Journal of Medical Economics

Multi-Cancer Detection (MCD) tests can detect more than 50 different types of cancer using a blood test. Recently passed law in the U.S. guarantees that Medicare will pay for these tests when they are FDA approved and show evidence for clinical benefit. This manuscript provides estimates of the cost of MCD tests to Medicare under different assumptions of cost per test, eligibility, and screening uptake in the eligible population. This manuscript additionally estimates the cost of follow-up testing resulting from false positive results, which are considered avoidable costs caused by the screening test.

Introduction Respiratory syncytial virus (RSV) is an important cause of respiratory disease in older adults and adults with chronic medical conditions, contributing substantially to the healthcare burden in Italy. The availability of effective RSV vaccines provides an opportunity to reduce RSV-related morbidity, mortality, and healthcare costs in populations at high risk of severe disease. This study evaluates the potential public health impact and cost-effectiveness of vaccination using mRNA-1345 administered as a single dose compared with no vaccination in Italian high-risk adults aged 60-74 years and all adults aged [≥]75 years. Methods A static decision-analytic model was developed to project clinical and economic outcomes over a 5-year time horizon. Economic outcomes were evaluated from the Italian National Health Service (Servizio Sanitario Nazionale, SSN) perspective. Model inputs were informed by the most recent Italian epidemiological, clinical, and economic evidence, supplemented by published international data when necessary. Deterministic, probabilistic, and scenario analyses were conducted to assess the impact of uncertainty in model inputs and assumptions on the study results. Results Vaccination with mRNA-1345 in high-risk adults aged 60-74 years and all adults aged [≥]75 years was projected to avert over 19,800 hospitalizations, 4,000 emergency department visits, 381,000 outpatient visits, 6,000 RSV-attributable deaths, and 212,000 antibiotic prescriptions compared with no vaccination over a 5-year period. The total incremental cost of {euro}1,143 million and the additional 47,477 QALYs gained resulted in an ICER of {euro}24,078, which was below the commonly referenced willingness to-pay range of {euro}33,000-40,000 per QALY gained. Sensitivity analyses confirmed robustness of the analysis results. Conclusions Vaccination with mRNA-1345 is a cost-effective strategy for the prevention of RSV in high-risk adults aged 60-74 years and all adults [≥]75 years in Italy and has the potential to provide substantial public health benefits.

Context: To ensure healthy resettlement and protect US health security, the Vaccination Program for US-bound Refugees (VPR) offers some recommended vaccines to refugees overseas before resettlement to the United States. The selected vaccines and number of doses vary by country of departure. VPR was found to be cost-saving in 2018 but had since expanded to more sites. Objective: Assess VPR's current costs and impact on post-arrival domestic vaccination needs and costs. Setting and Participants: A model-based analysis of the Federal government costs for VPR and post-arrival (US) vaccination of resettled refugees separated across five regions: Africa, Asia, the Middle East and North Africa/Republic of Turkiye and Middle East, Europe, and the Americas using fiscal year 2024 data. Design: We quantified and compared full vaccination costs for refugees under two scenarios: (1) 'No VPR' and (2) 'VPR'. Refugees would receive no vaccines overseas and be fully vaccinated after US arrival under 'No VPR'. Under 'VPR', refugees receive one or two doses of selected vaccines overseas before completing vaccination schedules after arrival. Main Outcomes: Costs were reported in 2023 US dollars for 'VPR' and 'No VPR' scenarios and further subdivided by grouping countries/sites depending on whether the International Organization for Migration (IOM) provides vaccination services for refugees (IOM sites) versus non-IOM providers (non-IOM sites). Results: 'VPR' resulted in average net cost savings of $147 per person or $14.7 million per 100,000-refugee cohort compared to providing all vaccines after US arrival ('No VPR'). 'VPR' was cost-saving across most regions, except for IOM sites in Europe, where a net cost of $44 per person was observed. Net cost savings per person were highest for IOM sites in Africa ($333). Conclusions: VPR remains a cost-saving strategy, while protecting US-bound refugees' health and US health security by preventing disease outbreaks during resettlement.

Background. Evidence of the effectiveness and cost-effectiveness of new vaccines that reduce the burden of respiratory syncytial virus (RSV) in older populations is emerging. The reported cost-effectiveness of these vaccination strategies varies substantially across different settings. This study assessed the cost-effectiveness of older adult-targeted RSV vaccination strategies in the Australian context and compared findings with published evaluations. Methods. We developed an individual-based dynamic transmission model of RSV infection, linked to a clinical pathways and cost-effectiveness model. We modelled different adult vaccination strategies for the general population and the Indigenous population, and present incremental cost-effectiveness ratios (ICERs) as cost per quality-adjusted life year gained, from a healthcare system perspective. Deterministic and probabilistic sensitivity analyses explored drivers of cost-effectiveness and sensitivity of findings to uncertainty in parameter estimates. Results. Vaccinating the general population of older adults in Australia was not found to be cost-effective at a dose price of 100 AUD, but was found to be cost-saving for Indigenous adults, given the higher disease burden in this population. Individual drivers of ICERs in our setting were dose price, hospitalisation incidence and mortality, however conclusions about cost-effectiveness were robust to joint parameter uncertainty. Conclusions. The cost-effectiveness of vaccinating adults against RSV depends on many uncertain and context-specific quantities. Strategies that target high risk populations were found to be cost-effective in Australia due to the larger avertable burden.

Background and Aims Barrett's esophagus (BE) is the principal precursor of esophageal adenocarcinoma (EAC), whose incidence has risen sharply in Western countries since the 1960s. Effective, dysplasia stratified surveillance strategies are needed to prevent progression. This study evaluated the cost effectiveness of dysplasia stratified surveillance intervals and endoscopic eradication therapy (EET) across the BE spectrum. Methods We developed an incidence-based Markov state transition model of BE progression calibrated to U.S. epidemiologic data from a healthcare sector perspective over a lifetime horizon. Four hypothetical cohorts of 50-year-old individuals with short segment BE (SSBE), nondysplastic BE (NDBE), low grade dysplasia (LGD), or high-grade dysplasia (HGD) were evaluated. Strategies included no surveillance; surveillance at 1-, 2-, 3-, 4-, 5-, or 10-year intervals; standard or AI assisted endoscopy; non endoscopic screening (sponge, breath, miRNA tests); and EET for LGD and HGD. Outcomes included costs, quality adjusted life years (QALYs), incremental cost effectiveness ratios (ICERs), net monetary benefits (NMBs), EAC cases, and EAC-related deaths. Sensitivity analyses used a willingness to pay threshold of US$100,000 per QALY. Results No surveillance was the most cost-effective strategy for SSBE and NDBE. For LGD, upfront EET was more cost effective than all surveillance strategies, with results sensitive to EAC incidence and recurrence. For HGD, EET was cost saving and yielded the greatest QALYs, with findings robust in 99.9% of simulations. EET prevented 12,614 and 44,295 EAC related deaths per 100,000 individuals with LGD and HGD, respectively. Conclusion Dysplasia-stratified management is essential for optimizing surveillance and treatment strategies in BE. Any degree of dysplasia should receive EET followed by targeted post-treatment monitoring, establishing EET as the central therapeutic pathway for dysplastic BE.

Objective: To determine whether and to what extent hospitals across the United States vary in their use of late-preterm steroids using a novel data set in which the timing of steroid administration relative to delivery can be observed. Methods: This was a retrospective cohort study of singleton births with known gestational ages identified in the Premier Healthcare Database from 2015 to 2022. The primary variable of interest was hospital-level adoption of antenatal corticosteroids for late-preterm singleton deliveries, calculated as the proportion of late-preterm singleton births (34-36 completed weeks of gestation) with any betamethasone exposure during the same late-preterm period. Hospital adoption was defined as the weighted average rate of ALPS administration among late-preterm infants across the entire post-period. Hospitals were ranked by their late-preterm steroid adoption rates and categorized by quartile based on the empirical distribution. Temporal trends were assessed using annual hospital-level adoption rates and visualized using time-series plots and distributional plots. A logistic regression model was constructed to determine hospital characteristics associated with being a highest-quartile adopting hospital. Results: The analysis cohort included 728 hospitals and 5,452,791 births, of which 361,006 (6.6%) were singleton late preterm births. Hospital steroid exposure rates ranged from 0 to 82% and were categorized into quartiles based on overall exposure rate, with cutoffs at 20.6%, 29.8%, and 40.1%. Median exposure rates increased progressively across quartiles from 14.1% (IQR 9.3-17.4%) in the lowest adopting hospitals (Q1) to 47.6% (IQR 43.7-53.2%) in the highest adopting hospitals (Q4), with substantial within-quartile variation. In the multivariable model, urban location was a strong predictor of high adoption after adjustment (aOR 2.05; 95% CI 1.11-3.83, p=0.02). Compared to Midwest hospitals, Southern hospitals had significantly lower odds of being high adopters (aOR 0.37; 95% CI 0.20-0.69, p<0.01). Among clinical case mix variables, a higher proportion of late preterm births at 34 weeks' gestation was strongly associated with high adoption (aOR 2.21; 95% CI 1.58-3.14, p<0.001). Conclusion: Following publication of the ALPS Trial, there was heterogeneous adoption of late preterm steroids among US hospitals. These findings highlight the need for a more in-depth exploration of local factors that drive the adoption of evidence-based practices outside of observable hospital characteristics.

Across 30 US states and the District of Columbia, eliminating the AIDS Drug Assistance Program is projected to save $6.45 billion in direct costs while generating $14.89 billion in downstream HIV care costs attributable to excess incident infections from 2026-2035. Costs are projected to surpass savings within six years.

Objective: To develop and externally validate a simple antepartum cumulative risk score that stratifies both vaginal birth after cesarean (VBAC) success and neonatal morbidity among patients undergoing trial of labor after cesarean (TOLAC). Methods: This retrospective cohort study was conducted in 2 stages: model development in a single tertiary care center in California (2019 to 2025) and external validation in the National Vital Statistics System natality files (2020 to 2024). The derivation cohort included 1,418 TOLAC attempts; the national validation cohort included 477,693 TOLAC attempts. A point-based score was constructed from routinely available antepartum characteristics associated with VBAC. VBAC success and neonatal intensive care unit (NICU) admission were evaluated across score levels in both cohorts, and model discrimination was assessed using area under the receiver operating characteristic curve (AUC). Results: In the derivation cohort, 1,087 of 1,418 patients (76.7%) achieved VBAC. The logistic regression model showed reasonable discrimination (AUC 0.70, 95% CI 0.67-0.73). VBAC success declined from 89.1% at a score of -1 to 37.8% at scores of 4 or higher, whereas NICU admission increased from 31.7 to 200.0 per 1,000. Uterine rupture occurred in 28 of 1,418 TOLAC attempts (1.97%) and was not predicted by antepartum characteristics. In the national cohort, VBAC success similarly declined from 90.5% to 44.8%, whereas NICU admission increased from 43.8 to 111.1 per 1,000 across the same score range. Conclusion: A simple antepartum risk score stratified both VBAC success and neonatal morbidity in single-center and national TOLAC cohorts, supporting its potential use in patient-centered counseling.

Background: Continuous glucose monitoring (CGM) improves glycaemic control in people with type 1 diabetes (T1D), but high costs limit uptake in low- and middle-income (LMIC) countries. Evidence on the cost-effectiveness of CGM is limited in LMIC settings. Objective: To evaluate the short- and long-term cost-effectiveness of intermittently-scanned continuous CGM (cCGM) and intermittently-scanned periodic CGM (pCGM) (one sensor every three months), versus standard self-monitoring of blood glucose (SMBG) in the South African public-sector. Methods: A three-arm randomised controlled trial (ACCEDE) was conducted among T1D individuals with HbA1c [&ge;]10% in South Africa. A within-trial cost-effectiveness analysis was conducted from a partial societal perspective over 9-months, using resource use data and QALYs derived from EQ-5D. A cost-utility analysis using a Markov microsimulation model was conducted for two populations: total T1D, and youth (<20 years). Results: Within-trial analysis showed no statistically significant differences in QALYs or HbA1c between arms. Costs were highest for cCGM (USD 1,504), followed by pCGM (USD 742) and SMBG (USD 467). CGM strategies were dominated in the within-trial analysis. In contrast, long-term modelling showed that CGM was more effective than SMBG and was cost-effective for youth when used periodically. cCGM delivered additional QALYs at a higher cost (ICERs USD 15,259-30,852/QALY) and was only potentially cost-effective in youth when sensor prices were reduced by >45%. Conclusions: While CGM was not cost-effective in the short term, modelling suggests pCGM use may offer value-for-money under specific assumptions and in select populations, highlighting the need for further evidence on long-term effectiveness, engagement, and pricing.

Introduction Care home (CH) influenza vaccination of staff improves resident health, yet uptake remains low at just over 11% (England, 2025/2026). We report an economic evaluation (EE) of "FluCare", an intervention to increase staff influenza vaccination through: vaccination clinics at CHs; promotional materials; and CH financial incentives. Method Seventy-five CHs were randomised to FluCare or control. A cost-consequence analysis took the influenza vaccination programme funder perspective, but also extended to the National Health Service (NHS) and CH perspective. Costs included: influenza vaccination; administration fee; FluCare components; CH resident NHS utilisation. Outcomes were: staff influenza vaccination rates; staff sickness; and resident mortality. Sensitivity analyses excluded intervention CHs that did not host vaccination clinics. Results Compared to control CHs, adjusted analysis found intervention homes with a mean absolute increase in vaccination rates of 1.8% (95% CI: -6.0%, 10.8%; p=0.572) at an increased cost of {pound}451 (95% CI: {pound}239, {pound}675; p<0.001) to the vaccination programme funders: {pound}249 per additional percentage point (PAPP) per CH. Vaccination clinics were delivered late in the influenza season, with 80% taking place from February 2023. Including only intervention CHs that hosted staff flu vaccination clinics (23/35), increases the mean difference to 10.1% (95% CI: 0.9%, 21.9%; p=0.018) and costs to {pound}805 (95% CI: {pound}603, {pound}1,079; p<0.001): {pound}79 PAPP per CH. Differences between trial arms in other costs and outcomes were marginal and generally non-significant. Conclusions FluCare delivered little improvement when staff flu vaccination clinics did not occur and had little impact on other costs/outcomes. Cost-effectiveness depends on willingness-to-pay for increased staff vaccination, but cost PAPP per CH improved from {pound}249 to {pound}79 when only CHs hosting clinics were considered. Late implementation, likely reduced impact by limiting clinic delivery, as reflected in sensitivity analysis. Future evaluations should implement FluCare earlier in the season.

Background: North Carolina Medicaid implemented the Pregnancy Medical Home program to improve access to high-quality maternity care and reduce the risk of adverse perinatal outcomes. Program recipients receive a prenatal risk screening form, originally intended to identify those at high risk of preterm birth and low birth weight, that includes an assessment of social and clinical factors. While prior studies have evaluated whether risk screening can identify pregnancies with higher risk of adverse neonatal outcomes, less is known about the relationship between programmatic risk-stratification and adverse maternal outcomes. Objective: To assess the use of a prenatal risk screen among pregnant Medicaid beneficiaries to identify those at risk of an adverse maternal event. Study design: Linked Medicaid hospital claims, live birth records, and risk screen data from the Pregnancy Medical Home program were used to identify risk factors for adverse maternal events among individuals who gave birth to a liveborn infant in North Carolina between 2014 and 2019. Only those with completed risk screens (75%) were included in the analysis. We used random forest classification to select variables for a multivariable prediction model. We used Poisson regression to model the association between adverse maternal events and selected demographic, psychosocial, clinical, and historical pregnancy characteristics. Adverse maternal events occurring at birth and up to six weeks postpartum included severe maternal morbidity, maternal intensive care unit admission, prolonged birth hospitalization, and postpartum readmissions. Results: A total of 205,916 births met inclusion criteria for this analysis. During the study period, 3.0% of Medicaid beneficiaries had an adverse maternal event occurring between birth and up to six weeks postpartum, including, 0.6% with severe maternal morbidity, 0.9% with an intensive care unit admission at birth, and 1.5% with a prolonged birth hospitalization or postpartum readmission. Maternal age greater than 25 years, Black race, being overweight or obese, smoking, chronic diseases (diabetes, hypertension, mental illness), and pregnancy history characteristics (nulliparity, history of preterm birth, history of hypertensive disorders of pregnancy or gestational diabetes) were associated with an increased risk of adverse maternal events. Modeled together, however, risk factors from the risk form were poorly predictive of the composite outcome. The final model had an Area Under the Curve (AUC) of 0.63 with an optimal sensitivity of 56% and specificity of 63%. Conclusion: Care management during pregnancy is an increasingly relevant topic in public health and prenatal care in the United States. The North Carolina Pregnancy Medical Home is a long-standing and robust Medicaid program that can serve as a model for design and implementation. While this program has effectively designed risk-stratification to identify pregnant people at risk of poor neonatal outcomes who benefit from care management, the risk screen poorly identifies pregnant people at risk of adverse maternal outcomes. Care coordination programs are often designed to optimize neonatal outcomes, and this study highlights the need to center and balance maternal health along with neonatal outcomes to address the needs of a very vulnerable population.

Introduction: Maternal morbidity and mortality in the US disproportionately affect some women, including the Medicaid-insured, rural, and Black, Hispanic, and Native American populations. The drivers of disparities are complex and there is an urgent need for multilevel interventions focused on pregnancy-related and associated morbidity and mortality (PRAMM). This study will be the first large-scale test of Community Health Worker (CHW) inclusive home visiting and provider/practice/system level improvement strategies that support empowered patients, pro-active providers, and integrates community and clinical care designed to reduce PRAMM and disparities among women who are disproportionately affected. Methods and analysis: The primary study outcome will be rates of PRAMM - a composite outcome including pregnancy-associated and pregnancy-related morbidity, severe maternal morbidity, and mortality - and disparities among women disproportionately affected. A quasi-experimental, stepped wedge design will be used. Participants will be Medicaid-insured women in three Michigan counties observed during pregnancy, at birth, and up to one year postpartum, who give birth between 2021-2028 (>101,000 births). Individual health outcomes will be assessed at three steps of the stepped-wedge design. Analyses will use a statewide linked data system including all Medicaid birth and death records, Medicaid claims, and other program data. In the context of Michigan extending pregnancy-related Medicaid, the study will evaluate the impact of the proposed multilevel intervention vs. usual care from early pregnancy through 12 months postpartum. The study was developed with full community engagement and participation including shared leadership with academic and community-based Principal Investigators representing intervention communities. Ethics and dissemination: An Institutional Review Board determined the study exempt from the human subject's regulations, for the following reasons. Two of the three intervention components will not interact with human subjects to collect data - we will only rely on secondary research using data or biospecimens not collected specifically for this study, and the data will be provided without identifiable information by someone without any role in this research study except providing the data. The third intervention component, medical provider surveys, is a benign behavioral intervention where information will be recorded using methods that prevent subjects' identities from being readily ascertained. Results will be published in peer-reviewed journals following EQUATOR guidelines.

Importance: The 2026 public charge rule could discourage immigrants from accessing health coverage programs, creating a chilling effect that potentially leads to negative health outcomes; However, its long-term health impact is poorly understood. Objective: To model potential impacts of the 2026 public charge rule on primary care and premature mortality among immigrants in New York City (NYC). Design, Setting, and Participants: The simulation used a deterministic compartmental model with Ordinary Differential Equations (ODEs) using 2023 NYC Vital statistics data and American Community Survey, and estimates obtained from 2 previous studies about effects of healthcare access on primary care and Medicaid expansion on premature mortality. Main Outcomes and Measures: Rates of primary care outcomes (access, doctor's visits) in 5 years, and premature mortality in 5 and 20 years, projected by the model under conservative, moderate, and aggressive scenarios of avoidance/disenrollment due to the public charge rule, known as the 'chilling effect'. Effects of the avoidance/disenrollment on primary care outcomes and premature mortality were obtained from 2 previous studies. Projected rates of the outcomes under each scenario were compared with counterfactuals to estimate the health impacts of the chilling effect. Results: Implementation of the public charge rule was projected to decrease the primary care access rate by 4.1% (conservative) to 9.9% (aggressive) over 5 years, relative to the counterfactual scenario without the rule. The rate of doctors' visits was projected to decrease over 5 years by 5.1% (conservative) to 12.2% (aggressive). Premature mortality was projected to increase by 4.4% (conservative) to 10.6% (aggressive) in 5 years and 7.4% (conservative) to 17.4% (aggressive) in 20 years. Legal noncitizens and Black immigrant New Yorkers were predicted to experience higher burdens of premature mortality attributed to the chilling effect, compared with other immigrant groups and racial/ethnic groups, respectively. Conclusions and Relevance: This study demonstrates adverse health consequences of federal public charge rule changes among immigrants in NYC. The model projected a decrease in primary care visits and increase in premature mortality across various scenarios. These findings suggest urgent reconsideration of a regulatory change that disproportionately increases risk of premature mortality among immigrants in NYC.

Introduction: Preeclampsia (PE) is a leading cause of maternal and neonatal morbidity and mortality, and low-dose aspirin (LDA) prophylaxis is the cornerstone of evidence-based prevention. Despite guideline recommendations, LDA adherence remains poor, with 10-25% of moderate-risk patients taking aspirin. Objective personalized risk stratification using biomarkers has been shown to motivate behavior change in other disease contexts. Survey data suggest that patients are more motivated to take aspirin if informed by an objective predictive test. Here, we report real-world LDA adherence among patients who received a high-risk result from a cell-free RNA (cfRNA) PE risk prediction test. Methods: This retrospective, observational survey study included asymptomatic patients of advanced maternal age (AMA; [&ge;] 35 years at delivery) with singleton pregnancies without USPSTF-defined preexisting high-risk conditions for PE who received the cfRNA PE risk prediction test. Patients who opted in to receive text message surveys were asked about LDA use following receipt of test results. High adherence was defined as reporting LDA use on at least 6 of 7 days per week at least 85% of the time surveyed. The primary analysis included patients with a high-risk test result and at least one LDA frequency survey response following receipt of test result. The observed proportion of adherent patients was compared to a baseline estimate of 25% using an exact binomial test. Results: Of 166 patients who received a cfRNA PE risk prediction test result, 48 (28.9%) received a high-risk result. Of these, 29 (60%) opted in and responded to at least one survey, constituting the primary analysis population. Twenty-seven of the 29 (93.1%; 95% CI: 78.0-98.1%) were classified as highly adherent, significantly higher than the 25% baseline adherence estimate for moderate-risk patients (p < 0.0001). Conclusion: Among surveyed patients who received a high-risk cfRNA PE test result, the proportion classified as highly adherent to LDA (93%) substantially exceeded published estimates of adherence in a similar patient population and met the clinically meaningful threshold of [&ge;] 80% associated with reduced risk of preterm preeclampsia. These findings indicate that objective and personalized biomarker risk testing may be a powerful driver of behavior change that current guidelines have failed to produce.

Improving primary care is a long-standing strategy to constrain health care spending. Yet, evaluations of primary care models focused on payment reform have shown minimal effects on total cost of care. We report the results from a large-scale, real-world evaluation of an advanced primary care model that restructures access through same-day and next-day appointments, on-demand video visits, asynchronous clinician messaging, and extended hours. Using a stacked-cohort difference-in-differences design with entropy balancing and inverse probability of censoring weighting, we analyzed multi-payer claims covering April 2022 through March 2025. Advanced primary care use was associated with an 8.6% reduction in total cost of care (-$729 per patient per year; P = 0.004), driven by lower specialist cost (-$939/year; P < 0.001) and, to a lesser degree, by reductions in inpatient (-$134/year; P < 0.001), urgent care (-$70/year; P < 0.001), and emergency department cost (-$16/year; P = 0.02), partially offset by higher primary care cost (+$350/year; P < 0.001). The specialist reduction was concentrated in knowledge-based consultative encounters (-$663/year; P < 0.001), while procedural specialist cost was largely unchanged (-$276/year; P = 0.09). Cost differences emerged in the first post-index month. These findings suggest that advanced primary care may reduce total health care spending, with observed savings driven primarily by lower spending on consultative specialty care.

FeePredict is a three-stage random forest machine learning framework to simul-taneously predict whether Medicare reimbursement rates for specific procedures will change, in which direction they will change, and by how much. FeePredict was ap-plied to the four major Medicare fee schedules: the Clinical Laboratory Fee Schedule (CLFS), the Physician Fee Schedule (PFS), the Ambulance Fee Schedule (AFS), and the Durable Medical Equipment, Prosthetics, Orthotics, and Supplies (DMEPOS) fee schedule. Each of these fee schedules contains publicly available data from the Centers for Medicare & Medicaid Services (CMS) for the years 2024, 2025, and 2026, with the number of procedures represented in the data ranging from 3,264 to 2,952,842 observations.FeePredict utilizes lag-1 feature engineering and train-only preprocessing steps to ensure that there is no data leakage into the model. Chronological out-of-time valida-tion was performed on three of the four fee schedules to determine the generalizability of the model over time. FeePredict significantly outperformed the assumption that there would be no changes to Medicare reimbursement rates for procedures (p < 0.001), achieving concordance indices between 0.815 and 0.998, and reducing the mean abso-lute error for predicting changes to reimbursement rates by 29% to 85%. Permutation testing of the model with shuffled reimbursement rate labels indi-cates that there is no evidence of data leakage (AUC values: 0.467-0.515). The model achieved concordance indices of 0.854 and 0.972 for the CLFS and DMEPOS fee sched-ules, respectively, outside of its training period, but performed less well outside of its training period for the PFS, indicating that it generalizes less well to changes to the Medicare policy regime that existed after its training period. Overall, though, these re-sults indicate that it is possible to accurately predict whether Medicare reimbursement rates for medical procedures will change using only data from the historical versions of those fee schedules.

The US spends more on health care than any other nation, yet tens of millions of Americans are uninsured or underinsured, and coverage retractions enacted in 2025 are widening these gaps. The misalignment between the for-profit insurance architecture and optimal patient care, together with the inefficiencies of a fragmented system, contributes to both unnecessary costs and preventable mortality. We update our previous analyses with the most recent data to project the economic benefits and the number of lives saved that would be achieved by single-payer universal coverage, as proposed in the Medicare for All Act. We estimate that such a system would reduce national health expenditure by $1,041 billion annually. Sources of savings include reductions in administrative overhead, pharmaceutical prices, fraudulent billing, and avoidable emergency care. Combined with the reversal of recent retractions, universal coverage would save over 114,000 lives annually.

To evaluate the cost-utility and 5-year budget impact of first-line olaparib plus abiraterone versus abiraterone alone for metastatic castration-resistant prostate cancer (mCRPC) in China after the eleventh round of volume-based procurement (VBP). The intention-to-treat (ITT) population was assigned primary decision-analytic weight; the prespecified BRCA1/2-mutated (BRCAm) subgroup was a supporting analysis.

Drug shortages represent persistent supply disruptions in the U.S. pharmaceutical market, threatening patient access and increasing drug costs. Prior research commonly treats shortages as binary events and relies on static designs, limiting insight into how shortage characteristics drive cost escalation. This study uncovers the heterogeneity behind drug shortages and pharmacy acquisition costs of generic non-injectable drugs. FDA drug shortage records with weekly National Average Drug Acquisition Cost (NADAC) prices were fit with fixed-effects models, duration-specific models, and a double machine-learning framework to characterize heterogeneity in shortage-price associations by duration, market structure, and shortage reasons. In the baseline two-way fixed-effects model, active shortage designation alone was not associated with a significant increase in NADAC under clustered standard errors. In duration-specific models, shortages lasting more than four consecutive weeks were associated with approximately 7% higher NADAC, while each additional cumulative shortage week was associated with approximately 0.37% higher NADAC. Estimated CATEs varied widely across drugs in each week. Allocation restrictions, raw material and distribution disruptions, together with a lack of manufacturers, characterized shortages with higher estimated CATEs. These findings support monitoring both shortage persistence and supply-chain mechanisms to mitigate impacts on healthcare systems.

Introduction: Research has documented that obesity and morbidity are associated. Black persons in the United States (U.S.) incur higher financial costs of obesity-related multimorbidity (ORM). However, lifetime healthcare costs (LHCs) remain underexamined for these populations. Objective: We quantified racial differences in 1) LHCs and 2) lifetime healthcare cost differential (LCD) associated with ORM for ages > 40 years. Methods: We used the 2008- 2012 Medical Expenditure Panel Survey Household Component to examine unique obesity-related diseases (ORDs): high blood sugar, hypertension, coronary heart disease, and stroke. We used a prior published Markov model to simulate a person's life history of ORDs and compute LHCs among ages > 40 years. We computed LCD-associated ORM as the difference in LHC for those with ORM and LHC for members without ORDs. We quantified differences in race as the difference between LHC or LCD among White and Black men and women. Results: Our analytic sample included 53,035 Black and White persons representing 97,229,611 (S.E., 2,104,365), 12.4% as Black and 87.6% as White persons. ORM was more prevalent in the Black (21.2%) than the White group (13.4%). LHCs by race (Black/White) for women/men with ORM and LCDs associated with ORM (2012$) were $3 1,035/43,595 and $11,350/26,948 for age 40-49, $2 1,567/25,6 115 and $3,846/9,808 for 50-59, $9,863/18,515 and -$2,566/7,426 for 60-69, -$8,220/16,285 and -$11,524/3,865 for 70-79. Conclusions: Racial Differences in LHCs and LCDs related to ORM persist and vary across subpopulations. Future interventions designed to prevent/manage ORM are crucial for prioritizing populations with high LHCs and advancing health equity.