Changes in Health Care Workers' Economic Outcomes Following Medicaid Expansion.

Importance: The extent to which changes in health sector finances impact economic outcomes among health care workers, especially lower-income workers, is not well known. Objective: To assess the association between state adoption of the Affordable Care Act's Medicaid expansion-which led to substantial improvements in health care organization finances-and health care workers' annual incomes and benefits, and whether these associations varied across low- and high-wage occupations. Design, Setting, and Participants: Difference-in-differences analysis to assess differential changes in health care workers' economic outcomes before and after Medicaid expansion among workers in 30 states that expanded Medicaid relative to workers in 16 states that did not, by examining US individuals aged 18 through 65 years employed in the health care industry surveyed in the 2010-2019 American Community Surveys. Exposure: Time-varying state-level adoption of Medicaid expansion. Main Outcomes and Measures: Primary outcome was annual earned income; secondary outcomes included receipt of employer-sponsored health insurance, Medicaid, and Supplemental Nutrition Assistance Program benefits. Results: The sample included 1 322 263 health care workers from 2010-2019. Health care workers in expansion states were similar to those in nonexpansion states in age, sex, and educational attainment, but those in expansion states were less likely to identify as non-Hispanic Black. Medicaid expansion was associated with a 2.16% increase in annual incomes (95% CI, 0.66%-3.65%; P = .005). This effect was driven by significant increases in annual incomes among the top 2 highest-earning quintiles (ß coefficient, 2.91%-3.72%), which includes registered nurses, physicians, and executives. Health care workers in lower-earning quintiles did not experience any significant changes. Medicaid expansion was associated with a 3.15 percentage point increase in the likelihood that a health care worker received Medicaid benefits (95% CI, 2.46 to 3.84; P < .001), with the largest increases among the 2 lowest-earning quintiles, which includes health aides, orderlies, and sanitation workers. There were significant decreases in employer-sponsored health insurance and increases in SNAP following Medicaid expansion. Conclusion and Relevance: Medicaid expansion was associated with increases in compensation for health care workers, but only among the highest earners. These findings suggest that improvements in health care sector finances may increase economic inequality among health care workers, with implications for worker health and well-being.

Variation in Procedural Denials of Medicaid Eligibility Across States Before the COVID-19 Pandemic.

This cross-sectional study examines denials of Medicaid and Children's Health Insurance Program coverage due to procedural reasons.

Realigning Reality With Intent in Funding Safety-Net Hospitals.

This Viewpoint discusses how revisiting the design and implementation of the disproportionate share hospital program represents a key policy lever for improving health equity in the US.

Patient Experience at US Hospitals Following the Caregiver Advise, Record, Enable (CARE) Act.

Importance: Communication with caregivers is often not established or standardized during hospitalization. The Caregiver Advise, Record, Enable (CARE) Act is a state-level policy designed to facilitate communication among patients, caregivers, and clinical care teams during hospitalization to improve patient experience; 42 states have passed this policy since 2014, but whether it was associated with achieving these goals remains unknown. Objective: To determine whether passage of the CARE Act was associated with improvements in patient experience. Design, Setting, and Participants: This cohort study used a difference-in-differences analysis of short-term, acute-care US hospitals from 2013 to 2019 to analyze changes in patient experience before vs after CARE Act implementation in hospitals located in states that passed the CARE Act compared with those in states that did not. Analyses were performed between September 1, 2021, and July 31, 2022. Exposure: Time-varying indicators for whether a hospital was in a state that passed the CARE Act. Main Outcomes and Measures: Patient-reported experience via the Hospital Consumer Assessment of Healthcare Providers and Systems survey. Results: A total of 2763 hospitals were included, with 2188 hospitals in CARE Act states and 575 in non-CARE Act states. There were differential improvements in patient experience in the measures of communication with nurses (unadjusted mean [SD] score, 78.40% [0.42%]; difference, 0.18 percentage points; 95% CI, 0.07-0.29 percentage points; P = .002), communication with physicians (mean [SD] score, 80.00% [0.19%]; difference, 0.17 percentage points; 95% CI, 0.06-0.28 percentage points; P = .002), and receipt of discharge information (mean [SD] score, 86.40% [0.22%]; difference, 0.11 percentage points; 95% CI, 0.02-0.21 percentage points; P = .02) among CARE Act states compared with non-CARE Act states after policy passage. In subgroup analyses, improvements were larger among hospitals with lower baseline Hospital Consumer Assessment of Healthcare Providers and Systems performance on measures of communication with nurses, communication with physicians, and overall hospital rating. Conclusions and Relevance: These findings suggest that implementation of the CARE Act was associated with improvements in several measures of patient experience. Policies that formally incorporate caregivers into patient care during hospitalization may improve patient outcomes.

Trends in Supply of Nursing Home Beds, 2011-2019.

Importance: Nursing homes play a vital role in providing postacute and long-term care for individuals whose needs cannot be met in the home or community. Whether the supply of nursing home beds and, specifically, the supply of high-quality beds has kept pace with the growth of the older adult population is unknown. Objective: To describe changes in the supply of population-adjusted nursing home beds from 2011 to 2019. Design, Setting, and Participants: This cross-sectional study examines changes in the population-adjusted supply of nursing home beds across all US counties from 2011 to 2019 and describes county and nursing home characteristics where the supply of nursing home beds has increased vs decreased. Main Outcomes and Measures: Number of nursing home beds adjusted per 10 000 adults aged 65 years and older. Results: The population-adjusted supply of nursing home beds declined from 2011 to 2019 for 86.4% of US counties, by a mean (SD) of 129.9 (123.8) beds per 10 000 adults aged 65 years or older per county from a baseline mean (SD) of 552.5 (274.4) beds per 10 000 adults aged 65 years or older per county in 2011. The share of beds that were high quality (4- or 5-star ratings) also declined, which was driven by a small number of counties where nursing home bed supply increased due to a proliferation of lower-quality beds. Simultaneously, metropolitan counties with declining numbers of nursing home beds also experienced declining number of senior housing residential beds (-11.3 [54.6] beds per 10 000 adults aged 65 years or older per county from a baseline mean [SD] of 354.8 [222.3]). Conclusions and Relevance: The findings of this cross-sectional study suggest that the supply of nursing home beds, specifically high-quality nursing home beds, and senior residential housing beds have not kept pace with the demographics of an aging population. Understanding the supply of high-quality nursing home beds and associated geographic variation can inform targeted policies to best support older adults requiring nursing home care.

Variation And Changes In The Targeting Of Medicaid Disproportionate Share Hospital Payments.

Little is known about how Medicaid disproportionate share hospital payments, which are intended to support hospitals that serve low-income patients, are allocated or whether allocation patterns have changed over time. We employed alternative definitions of targeting, or the degree to which allocations were made in a manner consistent with the statutory goals and intent of the program, to examine disproportionate share hospital payment allocations in forty-nine participating states. The most recent data indicate that 57.2 percent of acute care hospitals received disproportionate share hospital payments, totaling more than $14.5 billion, in 2015. The majority of payments went to hospitals with Medicaid shares above the state-specific median (89.1 percent), hospitals with uncompensated care shares above the state-specific median (60.6 percent), or hospitals deemed as disproportionate share per statutory definitions (64.6 percent). However, among all hospitals receiving these payments, up to 31.6 percent of payments were allocated to hospitals that did not meet a given definition, and 3.2 percent went to hospitals that met none of them. These findings suggest that although the majority of the payments were targeted to hospitals serving low-income patients, opportunities exist to better align allocation with statutory goals and intent or to revise applicable statute.

Characteristics of Hospitals Eligible for Rural Emergency Hospital Designation.

This cross-sectional study compares the characteristics, finances, services, and challenges at hospitals that are eligible vs not eligible to become rural emergency hospitals.

Structural Racial Disparities in the Allocation of Disproportionate Share Hospital Payments.

This cross-sectional study examines the allocation of Medicare and Medicaid Disproportionate Share Hospital payments by race.

Lobbying Expenditures in the US Health Care Sector, 2000-2020.

This cross-sectional study uses publicly available, nonpartisan data to evaluate trends in lobbying expenditures across health care industries.

Characteristics, utilization, and concentration of outpatient care for dual-eligible Medicare beneficiaries.

OBJECTIVES: To characterize the (1) distribution of outpatient care for dual-eligible Medicare beneficiaries ("duals") and (2) intensity of outpatient care utilization of duals vs non-dual-eligible beneficiaries ("nonduals"). STUDY DESIGN: Using data preceding the introduction of several outpatient alternative payment models, as well as Medicaid expansion, we evaluated the distribution of outpatient care across physician practices using a Lorenz curve and compared utilization of different outpatient services between duals and nonduals. METHODS: We defined practices that did (high dual) and did not (low dual and no dual) account for the large majority of visits based on the Lorenz curve and then performed descriptive statistics between these groups of practices. Practice-level outcomes included patient demographics, practice characteristics, and county measures of structural disadvantage and population health. Patient-level outcomes included number of outpatient visits and unique outpatient physicians, primary vs subspecialty care visits, and expenditures. RESULTS: Nearly 80% of outpatient visits for duals were provided by 35% of practices. Compared with low-dual and no-dual practices, high-dual practices served more patients (1117.6 patients per high-dual practice vs 683.8 patients per low-dual practice and 447.5 patients per no-dual practice; P < .001) with more comorbidities (3.9 mean total Elixhauser comorbidities among patients served by high-dual practices vs 3.6 among low-dual practices and 3.3 among no-dual practices; P < .001). With regard to utilization, duals had 2 fewer outpatient visits per year compared with nonduals (13.3 vs 15.2; P < .001), with particularly fewer subspecialty care visits (6.5 vs 7.9; P < .001) despite having more comorbidities (3.5 vs 2.7; P < .001). CONCLUSIONS: Outpatient care for duals was concentrated among a small number of practices. Despite having more chronic conditions, duals had fewer outpatient visits. Duals and the practices that serve them may benefit from targeted policies to promote access and improve outcomes.

Changes in economic outcomes before and after rural hospital closures in the United States: A difference-in-differences study.

OBJECTIVE: The objective of this study is to assess changes in local economic outcomes before and after rural hospital closures. DATA SOURCES: Rural hospital closures from January 1, 2005, to December 31, 2018, were obtained from the Sheps Center for Health Services Research. Economic outcomes from this same period were obtained from the Bureau of Labor Statistics, Bureau of Economic Analysis, Quarterly Workforce Indicators, U.S. Federal Reserve Economic Data, RAND Corporation state statistics database, U.S. Social Security Administration, and U.S. Census Bureau. DESIGN: Difference-in-differences study of 2094 rural counties. DATA COLLECTION/EXTRACTION: The primary exposure was county-level rural hospital closures. The primary outcomes were county-level unemployment rates; employment-population ratios; labor force participation-population ratios; per capita income; total jobs; health care sector jobs; disability program participation-population ratios; percent of the population with subprime credit scores; total filings for bankruptcies per 1000 population; and population size. PRINCIPAL FINDINGS: A total of 104 rural counties experienced a hospital closure, compared to 1990 rural counties that did not. Rural hospital closures were associated with significant reductions in health care sector employment (-13.8%; 95% CI: -22%, -5.6%; p < 0.001), but not with changes in any other economic measure. For unemployment rates, employment-population ratios, per capita income, disability program participation-population ratios, and total jobs, we found evidence of adverse trends preceding hospital closures. Findings were robust to adjusting for county-specific time trends, specifying exposure at the commuting zone-level, and using alternate definitions of rurality to define sample counties. CONCLUSION: With the exception of a decline in jobs within the health care sector, there was no association between rural hospital closures and county-level economic outcomes. Instead, economic conditions were already declining in counties experiencing closures compared to those that did not.

Medicaid Expansion Alone Not Associated With Improved Finances, Staffing, Or Quality At Critical Access Hospitals.

Critical access hospitals are important providers of care for rural and other underserved communities, but they face staffing and quality challenges while operating with low margins. Medicaid expansion has been found to improve hospital finances broadly and therefore may have permitted sustained investments in staffing and quality improvement at these vulnerable hospitals. In this difference-in-differences analysis, we found that critical access hospitals in Medicaid expansion states did not have statistically significant postexpansion increases in operating margins relative to hospitals in nonexpansion states. Nor did we see evidence of statistically significant differential improvement at critical access hospitals in expansion versus nonexpansion states on either staffing measures (physicians and registered nurses per 1,000 patient days) or quality measures (percentage-point changes in readmissions and mortality within thirty days of admission for pneumonia or heart failure). These findings suggest that critical access hospitals may need to take additional measures to bolster finances to provide continued support for the delivery of high-quality care to rural and other underserved communities.

The Effect of Hospital Safety Net Status on the Association Between Bundled Payment Participation and Changes in Medical Episode Outcomes.

BACKGROUND: Under Medicare's Bundled Payments for Care Improvement (BPCI) program, hospitals have maintained quality and achieved savings for medical conditions. However, safety net hospitals may perform differently owing to financial constraints and organizational challenges. OBJECTIVE: To evaluate whether hospital safety net status affected the association between bundled payment participation and medical episode outcomes. DESIGN, SETTING, AND PARTICIPANTS: This observational difference-in-differences analysis was conducted in safety net and non-safety net hospitals participating in BPCI for medical episodes (BPCI hospitals) using data from 2011-2016 Medicare fee-for-service beneficiaries hospitalized for acute myocardial infarction, pneumonia, congestive heart failure, and chronic obstructive pulmonary disease. EXPOSURE(S): Hospital BPCI participation and safety net status. MAIN OUTCOME(S) AND MEASURE(S): The primary outcome was postdischarge spending. Secondary outcomes included quality and post-acute care utilization measures. RESULTS: Our sample consisted of 803 safety net and 2263 non-safety net hospitals. Safety net hospitals were larger and located in areas with more low-income individuals than non-safety net hospitals. Among BPCI hospitals, safety net status was not associated with differential postdischarge spending (adjusted difference-in-differences [aDID], $40; 95% CI, -$254 to $335; P = .79) or quality (mortality, readmissions). However, BPCI safety net hospitals had differentially greater discharge to institutional post-acute care (aDID, 1.06 percentage points; 95% CI, 0.37-1.76; P = .003) and lower discharge home with home health (aDID, -1.15 percentage points; 95% CI, -1.73 to -0.58; P < .001) than BPCI non-safety net hospitals. CONCLUSIONS: Under medical condition bundles, safety net hospitals perform differently from other hospitals in terms of post-acute care utilization, but not spending. Policymakers could support safety net hospitals and consider safety net status when evaluating bundled payment programs.

Gender Disparity in Citations in High-Impact Journal Articles.

Importance: Women are less likely to be promoted and hold leadership positions in academic medicine. How often academic articles are cited is a key measure of scholarly impact and frequently assessed for professional advancement; however, it is unknown whether peer-reviewed articles written by men and women are cited differently. Objective: To evaluate whether academic articles from high-impact medical journals written by men and women are cited differently. Design, Setting, and Participants: In this cross-sectional study of all original research and commentary articles from 5 high-impact medical journals (Annals of Internal Medicine, British Medical Journal, JAMA, JAMA Internal Medicine, and The New England Journal of Medicine) from 2015 to 2018, the gender of the primary and senior authors of each article were identified using an online database, and the number of times each article has been cited was identified using Web of Science. The number of citations by primary and senior author gender were then compared. Data were analyzed from July 2020 to April 2021. Exposures: Primary and senior authors' genders. Main Outcomes and Measures: Number of citations per article. Results: Among 5554 articles, women wrote 1975 (35.6%) as primary author and 1273 of 4940 (25.8%) as senior author. Original research articles written by women as primary authors had fewer median (interquartile range) citations than articles written by men as primary authors (36 [17-82] citations vs 54 [22-141] citations; P < .001) and senior authors (37 [17-93] citations vs 51 [20-128] citations; P < .001). Articles written by women as both primary and senior authors had approximately half as many median (interquartile range) citations as those authored by men as both primary and senior authors (33 [15-68] citations vs 59 [23-149] citations; P < .001). Differences in citations remained in each year of the study and were less pronounced among commentary articles. Conclusions and Relevance: In this study, articles written by women in high-impact medical journals had fewer citations than those written by men, particularly when women wrote together as primary and senior authors. These differences may have important consequences for the professional success of women and achieving gender equity in academic medicine.

Association of Medicaid Expansion With Quality in Safety-Net Hospitals.

Importance: Safety-net hospitals (SNHs) operate under limited financial resources and have had challenges providing high-quality care. Medicaid expansion under the Affordable Care Act led to improvements in hospital finances, but whether this was associated with better hospital quality, particularly among SNHs given their baseline financial constraints, remains unknown. Objective: To compare changes in quality from 2012 to 2018 between SNHs in states that expanded Medicaid vs those in states that did not. Design, Setting, and Participants: Using a difference-in-differences analysis in a cohort study, performance on quality measures was compared between SNHs, defined as those in the highest quartile of uncompensated care in the pre-Medicaid expansion period, in expansion vs nonexpansion states, before and after the implementation of Medicaid expansion. A total of 811 SNHs were included in the analysis, with 316 in nonexpansion states and 495 in expansion states. The study was conducted from January to November 2020. Exposures: Time-varying indicators for Medicaid expansion status. Main Outcomes and Measures: The primary outcome was hospital quality measured by patient-reported experience (Hospital Consumer Assessment of Healthcare Providers and Systems Survey), health care-associated infections (central line-associated bloodstream infections, catheter-associated urinary tract infections, and surgical site infections following colon surgery) and patient outcomes (30-day mortality and readmission rates for acute myocardial infarction, heart failure, and pneumonia). Secondary outcomes included hospital financial measures (uncompensated care and operating margins), adoption of electronic health records, provision of safety-net services (enabling, linguistic/translation, and transportation services), or safety-net service lines (trauma, burn, obstetrics, neonatal intensive, and psychiatric care). Results: In this difference-in-differences analysis of a cohort of 811 SNHs, no differential changes in patient-reported experience, health care-associated infections, readmissions, or mortality were noted, regardless of Medicaid expansion status after the Affordable Care Act. There were modest differential increases between 2012 and 2016 in the adoption of electronic health records (mean [SD]: nonexpansion states, 99.4 [7.4] vs 99.9 [3.8]; expansion states, 94.6 [22.6] vs 100.0 [2.2]; 1.7 percentage points; P = .02) and between 2012 and 2018 in the number of inpatient psychiatric beds (mean [SD]: nonexpansion states, 24.7 [36.0] vs 23.6 [39.0]; expansion states: 29.3 [42.8] vs 31.4 [44.3]; 1.4 beds; P = .02) among SNHs in expansion states, although they were not statistically significant at a threshold adjusted for multiple comparisons. In subgroup analyses comparing SNHs with higher vs lower baseline operating margins, an isolated differential improvement was noted in heart failure readmissions among SNHs with lower baseline operating margins in expansion states (mean [SD], 22.8 [2.1]; -0.53 percentage points; P = .001). Conclusions and Relevance: This difference-in-differences cohort study found that despite reductions in uncompensated care and improvements in operating margins, there appears to be little evidence of quality improvement among SNHs in states that expanded Medicaid compared with those in states that did not.

"Make the Implicit Explicit": Measuring Perceptions of Gender Bias and Creating a Gender Bias Curriculum for Internal Medicine Residents.

BACKGROUND: Gender bias in clinical training has been well established; however, little is known about how perceptions differ between men and women. Furthermore, few curricular options have been developed to discuss gender bias. OBJECTIVE: To measure the prevalence of gender bias, examine qualitative differences between men and women, and create a gender bias curriculum for internal medicine residents. METHODS: We surveyed 114 residents (response rate of 53.5%) to identify the prevalence and types of gender bias experienced in training. We compared estimates between genders and organized qualitative results into shared themes. We then developed a curriculum to promote and normalize discussions of gender bias. RESULTS: Among surveyed residents, 61% reported personal experiences of gender bias during training, with 98% of women and 19% of men reporting experiences when stratified by gender. We identified two domains in which gender bias manifested: role misidentification and a difficult working environment. Residents identified action items that led to the development of a gender bias curriculum. The curriculum includes didactic conferences and training sessions, a microaggression response toolkit, dinners for men and women residents, participation in a WhatsApp support group, and participation in academic projects related to gender bias in training. CONCLUSION: We confirmed a wide prevalence of gender bias and developed a scalable curriculum for gender bias training. Future work should explore the long-term impacts of these interventions.