The impact of Medicaid expansion on state expenditures through the COVID-19 era.

OBJECTIVE: To investigate the impact of Medicaid expansion on state expenditures through the end of 2022. DATA SOURCES: We used data from the National Association of State Budget Officers (NASBO)'s State Expenditure Report, Kaiser Family Foundation (KFF)'s Medicaid expansion tracker, US Bureau of Labor Statistics data (BLS), US Bureau of Economic Analysis data (BEA), and Pandemic Response Accountability Committee Oversight (PRAC). STUDY DESIGN: We investigated spending per capita (by state population) across seven budget categories, including Medicaid spending, and four spending sources. We performed a difference-in-differences (DiD) analysis that compared within-state changes in spending over time in expansion and nonexpansion states to estimate the effect of Medicaid expansion on state budgets. We adjusted for annual state unemployment rate, annual state per capita personal income, and state spending of Coronavirus Relief Funds (CRF) from 2020 to 2022 and included state and year fixed effects. DATA COLLECTION/EXTRACTION METHODS: We linked annual state-level data on state-reported fiscal year expenditures from NASBO with state-level characteristics from BLS and BEA data and with CRF state spending from PRAC. PRINCIPAL FINDINGS: Medicaid expansion was associated with an average increase of 21% (95% confidence interval [CI]: 16%-25%) in per capita Medicaid spending after Medicaid expansion among states that expanded prior to 2020. After inclusion of an interaction term to separate between the coronavirus disease (COVID) era (2020-2022) and the prior period following expansion (2015-2019), we found that although Medicaid expansion led to an average increase of 33% (95% CI: 21%-45%) in federal funding of state expenditures in the post-COVID years, it was not significantly associated with increased state spending. CONCLUSIONS: There was no evidence of crowding out of other state expenditure categories or a substantial impact on total state spending, even in the COVID-19 era. Increased federal expenditures may have shielded states from substantial budgetary impacts.

Medicare Advantage growth and skilled nursing facility finances.

OBJECTIVE: To examine the relationship between growth in Medicare Advantage (MA) enrollment and changes in finances at skilled nursing facilities (SNFs). DATA SOURCES: Medicare SNF cost reports, LTCFocus.org data, and county MA penetration rates. STUDY DESIGN: We used ordinary least squares regression with SNF and year fixed effects. Our primary outcomes were SNF revenues, expenses, profits, and occupancy. Our primary independent variable was the yearly county Medicare Advantage penetration. DATA COLLECTION/EXTRACTION: We linked facility-year data from 2012 to 2019 obtained from cost reports and LTCFocus.org to county-year MA penetration. PRINCIPAL FINDINGS: A 10 percentage point increase in county MA enrollment was associated with a $213,883.89 (95% Confidence Interval [CI]: -296,869.08, -130,898.71) decrease in revenue, a $132,456.19 (95% CI: -203,852.28, -61,060.10) decrease in expenses, and a 0.59 percentage point (95% CI: -0.97, -0.21) decrease in profit margin. A 10 percentage point increase in county MA enrollment was associated with a decline (-318.93; 95% CI: -468.84, -169.02) in the number of resident-days (a measure of occupancy) as well as a decline in the revenue per resident day ($4.50; 95% CI: -6.81, -2.20), potentially because of lower prices in MA. There was also a decline in expenses per patient day (-2.35; 95% CI: -4.76, 0.05), though this was only statistically significant at the 10% level. While increased MA enrollment was associated with a substantial decline in the number of Medicare resident days (487.53; 95% CI: -588.70, -386.37), this was partially offset by an increase in other payer (e.g., private pay) resident days (285.91; 95% CI: 128.18, 443.63). Increased MA enrollment was not associated with changes in the number of Medicaid resident days or a decrease in staffing per resident day. CONCLUSION: SNFs in counties with more MA growth had substantially greater relative declines in revenue, expenses, and profit margins. The continued growth of MA may result in significant changes in the SNF industry.

Unfulfilled and method-specific contraceptive preferences among reproductive-aged contraceptive users in Arizona, Iowa, New Jersey, and Wisconsin.

OBJECTIVE: To identify characteristics associated with unfulfilled contraceptive preferences, document reasons for these unfulfilled preferences, and examine how these unfulfilled preferences vary across specific method users. DATA SOURCES AND STUDY SETTING: We draw on secondary baseline data from 4660 reproductive-aged contraceptive users in the Arizona, Iowa, New Jersey, and Wisconsin Surveys of Women (SoWs), state-representative surveys fielded between October 2018 and August 2020 across the four states. STUDY DESIGN: This is an observational cross-sectional study, which examined associations between individuals' reproductive health-related experiences and contraceptive preferences, adjusting for sociodemographic characteristics. Our primary outcome of interest is having an unfulfilled contraceptive preference, and a key independent variable is experience of high-quality contraceptive care. We also examine specific contraceptive method preferences according to current method used, as well as reasons for not using a preferred method. DATA COLLECTION/EXTRACTION METHODS: Survey respondents who indicated use of any contraceptive method within the last 3 months prior to the survey were eligible for inclusion in this analysis. PRINCIPAL FINDINGS: Overall, 23% reported preferring to use a method other than their current method, ranging from 17% in Iowa to 26% in New Jersey. Young age (18-24), using methods not requiring provider involvement, and not receiving quality contraceptive care were key attributes associated with unfulfilled contraceptive preferences. Those using emergency contraception and fertility awareness-based methods had some of the highest levels of unfulfilled contraceptive preferences, while pills, condoms, partner vasectomy, and IUDs were identified as the most preferred methods. Reasons for not using preferred contraceptive methods fell largely into one of two buckets: system-level or interpersonal/individual reasons. CONCLUSIONS: Our findings highlight that avenues for decreasing the gap between contraceptive methods used and those preferred to be used may lie with healthcare providers and funding streams that support the delivery of contraceptive care.

The mechanics of risk adjustment and incentives for coding intensity in Medicare.

OBJECTIVE: To study diagnosis coding intensity across Medicare programs, and to examine the impacts of changes in the risk model adopted by the Centers for Medicare and Medicaid Services (CMS) for 2024. DATA SOURCES AND STUDY SETTING: Claims and encounter data from the CMS data warehouse for Traditional Medicare (TM) beneficiaries and Medicare Advantage (MA) enrollees. STUDY DESIGN: We created cohorts of MA enrollees, TM beneficiaries attributed to Accountable Care Organizations (ACOs), and TM non-ACO beneficiaries. Using the 2019 Hierarchical Condition Category (HCC) software from CMS, we computed HCC prevalence and scores from base records, then computed incremental prevalence and scores from health risk assessments (HRA) and chart review (CR) records. DATA COLLECTION/EXTRACTION METHODS: We used CMS's 2019 random 20% sample of individuals and their 2018 diagnosis history, retaining those with 12 months of Parts A/B/D coverage in 2018. PRINCIPAL FINDINGS: Measured health risks for MA and TM ACO individuals were comparable in base records for propensity-score matched cohorts, while TM non-ACO beneficiaries had lower risk. Incremental health risk due to diagnoses in HRA records increased across coverage cohorts in line with incentives to maximize risk scores: +0.9% for TM non-ACO, +1.2% for TM ACO, and + 3.6% for MA. Including HRA and CR records, the MA risk scores increased by 9.8% in the matched cohort. We identify the HCC groups with the greatest sensitivity to these sources of coding intensity among MA enrollees, comparing those groups to the new model's areas of targeted change. CONCLUSIONS: Consistent with previous literature, we find increased health risk in MA associated with HRA and CR records. We also demonstrate the meaningful impacts of HRAs on health risk measurement for TM coverage cohorts. CMS's model changes have the potential to reduce coding intensity, but they do not target the full scope of hierarchies sensitive to coding intensity.

Growing a rural family physician workforce: The contributions of rural background and rural place of residency training.

OBJECTIVE: To determine the distinct influences of rural background and rural residency training on rural practice choice among family physicians. DATA SOURCES AND STUDY SETTING: We used a subset of The RTT Collaborative rural residency list and longitudinal data on family physicians from the American Board of Family Medicine National Graduate Survey (NGS; three cohorts, 2016-2018) and American Medical College Application Service (AMCAS). STUDY DESIGN: We conducted a logistic regression, computing predictive marginals to assess associations of background and residency location with physician practice location 3 years post-residency. DATA COLLECTION/EXTRACTION METHODS: We merged NGS data with residency type-rural or urban-and practice location with AMCAS data on rural background. PRINCIPAL FINDINGS: Family physicians from a rural background were more likely to choose rural practice (39.2%, 95% CI = 35.8, 42.5) than those from an urban background (13.8%, 95% CI = 12.5, 15.0); 50.9% (95% CI = 43.0, 58.8) of trainees in rural residencies chose rural practice, compared with 18.0% (95% CI = 16.8, 19.2) of urban trainees. CONCLUSIONS: Increasing rural programs for training residents from both rural and urban backgrounds, as well as recruiting more rural students to medical education, could increase the number of rural family physicians.

Social determinants of health as a framework to identify and assess cross-sector funding opportunities.

OBJECTIVE: To present a content analysis and method for applying a social determinants of health (SDOH) analytical framework to legislation. DATA SOURCES AND STUDY SETTING: Secondary data include 215 sections of the American Rescue Plan Act of 2021 (ARPA) and related information from federal government websites (e.g., press releases, notices of funding announcements, and funding tables). STUDY DESIGN: Researchers conducted a qualitative content analysis of legislative text, recording all sections, appropriations, allocations, and administrators. Using an SDOH analytical framework defined by Healthy People 2030, researchers coded each section, appropriation, and allocation within the legislation. DATA COLLECTION/EXTRACTION METHODS: Researchers reviewed all ARPA sections, appropriations, and allocations separately, resulting in 328 entries. Descriptive characteristics were calculated using Tableau and Microsoft Excel. Researchers coded each appropriation or allocation using definitions and key words presented in the SDOH analytical framework. PRINCIPAL FINDINGS: Applying an SDOH analytical framework to the legislation's funding amounts reveals an overlap of investment opportunities that cross-sector initiatives can leverage. This overlap is seen primarily in two ways: (1) specific allocations and appropriations that can be used to meet multiple SDOH goals and (2) federal administrators receiving money that can be categorized according to multiple SDOHs. For example, approximately 99% of tracked ARPA funds can be used to support one or more SDOHs. Thirty-five appropriations or allocations can support programs categorized for more than one SDOH category. Eight departments received funds that could be designated for two or more SDOHs. All five SDOH categories can potentially receive funding from 3 to 11 federal administrators. CONCLUSIONS: Using an SDOH analytical framework is an innovative approach to conceptualizing and synthesizing the contents of complex legislation. This approach demonstrates funding patterns across SDOH that can encourage cross-sector collaborations. Future content analysis of legislation can employ this SDOH framework to demonstrate cross-sector initiative funding opportunities.

Veterans Health Administration enrollees' choice of care setting relates to the expansion of care options: Evidence from screening colonoscopies before and after the MISSION Act.

OBJECTIVE: To estimate whether those enrolled in the Veterans Health Administration (VHA) were less likely to use VHA-delivered colorectal cancer screening colonoscopies after the MISSION Act. DATA SOURCES AND STUDY SETTING: Secondary data were collected on VHA-enrolled Veterans from FY2017-FY2021. STUDY DESIGN: This retrospective cross-sectional study measured the volume and share of screening colonoscopies that were VHA-delivered over time and by drive time eligibility-defined as living more than 60 min away from the nearest VHA specialty-care clinic. We used a multivariable logistic regression to adjust for patient and facility factors. DATA EXTRACTION: Data were extracted for VHA enrollees (n = 773,766) who underwent a screening colonoscopy either performed or purchased by the VHA from FY2017-FY2021. PRINCIPAL FINDINGS: In the 9 months after the implementation of the MISSION Act, and before the onset of the Covid-19 pandemic, the average monthly VHA-share of screening colonoscopies decreased by 3 percentage points (pp; 95% confidence interval [CI] = [-4 to -2 pp]) for the non-drive time eligible group and it decreased by 16 pp (95% CI = [-22 to -9 pp]) for the drive time eligible group. The total number of screening colonoscopies did not significantly change in either group during this time period. After adjusting for patient characteristics, a linear time trend, and parent facility fixed effects, implementation of the MISSION Act was associated with a reduction in the probability of a VHA-delivered screening colonoscopy (average marginal effect [AME]: -2.5 pp; 95% CI = [-5.1 to 0.0 pp]) for the non-drive time eligible group. The drive time eligible group (AME: -9.4 pp; 95% CI = [-13.2 to -5.5 pp]) experienced a larger change. CONCLUSIONS: The VHA-share of screening colonoscopies among VHA enrollees fell in the 9 months immediately after the passage of the MISSION Act. This decline was larger for VHA enrollees who were targeted for eligibility due to a longer drive time. These results suggest that the MISSION Act led to more VHA-purchased care among targeted VHA enrollees, though it is unclear whether total utilization increased.

To be or not to be compliant? Hospitals' initial strategic responses to the federal price transparency rule.

OBJECTIVE: To understand US hospitals' initial strategic responses to the federal price transparency rule that took effect January 2021. DATA SOURCES AND STUDY SETTING: Primary interview data collected from 12 not-for-profit hospital organizations in six US metropolitan markets. All but one organization were multihospital systems; the 12 organizations represent a total of 81 hospitals. STUDY DESIGN: Exploratory, cross-sectional, qualitative interview study of a convenience sample of hospital organizations across six geographically and compliance diverse markets. DATA COLLECTION/EXTRACTION METHODS: In-depth, semi-structured, qualitative interviews with 16 key informants across sampled organizations between November 2021 and March 2022. Interviews solicited data about internal organizational factors and external market factors affecting strategic responses. Transcribed interviews were de-identified, coded, and analyzed using the constant comparative method. PRINCIPAL FINDINGS: Hospitals' strategic responses were influenced internally by the degree of the regulation's alignment with organizational values and goals, and task complexity vis-a-vis available resources. We found extensive variation in organizational capabilities to comply, and all but one organization relied on consultants and vendors to some degree. Key external factors driving strategic responses were hospitals' variable perceptions about how available price information would affect their competitive position, bottom line, and reputation. Organizations with more confidence in their interpretation of the environment, including how peers or purchasers would behave, and greater clarity in their own organization's position and goals, had more definitive initial strategic responses. In the first year, organizations' strategic responses skewed toward compliance, especially for the rule's consumer shopping requirements. CONCLUSIONS: A deeper understanding of the realities of operationalizing price transparency policy for hospitals is needed to improve its impact.

Systemic Racism Affecting Latinx Population Health During the COVID-19 Pandemic and Beyond: Perspectives of Latinx Community Health Workers and Community-Based Organization Leaders.

Introduction: The purpose of this study is to identify forms of systemic racism experienced by Latinx communities in North Carolina during the COVID-19 pandemic as identified by Latinx community health workers (CHWs) and community-based organization (CBO) leaders. Methods: We conducted three focus groups in July 2022 (N=16). We performed qualitative analysis of data using an iterative inductive approach of the original language in Dedoose. Results: Four central themes emerged: (1) Access to resources for Latinx individuals; (2) Immediate, transitional, and future fears; (3) Benefits of CHWs; and (4) Lessons learned. Discussion: Institutional and state policies often do not involve community members, such as CHWs and CBO leaders, at the start of the development process, leading to ineffective interventions that perpetuate health disparities and systemic racism. Health Equity Implications: Community-informed policy recommendations can improve alignment of community and policy priorities to create more effective interventions to address systemic racism and promote health equity.

The impact of access to prenatal health insurance for noncitizen women on child health.

OBJECTIVE: To estimate the effects of prenatal public health insurance targeting noncitizens on the health of U.S.-born children of noncitizen mothers beyond birth outcomes. DATA SOURCES AND STUDY SETTING: This paper uses the restricted version of the 1998-2014 National Health Interview Survey with state-level geographic identifiers. STUDY DESIGN: The empirical strategy compares outcomes in states that adopted the Children's Health Insurance Plan (CHIP) Unborn Child Option with states that never adopted or adopted it at different times, controlling for differences in the pre-treatment period. I use a flexible event-study analysis to quantify the effects of the Unborn Child Option on noncitizen women's health insurance coverage, health care utilization, and their children's health. DATA COLLECTION/EXTRACTION METHODS: All data are derived from pre-existing sources. PRINCIPAL FINDINGS: The study finds that the impact of the Unborn Child Option is a 4.7%-point increase in public health insurance coverage (p < 0.01) and 0.48 more doctor's office visits (p < 0.1) annually among noncitizens of childbearing ages. Subsequently, the reform leads to a 7%-point rise in the rate of parents reporting their 4-6-year-old children are in "excellent" or "very good" health (p < 0.01). While no improvements are evident at birth and at younger ages, observed health improvements begin to appear by preschool age. CONCLUSIONS: The study contributes to the literature by providing evidence that certain benefits of in-utero public health insurance targeting noncitizens may appear several years after birth, specifically around preschool age.

The impact of Medicaid expansion on spending and utilization by older low-income Medicare beneficiaries.

OBJECTIVE: To examine indirect spillover effects of Affordable Care Act (ACA) Medicaid expansions to working-age adults on health care coverage, spending, and utilization by older low-income Medicare beneficiaries. DATA SOURCES: 2010-2018 Health and Retirement Study survey data linked to annual Medicare beneficiary summary files. STUDY DESIGN: We estimated individual-level difference-in-differences models of total spending for inpatient, institutional outpatient, physician/professional provider services; inpatient stays, outpatient visits, physician visits; and Medicaid and Part A and B Medicare coverage. We compared changes in outcomes before and after Medicaid expansion in expansion versus nonexpansion states. DATA COLLECTION/EXTRACTION METHODS: The sample included low-income respondents aged 69 and older with linked Medicare data, enrolled in full-year traditional Medicare, and residing in the community. PRINCIPAL FINDINGS: ACA Medicaid expansion was associated with a 9.8 percentage point increase in Medicaid coverage (95% CI: 0.020-0.176), a 4.4 percentage point increase in having any institutional outpatient spending (95% CI: 0.005-0.083), and a positive but statistically insignificant 2.4 percentage point change in Part B enrollment (95% CI: -0.003 to 0.050, p = 0.079). CONCLUSIONS: ACA Medicaid expansion was associated with more institutional outpatient spending among older low-income Medicare beneficiaries. Increased care costs should be weighed against potential benefits from increased realized access to care.

Medicare advantage and dialysis facility choice.

OBJECTIVE: To compare the characteristics of dialysis facilities used by traditional Medicare (TM) and Medicare advantage (MA) enrollees with end-stage kidney disease (ESKD). DATA SOURCES: We used 20% TM claims and 100% MA encounter data from 2018 and publicly available data from the Centers for Medicare and Medicaid Services. STUDY DESIGN: We compared the characteristics of the dialysis facilities treating TM and MA patients in the same ZIP code, adjusting for patient characteristics. The outcome variables were facility ownership, distance to the facility, and several measures of facility quality. DATA COLLECTION/EXTRACTION: We identified point prevalent dialysis patients as of July 15, 2018. PRINCIPAL FINDINGS: Compared to TM patients in the same ZIP code, MA patients were 1.84 percentage points more likely to be treated at facilities owned by the largest two dialysis organizations and 1.85 percentage points less likely to be treated at an independently owned facility. MA patients went to further and lower quality facilities than TM patients in the same ZIP code. However, these differences in facility quality were modest. For example, while the mean dialysis facility mortality rate was 21.85, the difference in mortality rates at facilities treating MA and TM patients in the same ZIP code was 0.67 deaths per 100 patient-years. Similarly, MA patients went to facilities that were, on average, 0.15 miles further than TM patients in the same ZIP code. CONCLUSION: MA enrollees with ESKD were more likely than TM enrollees in the same ZIP code to use the dialysis facilities owned by the two largest chains, travel further for care, and receive care at lower quality facilities. While the magnitude of differences in facility distance and quality was modest, the direction of these results underscores the importance of monitoring dialysis network adequacy as ESKD MA enrollment continues to grow.

Safety-net hospital performance under Comprehensive Care for Joint Replacement.

OBJECTIVE: To investigate the relative progress of safety-net hospitals (SNHs) under Medicare's Comprehensive Care for Joint Replacement (CJR) mandatory bundled payment model over 2016-2020 and to identify the contributors to SNHs' realization of success under the program. DATA SOURCES/STUDY SETTING: Secondary data on all CJR hospitals were collected from the Centers for Medicare and Medicaid Services (CMS) public use files and from the American Hospital Association. STUDY DESIGN: We addressed whether SNHs can achieve progress in financial performance under CJR by focusing on the relative change in reconciliation payments or the difference between episode spending and target prices. We applied the method of dominance analysis to ordinary least squares regression to determine the relative importance of predictors of change in reconciliation payments over time. PRINCIPAL FINDINGS: Compared to CJR hospitals overall, SNHs were less successful in meeting episode spending targets. Hospital factors dominated socioeconomic factors in explaining progress among SNHs, but not among non-SNHs. The contribution of nurse staffing was negligible across all CJR hospitals. CONCLUSIONS: The formula used by CMS to determine spending targets may not be sufficient to address disparities in SNH financial performance under mandatory bundled payment.

Association between non-profit hospital community benefit spending and health outcomes.

OBJECTIVE: To determine if greater non-profit hospital spending for community benefits is associated with better health outcomes in the county where they are located. DATA SOURCES AND STUDY SETTING: Community benefit data from IRS Form 990/Schedule H was linked to health outcome data from Area Health Resource Files, Map the Meal Gap, and Medicare claims from the Center for Medicare and Medicaid Services at the county level. Counties with at least one non-profit hospital in the United States from 2015 to 2019 (N = 5469 across the 5 years) were included. STUDY DESIGN: We ran multiple regressions on community benefit expenditures linked with the number of health professionals, food insecurity, and adherence to diabetes and hypertension medication for each county. DATA COLLECTION: The three outcomes were chosen based on prior studies of community benefit and a recent survey sent to 12 health care executives across four regions of the U.S. Data on community benefit expenditures and health outcomes were aggregated at the county level. PRINCIPAL FINDINGS: Average hospital community benefit spending in 2019 was $63.6 million per county ($255 per capita). Multivariable regression results did not demonstrate significant associations of total community benefit spending with food insecurity or medication adherence for diabetes. Statistically significant associations with the number of health professionals per 1000 (coefficient, 12.10; SE, 0.32; p < 0.001) and medication adherence for hypertension (marginal effect, 0.27; SE, 0.09; p = 0.003) were identified, but both would require very large increases in community benefit spending to meaningfully improve outcomes. CONCLUSIONS: Despite varying levels of non-profit hospital community benefit investment across counties, higher community benefit expenditures are not associated with an improvement in the selected health outcomes at the county level. Hospitals can use this information to reassess community benefit strategies, while federal, state, and local governments can use these findings to redefine the measures of community benefit they use to monitor and grant tax exemption.

The impact of criminal law regulation-based business environment optimization on entrepreneurial spirit and enterprise development.

The purpose is to explore the impact of the business environment optimization by Criminal Law Regulation (CLR) on Entrepreneurial Spirit (ES) and Enterprise Development (ED) and to provide a reference for subsequent related research. Based on this, this work first makes a detailed analysis of the business environment and CLR. Second, the research hypotheses are put forward, and the conceptual model is proposed. At the same time, a Questionnaire Survey (QS) is designed to analyze the business environment, ES, and ED, and their relationships. Finally, a Structural Equation Model (SEM) is constructed and the CLR-optimized business environment is used as the intermediary variable to explore the impact of the business environment on ES and ED. Then, 200 QSs (recovering 192 valid ones) are distributed to investigate entrepreneurs' attitudes toward ES and ED in different regions. Statistical analysis and independent t-tests are performed on the survey results to judge the relationship between variables. The results of empirical analysis show that (1) The significance coefficient P of ES and ED is 0.005 < 0.01, and the scores of ES and ED of large enterprises are 132.7864 and 142.3243, respectively, which are the highest. Therefore, CLR-optimized business regulation has a significant positive impact on the ED. (2) The influence coefficient of CLR-optimized business regulation and ES is 0.60, and the influence coefficient of CLR-optimized business regulation and ED is 0.75. Therefore, CLR-optimized business regulation plays a positive role in the development of ES. CLR-optimized business regulation plays a regulating role between ES and ED. (3) CLR-optimized business regulation has a significant positive impact on the formation of ES. The policy enlightenment of this work mainly has three points. First, optimizing the business environment can stimulate and protect ES, thus improving the quality of economic growth. All regions should promote "mass entrepreneurship and innovation" and high-quality economic development by improving the convergence of economic policies and building a legal and market-oriented business environment. Second, all regions should implement dynamic and differentiated policies to optimize the business environment's spatial pattern in Chinese cities. Third, there is a need to further strengthen the construction of new infrastructure through cutting-edge information technologies, such as Fifth Generation (5G) mobile communication, Big Data, and Artificial Intelligence (AI).

Effects of Medicaid expansion on insurance coverage and health services use among adults with disabilities newly eligible for Medicaid.

OBJECTIVE: To estimate the effects of Affordable Care Act (ACA) Medicaid expansion on insurance and health services use for adults with disabilities who were newly eligible for Medicaid. DATA SOURCES: 2008-2018 Medical Expenditure Panel Survey data. STUDY DESIGN: We used the Agency for Healthcare Research and Quality (AHRQ) PUBSIM model to identify adults aged 26-64 years with disabilities who were newly Medicaid-eligible in expansion states or would have been eligible in non-expansion states had those states opted to expand. Outcomes included insurance coverage; access to care; receipt of primary care, outpatient specialty physician services, and preventive services; and out-of-pocket health care spending. To estimate the effects of Medicaid expansion, we used two-way fixed effects models and a triple differences framework to compare pre-post changes in each outcome in expansion and non-expansion states for adults with and without disabilities. EXTRACTION METHODS: We simulated Medicaid eligibility with the AHRQ PUBSIM model, which uses state-specific Medicaid rules and MEPS data on family relationships, state of residence, and income. PRINCIPAL FINDINGS: Among adults with disabilities who were newly eligible for Medicaid, Medicaid expansion was associated with significant increases in full-year Medicaid coverage (35.9 percentage points [pp], p < 0.001), receipt of primary care (15.5 pp, p < 0.01), and receipt of flu shots (19.2 pp, p < 0.01), and a significant decrease in out-of-pocket spending (-$457, p < 0.01). There were larger improvements for adults with disabilities compared to those without disabilities in full-year Medicaid coverage (11.0 pp, p < 0.01) and receipt of flu shots (18.0 pp, p < 0.05). CONCLUSIONS: Medicaid expansion was associated with improvements in full-year insurance coverage, receipt of primary and preventive care, and out-of-pocket spending for adults with disabilities who were newly eligible for Medicaid. For insurance coverage, preventive care, and some primary care measures, there were differentially larger improvements for adults with disabilities than for those without disabilities.

The association of strained ICU capacity with hospital patient racial and ethnic composition and federal relief during the COVID-19 pandemic.

OBJECTIVE: To identify the association between strained intensive care unit (ICU) capacity during the COVID-19 pandemic and hospital racial and ethnic patient composition, federal pandemic relief, and other hospital characteristics. DATA SOURCES: We used government data on hospital capacity during the pandemic and Provider Relief Fund (PRF) allocations, Medicare claims and enrollment data, hospital cost reports, and Social Vulnerability Index data. STUDY DESIGN: We conducted cross-sectional bivariate analyses relating strained capacity and PRF award per hospital bed with hospital patient composition and other characteristics, with and without adjustment for hospital referral region (HRR). DATA COLLECTION: We linked PRF data to CMS Certification Numbers based on hospital name and location. We used measures of racial and ethnic composition generated from Medicare claims and enrollment data. Our sample period includes the weeks of September 18, 2020 through November 5, 2021, and we restricted our analysis to short-term, general hospitals with at least one intensive care unit (ICU) bed. We defined "ICU strain share" as the proportion of ICU days occurring while a given hospital had an ICU occupancy rate ≥ 90%. PRINCIPAL FINDINGS: After adjusting for HRR, hospitals in the top tercile of Black patient shares had higher ICU strain shares than did hospitals in the bottom tercile (30% vs. 22%, p < 0.05) and received greater PRF amounts per bed ($118,864 vs. $92,407, p < 0.05). Having high versus low ICU occupancy relative to pre-pandemic capacity was associated with a modest increase in PRF amounts per bed after adjusting for HRR ($107,319 vs. $96,627, p < 0.05), but there were no statistically significant differences when comparing hospitals with high versus low ICU occupancy relative to contemporaneous capacity. CONCLUSIONS: Hospitals with large Black patient shares experienced greater strain during the pandemic. Although these hospitals received more federal relief, funding was not targeted overall toward hospitals with high ICU occupancy rates.

Analysis of a national response to a White House directive for ending veteran suicide.

OBJECTIVE: Analyze responses to a national request for information (RFI) to uncover gaps in policy, practice, and understanding of veteran suicide to inform federal research strategy. DATA SOURCE: An RFI with 21 open-ended questions generated from Presidential Executive Order #1386, administered nationally from July 3 to August 5, 2019. STUDY DESIGN: Semi-structured, open-ended responses analyzed using a collaborative qualitative and text-mining data process. DATA EXTRACTION METHODS: We aligned traditional qualitative methods with natural language processing (NLP) text-mining techniques to analyze 9040 open-ended question responses from 722 respondents to provide results within 3 months. Narrative inquiry and the medical explanatory model guided the data extraction and analytic process. RESULTS: Five major themes were identified: risk factors, risk assessment, prevention and intervention, barriers to care, and data/research. Individuals and organizations mentioned different concepts within the same themes. In responses about risk factors, individuals frequently mentioned generic terms like "illness" while organizations mentioned specific terms like "traumatic brain injury." Organizations and individuals described unique barriers to care and emphasized ways to integrate data and research to improve points of care. Organizations often identified lack of funding as barriers while individuals often identified key moments for prevention such as military transitions and ensuring care providers have military cultural understanding. CONCLUSIONS: This study provides an example of a rapid, adaptive analysis of a large body of qualitative, public response data about veteran suicide to support a federal strategy for an important public health topic. Combining qualitative and text-mining methods allowed a representation of voices and perspectives including the lived experiences of individuals who described stories of military transition, treatments that worked or did not, and the perspective of organizations treating veterans for suicide. The results supported the development of a national strategy to reduce suicide risks for veterans as well as civilians.

Impact of the Comprehensive Care for Joint Replacement model on patient-reported outcomes.

OBJECTIVE: To determine whether the Comprehensive Care for Joint Replacement (CJR) model, a mandatory episode-based payment program for knee and hip replacement surgery, affected patient-reported measures of quality. DATA SOURCES: Surveys of Medicare fee-for-service beneficiaries who had hip or knee replacement surgery, collected between July 2018 and March 2019, secondary Medicare administrative data, the Provider of Services file, CJR and Bundled Payments for Care Improvement participant lists from the Centers for Medicare & Medicaid Services, and the Area Health Resource Files. STUDY DESIGN: In 2018, participation in the CJR model was mandatory for nearly all hospitals in 34 randomly selected, metropolitan statistical areas (MSAs) that had high historical Medicare payments for lower-extremity joint replacements surgery. The control group included 47 high-payment MSAs randomly assigned as controls. We estimated risk-adjusted differences in self-reported measures of functional status and pain, satisfaction with care, and caregiver help between respondents in CJR hospitals and respondents in hospitals located in the control group. DATA COLLECTION: We selected a census of CJR patients and an equal number of control patients to survey. We fielded two waves of surveys using a mail and phone protocol, yielding 8433 CJR and 9014 control respondents. PRINCIPAL FINDINGS: CJR respondents were slightly more likely to depend on caregivers for certain activities of daily living when they got home (either directly from the hospital or after an institutional post-acute care stay). On a 100-point scale, differences ranged from -2.6 points (p < 0.01) for help needed bathing to -1.7 points (p < 0.05) for help needed using the toilet. However, differences in eight measures of self-reported functional status approximately 90-120 days after hospital discharge were not statistically significant, ranging from -1.1% (p = 0.087) to 0.7% (p = 0.437). CONCLUSIONS: CJR did not harm patient health or affect patient satisfaction on average but did increase reliance on caregivers during recovery.

From patient outcomes to system change: Evaluating the impact of VHA's implementation of the Whole Health System of Care.

OBJECTIVE: To describe how a partnered evaluation of the Whole Health (WH) system of care-comprised of the WH pathway, clinical care, and well-being programs-produced patient outcomes findings, which informed Veterans Health Administration (VA) policy and system change. DATA SOURCES: Electronic health records (EHR)-based cohort of 1,368,413 patients and a longitudinal survey of Veterans receiving care at 18 WH pilot medical centers. STUDY DESIGN: In partnership with VA operations, we focused the evaluation on the impact of WH services utilization on Veterans' (1) use of opioids and (2) care experiences, care engagement, and well-being. Outcomes were compared between Veterans who did and did not use WH services identified from the EHR. DATA COLLECTION: Pharmacy records and WH service data were obtained from the VA EHR, including WH coaching, peer-led groups, personal health planning, and complementary, integrative health therapies. We surveyed veterans at baseline and 6 months to measure patient-reported outcomes. PRINCIPAL FINDINGS: Opioid use decreased 23% (31.5-6.5) to 38% (60.3-14.4) among WH users depending on level of WH use compared to a secular 11% (12.0-9.9) decrease among Veterans using Conventional Care. Compared to Conventional Care users, WH users reported greater improvements in perceptions of care (SMD = 0.138), engagement in health care (SMD = 0.118) and self-care (SMD = 0.1), life meaning and purpose (SMD = 0.152), pain (SMD = 0.025), and perceived stress (SMD = 0.191). CONCLUSIONS: Evidence developed through this partnership yielded key VA policy changes to increase Veteran access to WH services. Findings formed the foundation of a congressionally mandated report in response to the Comprehensive Addiction and Recovery Act, highlighting the value of WH and complementary, integrative health and well-being programs for Veterans with pain. Findings subsequently informed issuance of an Executive Decision Memo mandating the integration of WH into mental health and primary care across VA, now one lane of modernization for VA.