This study investigated the effect of multiple patient and treatment-related factors, together with supervision frequency of assigned attending faculty, on orthodontic treatment duration in an advanced education clinic. This study included 295 patients who completed non-surgical orthodontic treatment at the Ohio State University graduate orthodontic clinic during 2016-2020, whose active treatment duration was calculated. Fifteen factors, including patients' age, sex, Medicaid eligibility, number of broken and urgent appointments, initial and final Peer Assessment Rating (PAR) Index, PAR improvement, occurrence of transfers, extraction or non-extraction plan, midcourse treatment plan change, extended adjustment interval, and frequency of assigned faculty supervision, were collected. Intra-rater reliability of data acquisition was assessed by intraclass correlation coefficient (ICC) and kappa tests for continuous and categorical variables, respectively. Effects of these factors on treatment duration were assessed by an Analysis of Covariance (ANCOVA) test. Intra-rater reliability for data acquisition was excellent (ICC or kappa >0.9) except for treatment plan change. For effects on treatment duration, statistical significance (p<0.05) was reached for the number of broken and urgent appointments, initial PAR score, supervision frequency of assigned faculty, occurrence of transfer among residents, and major treatment plan change. As for clinical significance (reflected by estimates of impact), an increase in the number of broken/urgent appointments and the occurrence of transfer prolonged treatment duration more substantially than a decrease in faculty supervision frequency. To avoid prolonging treatment duration in graduate orthodontic clinics, efforts to reduce patients' broken/urgent appointments and transfers among residents are more important than maximizing assigned faculty supervision frequency.

Medicaid eligibility for nursing home care is determined in part by an individual's (or a couples', if married) financial resources, including income and assets. To qualify, individuals must "spend down" their resources to meet states' Medicaid eligibility asset thresholds. Little empirical work has examined the rate of Medicaid spend-down in nursing homes over the past 2 decades. To identify the rate of spend-down in nursing homes, defined as the share of total residents who began their stay as non-Medicaid enrolled (after accounting for Medicare-covered skilled nursing facility [SNF] days, where applicable) and became Medicaid enrolled before discharge or death. This cohort study used a combination of administrative, enrollment, and claims data from 2018 to 2022 to build a panel of 191 416 US nursing home residents enrolled in traditional Medicare-including those admitted for postacute and long-term care-who newly entered a facility in 2018 and either stayed beyond their Medicare SNF days or did not have any Medicare-covered SNF days. Statistical analysis was performed from July 2024 to October 2025. Newly entering a nursing home in 2018 as non-Medicaid enrolled. The main outcome was whether an individual spent down their assets and became enrolled in Medicaid during their nursing home stay. Multivariate regression was used to identify factors associated with spend-down. The study included 191 416 individuals (mean [SD] age at time of admission, 81.0 [11.4] years; 58.0% women; mean [SD] time in nursing home, 331.0 [485.8] days) with traditional Medicare who newly entered a nursing home in 2018, of whom 33.9% either began their stay as Medicaid enrolled or enrolled in Medicaid after the completion of their Medicare-covered SNF days. The remaining 66.2% of individuals were initially not enrolled in Medicaid on admission or after the completion of their Medicare-covered SNF days. Of those who were initially not Medicaid enrolled, 16.4% spent down their assets during their stay and enrolled in Medicaid (mean [SD] time to spend-down, 6.1 [7.9] months). The likelihood of spend-down increased with length of stay and was higher among Black, Hispanic, North American Native, and younger residents. In this cohort study of nursing home residents, those who entered a nursing home as initially non-Medicaid enrolled, especially those with longer stays, were at risk of spending down their assets and enrolling in Medicaid. This finding raises concerns both about individuals impoverishing themselves because of the high cost of care and the long-term financial sustainability of the Medicaid program.

The study aims to analyze the impact of Medicaid Expansion on hospital finances. Medicaid eligibility may increase hospital reimbursements and lower uncompensated care costs if patients are moving from no insurance coverage to Medicaid. However, if patients taking up Medicaid are moving from a private insurance plan to Medicaid, then it is also possible that hospital reimbursements may be lower under Medicaid expansion. Medicaid expansion increased the eligibility for Medicaid coverage to a broader group of people and raised the income threshold to 138% of the federal poverty level. Some states chose to expand Medicaid while others did not. Using a natural experiment, I compare hospital revenues and uncompensated care costs in Eastern Washington, which chose to expand Medicaid in 2014, and in Idaho, which chose not to expand until 2020. Medicaid expansion may be associated with lower net revenues, higher Medicaid received, and lower uncompensated care costs per hospital bed, ceteris paribus. I find no significant impact on operating margins. This study adds to the current literature looking at Medicaid Expansion and hospital finances by looking at a different region than has been previously studied. This region offers similar demographic and economic situations in both states. These areas are more rural areas and have less populated cities, which allows for a unique perspective and contributes to the understanding of how Medicaid Expansion may impact hospital finances.

The issue of maternal morbidity and mortality is a highly urgent American health problem, with more than 50,000 women experiencing pregnancy complications each year. However, Black women are three times more likely to die because of pregnancy-related problems than White women in the United States (U.S.). Black women also experience disproportionately higher rates of maternal mortality than women of every other ethnic and racial group. Compared to other affluent countries, the United States has a strikingly high maternal mortality rate. Between 1990 and 2019, the rate in the U.S. nearly tripled, rising from 8.0 to 20.1 deaths per 100,000 live births. In the last twenty years, maternal mortality rates have declined in countries around the globe, but in the U.S., there has been a 50% increase in maternal mortality. Maternal mortality rates are highest in Mississippi, which had 82.5 deaths per 100,000 births in 2021, and lowest in California, which had 9.7 deaths per 100,000 births in 2021. Expanding Medicaid eligibility, extending postpartum coverage, standardizing care delivery, combating racial bias in medical care through provider training, subsidizing Black physician tuition, and increasing rural health care access will help not only reduce maternal deaths nationwide but also diminish racial disparities in maternal health outcomes.

Changes in breast and cervical cancer screening rates among Latinas after Medicaid expansion.

Affordable access to surgical procedures remains elusive for many in the US. However, the financial hardship attributable to surgical procedures is not well understood at the national level. To evaluate the association between surgical procedures and financial hardship among working-aged adults in the US, compare changes in financial hardship after elective vs emergency surgery, and examine variation by payer and income. This retrospective cohort study of the Medical Expenditure Panel Survey (MEPS) included respondents from 2014 to 2021. The MEPS is a nationally representative survey of noninstitutionalized US civilians. All adults aged 18 to 64 years old who reported undergoing a surgical procedure were matched to a cohort of nonsurgical control patients using coarsened exact matching on age, sex, race, ethnicity, income, payer, census region, comorbidities, and year. These data were analyzed from January 2025 to August 2025. The primary exposure was surgical procedure(s) within the last 12 months; secondary exposure was emergency vs elective surgical procedures. The primary outcome of interest was financial hardship, defined as problems paying medical bills or delaying needed care due to cost. Secondary outcome was family out-of-pocket (OOP) spending. The weighted sample included 40 million working-aged (18-64 years) adults (62% female and 38% male) who underwent surgical procedures. Overall, 37.9% of surgical patients experienced financial hardship in the year after surgery. On difference-in-differences analysis, surgical procedures were associated with a 5.4-percentage point increase (95% CI, 1.8-9.0) in financial hardship, a 16% relative increase. Uninsured patients had a 23.7-percentage point increase (95% CI, 5.1-42.2), privately insured patients had an 8.4-percentage point increase (95% CI, 3.6-13.1), and those with Medicaid had no significant change. OOP spending increased by $708 (95% CI, $576-$839) after operations, with the highest increases among emergency surgeries and non-Medicaid insurance type. Surgical procedures were associated with substantial financial hardship for working-aged adults in the US, especially after emergency surgery and among the uninsured and privately insured. The finding that Medicaid enrollees were protected against increases in financial hardship after surgical procedures suggests that policies that restrict Medicaid eligibility may increase financial hardship among working-aged surgical patients, unless other changes are made to improve financial risk protection.

To identify the Medicaid eligibility category at delivery and 6 months prior among those with Medicaid and Children's Health Insurance Program (CHIP)-financed births. Descriptive analysis of 2018 national Medicaid claims data. We used the 2018 Transformed Medicaid Statistical Information System Analytic Files to assess Medicaid/CHIP eligibility category at the time of birth and 6 months prior during pregnancy among enrollees with Medicaid/CHIP-paid births in 2018, stratifying by age, race/ethnicity, and state. Just over half (56.2%) of those enrolled in Medicaid/CHIP in 2018 were enrolled in the pregnancy eligibility category at delivery, while 29.5% were enrolled as parents, 8.2% as low-income adults, and 6.1% in other categories. The proportion of pregnant women enrolled via the pregnancy eligibility category varied widely by state, from 11.9% in Kentucky to 97.5% in Texas. Nearly half of pregnant Medicaid/CHIP enrollees were not enrolled via pregnancy Medicaid eligibility when they delivered. It is important for states to be aware of pregnancy status to apply correct eligibility criteria and benefits for pregnant and postpartum enrollees, including the 12 months of extended postpartum coverage newly available and elected in nearly all states.

Under the Consolidated Appropriations Act, 2023, which required the provision of national twelve-month continuous Medicaid eligibility for children up to age nineteen, children's Medicaid enrollment increased. After implementation of the act, states without prior twelve-month continuous eligibility showed larger gains in children's enrollment than states with prior continuous eligibility. These gains occurred during the unwinding of COVID-19 pandemic-era protections.

Substantial cancer underdiagnosis, especially early-stage cancers, occurred during the COVID-19 pandemic in the United States. Medicaid expansion under the Affordable Care Act could facilitate access to timely detection of cancer during pandemic-related financial and employment instability. This study examines the association of Medicaid expansion and changes in cancer stage at diagnosis during the COVID-19 pandemic. We compared changes in proportions of early-stage (stage I/II) cancer diagnosis in Medicaid expansion states versus non-expansion states among 1844515 individuals aged 18-64 years newly diagnosed with cancer in 2018-2022 from the National Cancer Database using a difference-in-differences (DD) approach. Adjusted DD estimates were calculated with linear probability models and stratified by key sociodemographic factors and cancer type. We found that Medicaid expansion was statistically significantly associated with smaller decreases in proportions of early-stage cancer diagnosis among individuals aged 18-44 years (DD = 1.26; 95% CI = 0.54 to 1.98), men (DD = 0.61; 95% CI = 0.08 to 1.14), and those with high comorbidity burden (Charlson-Deyo comorbidity score ≥ 2; DD = 1.51; 95% CI = 0.24 to 2.78), treated in academic facilities (DD = 0.55; 95% CI = 0.03 to 1.06), or diagnosed with prostate cancer (DD = 1.52; 95% CI = 0.56 to 2.47). Our findings suggest a protective effect of Medicaid expansion on early-stage cancer diagnoses during the COVID-19 pandemic and public health emergency in the United States, informing policy makers and the public in the 10 states that have yet to expand Medicaid eligibility. Findings can also inform policy makers and the public in all states about the public health implications of upcoming large federal cuts to Medicaid programs and coverage.

To evaluate the effects of the Family First Coronavirus Response Act (FFCRA) on work outcomes of women for whom the FFCRA effectively expanded income eligibility for Medicaid beyond 60 days postpartum by prohibiting states from redetermining Medicaid eligibility between March 2020 and March 2023. We use a difference-in-differences design that leverages the differences in income eligibility between pregnancy and non-pregnancy across states, and compares outcome changes pre-post FFCRA over these differences. Data come from the 2016-2022 American Community Survey. The sample includes 205,104 women aged 19-49 years who reported giving birth within the past 12 months in 41 states and Washington D.C. On average, the FFCRA increased postpartum Medicaid coverage by 2.8 percentage points (95% CI: 0.7-4.8) or by 9.3% relative to the 2019 Medicaid coverage rate. In contrast, the FFCRA effects on work outcomes were small and not significant: the average effect was 0.10 percentage points for labor force participation (95% CI: -1.0 to 1.2), 0.7 percentage points for employment (95% CI: -0.02 to 1.4), 0.04 h for weekly work hours (95% CI: -0.4 to 0.5), and 0.2 percentage points for full-time employment (95% CI: -1.1 to 1.5). These confidence intervals rule out an employment decline above 0.02 percentage points and full-time employment decline above 1.1 percentage points. The increase in Medicaid coverage is concentrated among states with a larger difference between pregnancy and non-pregnancy eligibility (+5.9 percentage points; 95% CI: 0.9 to 10.9) and estimates in this group also rule out relatively small declines in work outcomes. There is no evidence of declines in work outcomes following the increase in Medicaid coverage beyond 60 days postpartum that resulted from the FFCRA. The findings suggest that subsequent postpartum Medicaid coverage extensions for 12 months under the American Rescue Plan are unlikely to disincentivize work among beneficiaries.

285 Background: Digital breast tomosynthesis (DBT) has shown improved breast cancer detection over digital mammography (DM) in trials of women aged 46-69. However, its benefit of early detection for older women and its effectiveness in detecting more difficult-to-detect invasive lobular carcinomas (ILCs) remain uncertain. We hypothesized that, among women aged ≥67, DBT may detect tumors at smaller sizes and detect more ILCs compared to DM, and that these benefits would extend to women aged ≥75. We also hypothesized that DBT would detect ILCs at smaller sizes than DM. Methods: This was a retrospective SEER-Medicare cohort study of women aged ≥67 diagnosed with screen-detected ER+/HER2- breast cancer between 2015 to 2019. Screen-detected cases were identified using a validated claims-based algorithm. The primary exposure was screening modality (. The primary and secondary outcomes were tumor size at diagnosis (categorized in 10-mm intervals from 0–10 to ≥51 mm) and histology (ILC vs. other histology), respectively, and their associations with screening modality were assessed using ordinal and multivariable logistic regression. An interaction term was included to evaluate whether DBT is associated with detecting ILCs at smaller sizes. Results: Among 12,582 women, half (49.2%) received DBT at cancer detection. The majority were non-Hispanic White (82.4%), not dual eligible for Medicare and Medicaid (89.5%), and between ages 67 and 75 (55.8%). Among DBT-detected cases, 41.2% of tumors were ≤10 mm, compared to 37.8% among DM-detected cases (P &lt; 0.001). multivariable analyses, DBT was associated with 9% higher odds of detecting smaller tumors compared to DM (aOR: 1.09, CI: 1.01-1.17), but this association was not observed in women aged ≥75 (aOR: 1.01, CI: 0.91-1.13). DBT was also associated with 25% higher odds of detecting ILC compared to DM (aOR: 1.25, 95% CI: 1.12–1.39), and this association persisted among women aged ≥75 (aOR: 1.22; CI: 1.04–1.43). No significant interaction was observed between screening modality and tumor histology on tumor size. Conclusions: Our findings support the use of DBT as a routine screening modality for women aged 67-74 to improve the detection of ILCs. However, DBT did not demonstrate a significant advantage over DM in detecting smaller tumors among women aged ≥75, nor did it detect ILCs at smaller tumor sizes, which suggests that it may not facilitate earlier detection in this age group.

234 Background: Geographic and socioeconomic factors significantly influence health outcomes. The Rural-Urban Commuting Area (RUCA) codes classify U.S. census tracts by urbanization and commuting patterns. The Area Deprivation Index (ADI) measures neighborhood disadvantage based on income, education, employment, and housing. Dual eligibility for Medicare and Medicaid, along with low-income subsidy (LIS) status, indicates socioeconomic vulnerability. This study examined correlations among RUCA, ADI, and dual eligibility/LIS in patients with a cancer diagnosis receiving systemic anti-cancer therapies (SACT). Methods: We performed a retrospective, cross-sectional analysis using 6-month episodic claims data from ~2,000 patients with a cancer diagnosis with primary Medicare coverage treated with SACT across a large, multi-state, community oncology network (July 2023–June 2024). RUCA was classified as urban (1–3) or rural (4–10); ADI state rank scores were grouped into low (1–3), medium (4–6), and high (7–10) deprivation; and patients were categorized by dual eligibility/LIS status. Results: Dual eligibility/LIS: Dual eligible = 7%, LIS = 5.2%, non-dual/LIS = 87.8% RUCA: Rural = 28.4%, Urban = 71.6% ADI: High = 33.8%, Medium = 28.2%, Low = 36.1%, Unknown = 1.9% Rural patients were more likely to be dual eligible (10.2% vs. 5.8%) and live in high-deprivation areas (57.4% vs. 24.5%) compared to urban patients. High ADI was associated with greater dual eligibility (11.1%) and LIS use (8.9%) than low ADI (4% and 2.9%, respectively). However, dual eligibility alone was not a consistent indicator of deprivation. Patients in rural, high-deprivation areas had significantly higher hospitalization and emergency department visit rates (15.7% vs. 12.9%, p &lt; 0.0005) than those in urban, low-deprivation areas. Medium-deprivation patients showed more variable patterns. Conclusions: Rurality and neighborhood deprivation jointly shape healthcare access and utilization in oncology. Rural patients were more likely to live in deprived areas and require dual eligibility/LIS support, reflecting compounded structural disadvantage. However, dual eligibility alone did not reliably indicate deprivation. These findings highlight the need to integrate both RUCA and ADI in health equity research and to design targeted interventions addressing geographic and socioeconomic barriers to cancer care. Future studies should explore the domains of deprivation, such as financial toxicity and other individual social deprivation factors in the context of cancer care.

Gaps in Care Among Adolescents and Young Adults in the U.S.

196 Background: The Enhancing Oncology Model (EOM) drives health equity via increased monthly payments for dual-eligible beneficiaries, and an enhanced financial benchmark. The benchmark price includes a nearly equivalent adjustment for patients who are not dual-eligible but have Part D Low-Income Subsidy (LIS); this covers non-expansion states. However, the LIS covariate is not applied to lung and prostate cancer episodes. We explore how this methodological gap impacts practices situated in high-poverty states. Methods: We modeled a practice with 1,000 oncology episodes, a cancer type distribution of 20% lung cancer and 11% prostate cancer (observed during the EOM’s first performance period), and used CMS data on average monthly Medicaid and Medicare eligibility to calculate the share of full-dual and LIS eligible beneficiaries. We approximated the impact on episode benchmarks by multiplying these figures by the published Part D coefficients for dual-eligible and LIS status. Results: Within the 10 states with the highest estimated LIS episodes, we find that the impact of the benchmark adjustment ranges from 0.25% to 0.5% of the total episode cost - an underestimate of the true effect, given that only baseline costs are considered. Notably, most of the top ten states have a higher proportion of residents below 150% of the federal poverty level compared to the national average. Half of these states have not adopted Medicaid expansion. Conclusions: Promoting health equity is a core objective of the EOM program. However, the financial performance methodology may unintentionally penalize practices in low-income states, many of which have not expanded Medicaid - an unfortunate dual penalty. State Estimated % full dual episodes Estimated % LIS Change in the episode baseline % of all episode costs Percent below &lt;150% of Poverty Percent below &lt;150% of Poverty versus the national average Medicaid Expansion Status Connecticut 5.89% 11.25% $267,751 0.44% 15.80% -4.40% Adopted Alabama 6.72% 9.93% $239,128 0.39% 25.20% 5.00% Not adopted Mississippi 9.67% 9.68% $233,303 0.38% 30.20% 10.00% Not adopted Maine 13.07% 8.95% $216,330 0.36% 18.20% -2.00% Adopted Georgia 6.06% 8.45% $199,357 0.33% 22.10% 1.90% Not adopted Florida 9.91% 7.53% $176,559 0.29% 21.30% 1.10% Not adopted West Virginia 8.56% 6.46% $153,761 0.25% 26.30% 6.10% Adopted Tennessee 9.31% 6.16% $147,936 0.24% 22.70% 2.50% Not adopted Louisiana 7.57% 6.08% $147,936 0.24% 28.60% 8.40% Adopted New Mexico 5.94% 5.89% $147,936 0.24% 28.50% 8.30% Adopted

Venous thromboembolism following oncologic pancreas and liver surgery.

US children's health insurance is fragmented across public and private sources, with wide state variation. However, the extent of children's interactions with Medicaid and Children's Health Insurance Program (CHIP) and their experience of uninsurance over 18 years of childhood remains unclear. Such estimates can provide a baseline for gauging the potential impact of upcoming Medicaid policy changes. To estimate insurance dynamics in relation to Medicaid or CHIP and uninsurance over childhood under post-Affordable Care Act (ACA) prepandemic policy conditions. Using a microsimulation model, we projected individual-level monthly insurance coverage (Medicaid or CHIP, Marketplace, employment-based, other, or uninsured) from birth until the 18th birthday for a simulated nationally representative cohort of 100 000 US children. National data were synthesized (2015-2019), including natality records, Medical Expenditure Panel Survey pooled 2-year panels, and 1 Survey of Income and Program Participation (SIPP) 3-year panel. Monthly insurance status was simulated by matching dynamically updated predictors to SIPP samples every 12 months. Predictors included annual family income as a percentage of the federal poverty level, insurance history, state, and age. The analysis was bootstrapped 1000 times to generate 95% uncertainty intervals (95% UI). Insurance status and state of residence at birth. Cumulative insurance experience, overall and by subgroup. It was estimated that, by their 18th birthday, 61% (95% UI, 58%-63%) of US children were ever enrolled in Medicaid or CHIP and 42% (95% UI, 38%-46%) were ever uninsured. An estimated 26% (95% UI, 24%-29%) of children were continuously enrolled in employment-based or other insurance excluding Medicaid, CHIP, or Marketplace. Among children born with Medicaid or CHIP, the share ever uninsured was 59% (95% UI, 48%-66%) in ACA nonexpansion states vs 36% (95% UI, 30%-41%) in expansion states. Across alternative categorizations of policy restrictiveness, the highest share of ever uninsured among children born with Medicaid or CHIP was consistently estimated in states with the most restrictive Medicaid and CHIP eligibility criteria. An estimated 3 of 4 US children relied on publicly subsidized insurance (Medicaid, CHIP, or Marketplace) or experienced a period without any insurance by their 18th birthday in the post-ACA, prepandemic policy environment. Substantial state heterogeneity in childhood uninsurance underscores the critical role of Medicaid policies.

The Comparative Toxicity of Focal Ablation Versus Intensity Modulated Radiation Therapy for Prostate Cancer.

The evolving impact of Medicaid expansion on suicide mortality: demographic and method-specific effects.

The Inventory for Client and Agency Planning (ICAP) and the Supports Intensity Scale (SIS) have been used to determine Medicaid eligibility for individuals with disabilities but are designed to capture different information. This project explored how these surveys relate to services received and each other. ICAP and SIS surveys were conducted on 125 Wyoming adults with intellectual and developmental disabilities eligible for a Medicaid Waiver. Results suggest that both measures were strongly associated and could be used to predict services. However, this study suggests that the SIS and ICAP summary measures were separate constructs. Therefore, both instruments can be used to determine Medicaid eligibility, but implementers should be aware of differences in the types of constructs being captured.

Abstract Introduction: Remarkable progress in the survival of childhood cancer comes at a significant cost with late therapy-associated toxicities. Late effects of treatment include chronic health conditions and subsequent malignant neoplasms, which vary by original cancer diagnosis and treatment received. While key factors impacting long-term survivorship health outcomes have been identified, there remains a gap in understanding healthcare utilization within the first few years after cancer diagnosis. Methods: We conducted a retrospective cohort study to assess the relationship between risk stratification for late effects of cancer and both emergency department visits and subsequent hospitalizations, occurring 3-10 years after the cancer diagnosis. We identified cancer survivors from the University of Oklahoma (OU) Health cancer registry and linked with claims data from the Oklahoma Health Care Authority (OHCA), which maintains data for the state’s Medicaid program. We included survivors diagnosed with cancer between 2010 and 2017 who were aged 0-29 years at the time of diagnosis. We used modified Poisson regression to estimate risk ratios (RR) and 95% confidence intervals (CI) to account for potential confounding factors. Results: We identified 494 survivors that linked with an OHCA claims record. Approximately half of survivors were female (51%) and a child at diagnosis (49% compared to adolescent [16%] or young adult [35%]). Nearly half of survivors were at intermediate risk of late effects (49%), followed by low risk (35%), and high risk (13%). In our multivariable models, we found no association between risk stratification and hospitalizations (High risk RR: 1.08, 95% CI: 0.53, 2.20; Intermediate risk RR: 1.31, 95% CI: 0.82, 2.08 compared to low risk) or emergency department visits (High risk RR: 0.95, 95% CI: 0.68, 1.34; Intermediate risk RR: 0.97, 95% CI: 0.77, 1.22, compared to low risk). Discussion: We observed no significant differences in acute healthcare utilization among cancer survivors within 3-10 years after their cancer diagnosis. However, we were unable to measure healthcare utilization during periods when survivors were not covered by Medicaid, which may be particularly challenging for survivors transitioning into adulthood as eligibility for Medicaid requires lower income than during childhood. Citation Format: Amanda Janitz, Kamryn Ford, Talayeh Razzaghi, David Noyd. Risk of late effects and acute care utilization among childhood, adolescent, and young adult cancer survivors with Medicaid coverage [abstract]. In: Proceedings of the 18th AACR Conference on the Science of Cancer Health Disparities; 2025 Sep 18-21; Baltimore, MD. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2025;34(9 Suppl):Abstract nr B125.