White individuals. During the study period, there was a significant increase in short sleep prevalence among Black (6.39 [95% CI, 3.32-9.46] percentage points), Hispanic or Latino (6.61 [95% CI, 4.03-9.20] percentage points), and White (3.22 [95% CI, 2.06-4.38] percentage points) individuals (P < .001 for each), whereas prevalence of long sleep changed significantly only among Hispanic or Latino individuals (-1.42 [95% CI, -2.52 to -0.32] percentage points; P = .01). In 2018, compared with White individuals, short sleep prevalence among Black and Hispanic or Latino individuals was higher by 10.68 (95% CI, 8.12-13.24; P < .001) and 2.44 (95% CI, 0.23-4.65; P = .03) percentage points, respectively, and long sleep prevalence was higher only among Black individuals (1.44 [95% CI, 0.39-2.48] percentage points; P = .007). The short sleep disparities were greatest among women and among those with middle or high household income. In addition, across age groups, Black individuals had a higher short and long sleep duration prevalence compared with White individuals of the same age. Conclusions and Relevance: The findings of this cross-sectional study suggest that from 2004 to 2018, the prevalence of short and long sleep duration was persistently higher among Black individuals in the US. The disparities in short sleep duration appear to be highest among women, individuals who had middle or high income, and young or middle-aged adults, which may be associated with health disparities.

Identifying high-value care for Medicare beneficiaries: a cross-sectional study of acute care hospitals in the USA.

OBJECTIVES: High-value care is providing high quality care at low cost; we sought to define hospital value and identify the characteristics of hospitals which provide high-value care. DESIGN: Retrospective observational study. SETTING: Acute care hospitals in the USA. PARTICIPANTS: All Medicare beneficiaries with claims included in Center for Medicare & Medicaid Services Overall Star Ratings or in publicly available Medicare spending per beneficiary data. PRIMARY AND SECONDARY OUTCOME MEASURES: Our primary outcome was value defined as the difference between Star Ratings quality score and Medicare spending; the secondary outcome was classification as a 4 or 5 star hospital with lowest quintile Medicare spending ('high value') or 1 or 2 star hospital with highest quintile spending ('low value'). RESULTS: Two thousand nine hundred and fourteen hospitals had both quality and spending data, and were included. The value score had a mean (SD) of 0.58 (1.79). A total of 286 hospitals were classified as high value; these represented 28.6% of 999 4 and 5 star hospitals and 46.8% of 611 low cost hospitals. A total of 258 hospitals were classified as low value; these represented 26.6% of 970 1 and 2 star hospitals and 49.3% of 523 high cost hospitals. In regression models ownership, non-teaching status, beds, urbanity, nurse to bed ratio, percentage of dual eligible Medicare patients and percentage of disproportionate share hospital payments were associated with the primary value score. CONCLUSIONS: There are high quality hospitals that are not high value, and a number of factors are strongly associated with being low or high value. These findings can inform efforts of policymakers and hospitals to increase the value of care.

Perioperative magnetic resonance imaging in breast cancer care: Distinct adoption trajectories among physician patient-sharing networks.

BACKGROUND: Despite no proven benefit in clinical outcomes, perioperative magnetic resonance imaging (MRI) was rapidly adopted into breast cancer care in the 2000's, offering a prime opportunity for assessing factors influencing overutilization of unproven technology. OBJECTIVES: To examine variation among physician patient-sharing networks in their trajectory of adopting perioperative MRI for breast cancer surgery and compare the characteristics of patients, providers, and mastectomy use in physician networks that had different adoption trajectories. METHODS AND FINDINGS: Using the Surveillance, Epidemiology, and End Results-Medicare database in 2004-2009, we identified 147 physician patient-sharing networks (caring for 26,886 patients with stage I-III breast cancer). After adjusting for patient clinical risk factors, we calculated risk-adjusted rate of perioperative MRI use for each physician network in 2004-2005, 2006-2007, and 2008-2009, respectively. Based on the risk-adjusted rate, we identified three distinct trajectories of adopting perioperative MRI among physician networks: 1) low adoption (risk-adjusted rate of perioperative MRI increased from 2.8% in 2004-2005 to 14.8% in 2008-2009), 2) medium adoption (8.8% to 45.1%), and 3) high adoption (33.0% to 71.7%). Physician networks in the higher adoption trajectory tended to have a larger proportion of cancer specialists, more patients with high income, and fewer patients who were Black. After adjusting for patients' clinical risk factors, the proportion of patients undergoing mastectomy decreased from 41.1% in 2004-2005 to 38.5% in 2008-2009 among those in physician networks with low MRI adoption, but increased from 27.0% to 31.4% among those in physician networks with high MRI adoption (p = 0.03 for the interaction term between trajectory group and time). CONCLUSIONS: Physician patient-sharing networks varied in their trajectory of adopting perioperative MRI. These distinct trajectories were associated with the composition of patients and providers in the networks, and had important implications for patterns of mastectomy use.

Association Between Payments by Pharmaceutical Manufacturers and Prescribing Behavior in Rheumatology.

OBJECTIVE: To evaluate the association between pharmaceutical industry payments to rheumatologists and their prescribing behaviors. METHODS: A cross-sectional analysis was conducted of Medicare Part B Public Use File, Medicare Part D Public Use File, and Open Payments data for 2013 to 2015. Prescription drugs responsible for 80% of the total Medicare pharmaceutical expenditures in rheumatology were analyzed. We calculated the mean annual drug cost per beneficiary per year, the percentage of rheumatologists who received payments, and the median annual payment per physician per drug per year. Industry payments were categorized as food/beverage and consulting/compensation. Multivariable regression models were used to assess associations between industry payments and both prescribing patterns and prescription drug expenditures. RESULTS: Of 4822 rheumatologists in the Medicare prescribing databases, 3729 received any payment from a pharmaceutical company during this time frame. Food/beverage payments were associated with an increased proportion of prescriptions for the related drugs (range, 1.5% to 4.5%) and an increased proportion of annual Medicare spending for the related drugs (range, 3% to 23%). For every $100 in food/beverage payments, the probability of prescribing increased (range, 1.5% to 14% for most drugs) and Medicare reimbursements increased (range, 6% to 44% for most drugs). Consulting/compensation payments were associated with an increased proportion of prescriptions (range, 1.2% to 1.6%) and an increased proportion of annual Medicare spending (range, 1% to 2%). For every $1000 in consulting/compensation payments, both the probability of prescribing increased (5% or less for most drugs) and Medicare reimbursements increased (less than 10% for most drugs). CONCLUSION: Payments to rheumatologists by pharmaceutical companies are associated with increased probability of prescribing and Medicare spending.

National Trends in Racial and Ethnic Disparities in Antihypertensive Medication Use and Blood Pressure Control Among Adults With Hypertension, 2011-2018.

Poor hypertension awareness and underuse of guideline-recommended medications are critical factors contributing to poor hypertension control. Using data from 8095 hypertensive people aged ≥18 years from the National Health and Nutrition Examination Survey (2011-2018), we examined recent trends in racial and ethnic differences in awareness and antihypertensive medication use, and their association with racial and ethnic differences in hypertension control. Between 2011 and 2018, age-adjusted hypertension awareness declined for Black, Hispanic, and White individuals, but the 3 outcomes increased or did not change for Asian individuals. Compared with White individuals, Black individuals had a similar awareness (odds ratio, 1.20 [0.96-1.45]) and overall treatment rates (1.04 [0.84-1.25]), and received more intensive antihypertensive medication if treated (1.41 [1.27-1.56]), but had a lower control rate (0.72 [0.61-0.83]). Asian and Hispanic individuals had significantly lower awareness rates (0.69 [0.52-0.85] and 0.74 [0.59-0.89]), overall treatment rates (0.72 [0.57-0.88] and 0.69 [0.55-0.82]), received less intensive medication if treated (0.60 [0.50-0.72] and 0.86 [0.75-0.96]), and had lower control rates (0.66 [0.54-0.79] and 0.69 [0.57-0.81]). The racial and ethnic differences in awareness, treatment, and control persisted over the study period and were consistent across age, sex, and income strata. Lower awareness and treatment were significantly associated with lower control in Asian and Hispanic individuals (P<0.01 for all) but not in Black individuals. These findings highlight the need for interventions to improve awareness and treatment among Asian and Hispanic individuals, and more investigation into the downstream factors that may contribute to the poor hypertension control among Black individuals.

Trends in Differences in Health Status and Health Care Access and Affordability by Race and Ethnicity in the United States, 1999-2018.

IMPORTANCE: The elimination of racial and ethnic differences in health status and health care access is a US goal, but it is unclear whether the country has made progress over the last 2 decades. OBJECTIVE: To determine 20-year trends in the racial and ethnic differences in self-reported measures of health status and health care access and affordability among adults in the US. DESIGN, SETTING, AND PARTICIPANTS: Serial cross-sectional study of National Health Interview Survey data, 1999-2018, that included 596 355 adults. EXPOSURES: Self-reported race, ethnicity, and income level. MAIN OUTCOMES AND MEASURES: Rates and racial and ethnic differences in self-reported health status and health care access and affordability. RESULTS: The study included 596 355 adults (mean [SE] age, 46.2 [0.07] years, 51.8% [SE, 0.10] women), of whom 4.7% were Asian, 11.8% were Black, 13.8% were Latino/Hispanic, and 69.7% were White. The estimated percentages of people with low income were 28.2%, 46.1%, 51.5%, and 23.9% among Asian, Black, Latino/Hispanic, and White individuals, respectively. Black individuals with low income had the highest estimated prevalence of poor or fair health status (29.1% [95% CI, 26.5%-31.7%] in 1999 and 24.9% [95% CI, 21.8%-28.3%] in 2018), while White individuals with middle and high income had the lowest (6.4% [95% CI, 5.9%-6.8%] in 1999 and 6.3% [95% CI, 5.8%-6.7%] in 2018). Black individuals had a significantly higher estimated prevalence of poor or fair health status than White individuals in 1999, regardless of income strata (P < .001 for the overall and low-income groups; P = .03 for middle and high-income group). From 1999 to 2018, racial and ethnic gaps in poor or fair health status did not change significantly, with or without income stratification, except for a significant decrease in the difference between White and Black individuals with low income (-6.7 percentage points [95% CI, -11.3 to -2.0]; P = .005); the difference in 2018 was no longer statistically significant (P = .13). Black and White individuals had the highest levels of self-reported functional limitations, which increased significantly among all groups over time. There were significant reductions in the racial and ethnic differences in some self-reported measures of health care access, but not affordability, with and without income stratification. CONCLUSIONS AND RELEVANCE: In a serial cross-sectional survey study of US adults from 1999 to 2018, racial and ethnic differences in self-reported health status, access, and affordability improved in some subgroups, but largely persisted.

Physician variation in the de-adoption of ineffective statin and fibrate therapy.

OBJECTIVE: To describe physicians' variation in de-adopting concurrent statin and fibrate therapy for type 2 diabetic patients following a reversal in clinical evidence. DATA SOURCES: We analyzed 2007-2015 claims data from OptumLabs® Data Warehouse, a longitudinal, real-world data asset with de-identified administrative claims and electronic health record data. STUDY DESIGN: We modeled fibrate use among Medicare Advantage and commercially insured type 2 diabetic statin users before and after the publication of the ACCORD lipid trial, which found statins and fibrates were no more effective than statins alone in reducing cardiovascular events among type 2 diabetic patients. We modeled fibrate use trends with physician random effects and physician characteristics such as age and specialty. DATA EXTRACTION: We identified patient-year-quarters with one year of continuous insurance enrollment, type 2 diabetes diagnoses, and fibrate use. We designated the physician most responsible for patients' diabetes care based on evaluation and management visits and prescriptions of glucose-lowering drugs. PRINCIPAL FINDINGS: Fibrate use increased by 0.12 percentage points per quarter among commercial patients (95% CI, 0.10 to 0.14) and 0.17 percentage points per quarter among Medicare Advantage patients (95% CI, 0.13 to 0.20) before the trial and then decreased by 0.16 percentage points per quarter among commercial patients (95% CI, -0.18 to -0.15) and 0.05 percentage points per quarter among Medicare Advantage patients (95% CI, -0.06 to -0.03) after the trial. However, 45% of physicians treating commercial patients and 48% of physicians treating Medicare Advantage patients had positive trends in prescribing following the trial. Physicians' characteristics did not explain their variation (pseudo R2  = 0.000). CONCLUSION: On average, physicians decreased fibrate prescribing following the ACCORD lipid trial. However, many physicians increased prescribing following the trial. Observable physician characteristics did not explain variations in prescribing. Future research should examine whether physicians vary similarly in other de-adoption settings.