Expanding Medicaid plays a large role in ensuring that people across the United States have access to health care services. Although North Carolina recently moved toward Medicaid expansion, the impact of expansion on overdoses and overdose mortality may vary based on the type of treatment (offering medications for opioid use disorder [MOUD] vs. offering inpatient medically managed withdrawal without linkage to further MOUD treatment or non-MOUD-based treatment) accessed by individuals newly eligible for treatment through expansion. Based on official North Carolina statistics and published peer-reviewed literature, we developed a simulation model that forecasts opioid overdose and mortality under different scenarios for type of treatment accessed (MOUD-based vs. non-MOUD-based) and Medicaid coverage levels. An optimistic scenario assuming 70 % of individuals newly eligible for treatment would enter treatment during the first year of expansion estimated that 332 (Simulation Interval: 246-412) overdose deaths would be averted. A scenario more in line with recent historical trends assuming 38 % of individuals newly eligible for treatment would enter treatment resulted in 213 (Simulation Interval: 157-263) averted overdose deaths. In all scenarios, MOUD-based treatment approaches increased the number of lives saved compared with approaches expanding opioid treatment through non-MOUD-based treatment. Our study emphasized the need to ensure access to MOUD-based treatment for individuals newly covered by the Medicaid expansion.

Introduction  Gastric cancer, a significant public health concern, remains one of the most challenging malignancies to treat effectively. In the United States, survival rates for gastric cancer have historically been low, partly due to late-stage diagnosis and disparities in access to care. The Affordable Care Act (ACA) sought to address such disparities by expanding healthcare coverage and improving access to preventive and early treatment services.  Objective This study aims to determine the causal effects of the ACA\'s implementation on gastric cancer survival rates, focusing on a comparative analysis between two distinct U.S. states: New Jersey, which fully embraced ACA provisions, and Georgia, which has not adopted the policy, as of 2023.  Methods In this retrospective analysis, we utilized data from the Surveillance, Epidemiology, and End Results Program (SEER) registry to assess the impact of the ACA on cancer-specific survival (CSS) among gastric cancer patients. The study spanned the period from 2000 to 2020, divided into pre-ACA (2000-2013) and post-ACA (2016-2020) periods, with a two-year washout (2013-2015). We compared Georgia (a non-expansion state) to New Jersey (an expansion state since 2014) using a Difference-in-Differences (DiD) approach. We adjusted for patient demographics, income, metropolitan status, disease stage, and treatment modalities.  Results Among 25,061 patients, 58.7% were in New Jersey (14,711), while 41.3% were in Georgia (10,350). The pre-ACA period included 18,878 patients (40.0% in Georgia and 60.0% in New Jersey), and 6,183 patients were in the post-ACA period (45.2% in Georgia and 54.8% in New Jersey). The post-ACA period was associated with a 20% reduction in mortality hazard among gastric cancer patients, irrespective of the state of residence (HR = 0.80, 95% CI: 0.73-0.88). Patients who were residents of New Jersey experienced a 12% reduction in mortality hazard compared to those who resided in Georgia in the post-ACA period (HR = 0.88, 95% CI: 0.78-0.99). Other factors linked to improved survival outcomes included surgery (OR = 0.30, 95% CI: 0.28-0.34) and female gender (OR=0.83, 95% CI: 0.76-0.91).  Conclusion The study underscores the ACA\'s potential positive impact on CSS among gastric cancer patients, emphasizing the importance of healthcare policy interventions in improving patient outcomes.

OBJECTIVE: This study investigated the predictors of postpartum insurance loss (PPIL), assessed its association with postpartum healthcare receipt, and explored the potential buffering role of Medicaid expansion.
METHODS: Data from the 2016-2020 Pregnancy Risk Assessment Monitoring System (PRAMS) were analyzed, covering 197,820 individuals with live births. PPIL was determined via self-reported insurance status before and after pregnancy. Postpartum visits and depression screening served as key health service receipt indicators. The association between PPIL and maternal characteristics was examined using bivariate analysis. The association of PPIL with health service receipt was assessed through odds ratios derived from multivariate logistic regression models. The role of Medicaid expansion was explored by interacting ACA Medicaid expansion status with the dichotomous PPIL indicator.
RESULTS: PPIL was experienced by 7.8% of postpartum people, with higher rates in Medicaid non-expansion states (13.6%) compared to 6.1% in expansion states (p < 0.05). Racial and ethnic disparities were observed, with 16.5% of Hispanic and 4.6% of white people experiencing PPIL. Individuals who experienced PPIL had decreased odds of attending postpartum visits (adjusted odds ratio (aOR) = 0.81, 95% CI = 0.73-0.90) and receiving screening for postpartum depression (aOR = 0.86, 95% CI = 0.78-0.96) compared to those who maintained insurance coverage. People in expansion states with no PPIL had higher odds of postpartum depression screening (aOR = 1.33, 95% CI = 1.08-1.62). No differences in postpartum visits in expansion versus non-expansion were noted (aOR = 1.13, 95% CI = 0.93-1.36).
CONCLUSIONS: Ensuring consistent postpartum insurance coverage offers policymakers a chance to enhance healthcare access and outcomes, particularly for vulnerable groups.

Evidence is mixed on whether increased access to insurance, specifically through the ACA\'s Medicaid expansion, exacerbated the opioid public health crisis through increased opioid prescribing. Using survey data on retail prescription drug fills from 2008 to 2019, we did not find a significant relationship between Medicaid expansion and opioid prescribing in the newly eligible Medicaid population. It may be that the dangers of opioids were known well enough by the time of the Medicaid expansion that lack of access to care was no longer a binding constraint on opioid prescription receipt.

BACKGROUND: Recent mandates from the Center for Medicare and Medicaid Services (CMS) require United States hospitals to disclose healthcare service pricing. Yet, there\'s a gap in understanding how state-level factors affect hospital service pricing, like total shoulder arthroplasty (TSA). Comprehending these influences can help policymakers and healthcare providers manage costs and improve care access for vulnerable populations. The purpose of this study was to examine the effect of state characteristics such as partisan lean, Certificate of Need (CON) status, and Medicaid expansion, on TSA price.
METHODS: TSA price data was extracted from the Turquoise Health Database using CPT code 23472. State partisan lean was determined by evaluating each state during the 2020 election year for its legislature (both senate and house), governor, presidential vote, and Insurance Commissioner affiliation, categorizing states as either \"Republican-leaning\" or \"Democratic-leaning.\" CON status, Medicaid expansion, area deprivation index (ADI), and population density information was obtained from publicly available sources. Multivariable regression models were used to assess the relationship between these factors and TSA price.
RESULTS: The study included 2,068 hospitals nationwide. The median (IQR) price of TSA across these hospitals was $12,607 ($9,185). In the multivariable analysis, hospitals in Republican-leaning states were associated with a significantly greater price of +$210 (p = 0.0151), while Medicaid expansion was also associated with greater price +$1,878 (p < 0.0001). CON status was associated with a significant reduction in TSA prices of -$2,880 (p < 0.0001). In North Carolina an ADI >85 was associated with a reduction in price (p = 0.0045), while urbanization designation did not significantly impact TSA price (p = 0.8457).
CONCLUSIONS: This cross-sectional observational study found that Republican-leaning states and Medicaid expansion were associated with increased TSA prices, while an ADI >85 and CON laws were associated with reduced TSA prices.

BACKGROUND: The Affordable Care Act expanded Medicaid coverage for people with low income in the United States. Expanded insurance coverage could promote more timely access to cancer treatment, which could improve overall survival (OS), yet the long-term effects of Medicaid expansion (ME) remain unknown. We evaluated whether ME was associated with improved timely treatment initiation (TTI) and 3-year OS among patients with breast, cervical, colon, and lung cancers who were affected by the policy.
METHODS: Medicaid-insured or uninsured patients aged 40-64 with stage I-III breast, cervical, colon, or non-small cell lung cancer within the National Cancer Database (NCDB). A difference-in-differences (DID) approach was used to compare changes in TTI (within 60 days) and 3-year OS between patients in ME states versus nonexpansion (NE) states before (2010-2013) and after (2015-2018) ME. Adjusted DID estimates for TTI and 3-year OS were calculated using multivariable linear regression and Cox proportional hazards regression models, respectively.
RESULTS: ME was associated with a relative increase in TTI within 60 days for breast (DID = 4.6; p < 0.001), cervical (DID = 5.0 p = 0.013), and colon (DID = 4.0, p = 0.008), but not lung cancer (p = 0.505). In Cox regression analysis, ME was associated with improved 3-year OS for breast (DID hazard ratio [HR] = 0.82, p = 0.009), cervical (DID-HR = 0.81, p = 0.048), and lung (DID-HR = 0.87, p = 0.003). Changes in 3-year OS for colon cancer were not statistically different between ME and NE states (DID-HR, 0.77; p = 0.075).
CONCLUSIONS: Findings suggest that expanded insurance coverage can improve treatment and survival outcomes among low income and uninsured patients with cancer. As the debate surrounding ME continues nationwide, our findings serve as valuable insights to inform the development of policies aimed at fostering accessible and affordable healthcare for all.

BACKGROUND: The Affordable Care Act (ACA), enacted in 2010, aimed to improve healthcare coverage for American citizens. This study investigates the impact of Medicaid expansion (ME) under the ACA on the racial and ethnic composition of nursing home admissions in the U.S., focusing on whether ME has led to increased representation of racial/ethnic minorities in nursing homes.
METHODS: A difference-in-differences estimation methodology was employed, using U.S. county-level aggregate data from 2000 to 2019. This approach accounted for multiple time periods and variations in treatment timing to analyze changes in the racial and ethnic composition of nursing home admissions post-ME. Additionally, two-way fixed effects (TWFE) regression was utilized to enhance robustness and validate the findings.
RESULTS: The analysis revealed that the racial and ethnic composition of nursing home admissions has become more homogeneous following Medicaid expansion. Specifically, there was a decline in Black residents and an increase in White residents in nursing homes. Additionally, significant differences were found when categorizing states by income inequality, and poverty rate levels. These findings remain statistically significant even after controlling for additional variables, indicating that ME influences the racial makeup of nursing home admissions.
CONCLUSIONS: Medicaid expansion has not diversified nursing home demographics as hypothesized; instead, it has led to a more uniform racial composition, favoring White residents. This trend may be driven by nursing home preferences and financial incentives, which could favor residents with private insurance or higher personal funds. Mechanisms such as payment preferences and local cost variations likely contribute to these shifts, potentially disadvantaging Medicaid-reliant minority residents. These findings highlight the complex interplay between healthcare policy implementation and racial disparities in access to long-term care, suggesting a need for further research on the underlying mechanisms and implications for policy refinement.

States are able to choose whether to expand Medicaid as part of the Affordable Care Act (ACA); thus it is of interest to understand the impact of this policy choice. In this protocol, we outline a study on the impact of Medicaid expansion as part of the ACA on mortality during the COVID-19 pandemic in the United States. County-level matching using full, optimal matching with a propensity score model is used to estimate causal effects in this observational study. Due to the provisional nature of mortality data in 2020 as reported by the CDC, we outline a modified aligned rank test to account for censored data as well as reporting lags for different states. We aim to make connections between statistical and ethnographic methodologies by particularly examining adjacent counties and similar counties that are in the same region of the US and in vastly different regions of the US. Finally, we aim to add to the growing literature about the effect of ACA Medicaid expansion on mortality by calculating effects, disaggregating by race.

OBJECTIVE: To investigate changes in breast cancer incidence rates associated with Medicaid expansion in California.
METHODS: We extracted yearly census tract-level population counts and cases of breast cancer diagnosed among women aged between 20 and 64 years in California during years 2010-2017. Census tracts were classified into low, medium and high groups according to their social vulnerability index (SVI). Using a difference-in-difference (DID) approach with Poisson regression models, we estimated the incidence rate, incidence rate ratio (IRR) during the pre- (2010-2013) and post-expansion periods (2014-2017), and the relative IRR (DID estimates) across three groups of neighborhoods.
RESULTS: Prior to the Medicaid expansion, the overall incidence rate was 93.61, 122.03, and 151.12 cases per 100,000 persons among tracts with high, medium, and low-SVI, respectively; and was 96.49, 122.07, and 151.66 cases per 100,000 persons during the post-expansion period, respectively. The IRR between high and low vulnerability neighborhoods was 0.62 and 0.64 in the pre- and post-expansion period, respectively, and the relative IRR was 1.03 (95% CI 1.00 to 1.06, p = 0.026). In addition, significant DID estimate was only found for localized breast cancer (relative IRR = 1.05; 95% CI, 1.01 to 1.09, p = 0.049) between high and low-SVI neighborhoods, not for regional and distant cancer stage.
CONCLUSIONS: The Medicaid expansion had differential impact on breast cancer incidence across neighborhoods in California, with the most pronounced increase found for localized cancer stage in high-SVI neighborhoods. Significant pre-post change was only found for localized breast cancer between high and low-SVI neighborhoods.

BACKGROUND: Empirical evidence on the effects of Medicaid expansion is mixed and highly state-dependent. The objective of this study is to examine the association of Medicaid expansion with preterm birth and low birth weight, which are linked to a higher risk of infant mortality and chronic health conditions throughout life, providing evidence from a non-expansion state, overall and by race/ethnicity.
METHODS: We used the newborn patient records obtained from Texas Public Use Data Files from 2010 to 2019 for hospitals in Texarkana, which is located on the border of Texas and Arkansas, with all of the hospitals serving pregnancy and childbirth patients on the Texas side of the border. We employed difference-in-differences models to estimate the effect of Medicaid expansion on birth outcomes (preterm birth and low birth weight) overall and by race/ethnicity. Newborns from Arkansas (expanded Medicaid in 2014) constituted the treatment group, while those from Texas (did not adopt the expansion) were the control group. We utilized a difference-in-differences event study framework to examine the gradual impact of the Medicaid expansion on birth outcomes.
RESULTS: Medicaid expansion was associated with a 1.38-percentage-point decrease (95% confidence interval (CI), 0.09-2.67) in preterm birth overall. Event study results suggest that preterm births decreased gradually over time. Medicaid expansion was associated with a 2.04-percentage-point decrease (95% CI, 0.24-3.85) in preterm birth and a 1.75-percentage-point decrease (95% CI, 0.42-3.08) in low birth weight for White infants. However, Medicaid expansion was not associated with significant changes in birth outcomes for other race/ethnicity groups.  CONCLUSIONS: Our findings suggest that Medicaid expansion in Texas can potentially improve birth outcomes. However, bridging racial disparities in birth outcomes might require further efforts such as promoting preconception and prenatal care, especially among the Black population.