Hung, Anna, and Timothy S Anderson. (2026) 2026. “Cost-Related Medication Nonadherence Before and After the 2024 Inflation Reduction Act Provisions.”. JAMA Internal Medicine. https://doi.org/10.1001/jamainternmed.2026.0021.
Publications
2026
Bhat, Shamik, Devika A Shenoy, Magda Wojtara, Alissa Kainrath, Oak Sonfist, Jantzen Faulkner, Brianna Wang, Linnea Wilson, and Timothy S Anderson. (2026) 2026. “Changes in U.S. Medical School Conflict of Interest Policies from 2014 to 2023.”. PloS One 21 (3): e0344046. https://doi.org/10.1371/journal.pone.0344046.
BACKGROUND: Concerns about the influence of the pharmaceutical industry on medical education, ranging from education of students to professional development, have led professional societies to recommend regulation of interactions between industry and medical schools. The objective of this study was to evaluate conflict of interest (COI) policies at medical schools in 2023 compared to 2014.
METHODS: This study used a cross-sectional design to evaluate the COI policies at the top 30 medical schools identified by US News and World Report rankings. The authors collected policies by survey and review of public websites, and assessed their quality across 15 domains informed by guidelines published by leading national organizations and previous PharmFree Scorecards. Each domain was graded on a 3-level scale derived from professional organization guidelines, which when totaled corresponded to the following letter grades: an "A" (score 38-45), "B" (32-37), "C" (25-31), and "I/F" (< 25). This study assessed industry payments to school leadership using the 2023 Open Payments database.
RESULTS: Eleven of thirty medical schools submitted COI policies, and the remainder were analyzed based on publicly available information. No school received an "A," 22 (73.3%) schools received a "B", 6 (20.0%) schools received a "C", and 2 (6.7%) schools received an "I/F". Most schools had model policies around COI enforcement (29/30, 96.7%), gift acceptance (25/30, 83.3%), and ghostwriting (24/30, 80.0%). No schools had model policies in limiting direct faculty payments. When comparing 2014 and 2023 Scorecards over the shared 14 domains, 14 (46.7%) schools had a decrease in score, 11 (36.7%) schools had an increase, and 5 (16.7%) schools had no change. Faculty at every school accepted industry payments, including 20 (16.7%) deans and 52 (19.3%) of clerkship directors.
CONCLUSIONS: Medical school COI policies remain less stringent than consensus recommendations; thus, renewed attention to policies and implementation is needed to ensure bias-free medical education.
Li, Jinhong, Julie M Donohue, and Lu Tang. (2026) 2026. “Distributed Fusion R-Learner of Heterogeneous Treatment Effect Using Distributed Medicaid Data.”. Biometrics 82 (1). https://doi.org/10.1093/biomtc/ujag034.
Interest in data-driven decision-making has stimulated method developments in estimating heterogeneous treatment effect. In practice, accurately estimating a conditional average treatment effect (CATE) requires a large sample, which is often realized by data integration that leverages information from multiple data sites. This paper attempts to address two challenges involved in such task, treatment effect heterogeneity and privacy protection. The first pertains to differences in the CATE coefficient across sites due to heterogeneity in treatment effect; the second pertains to barriers in sharing sensitive data across sites. We propose a distributed fusion learning approach, DF $R$-learner, to jointly estimate CATE across sites without pooling individual-participant data. It allows the CATE functions to differ and uses a data-driven fusion penalty to combine similar parameters across sites in achieving improved estimation. The estimator uses confidence distributions to facilitate efficiency and private information exchange, which we show theoretically and empirically no loss of efficiency compared to its counterpart based on centralized data. We examine DF $R$-learner through a study of medication treatment for opioid use disorder using distributed Medicaid data from multiple managed care organizations within the state of Pennsylvania.
Hartung, Daniel M, Nico Gabriel, Walid F Gellad, Teresa Cameron, Noah M Feder, and Inmaculada Hernandez. (2026) 2026. “Changes in List and Net Prices for Multiple Sclerosis Disease-Modifying Therapy, 2013 to 2021.”. Neurology. Clinical Practice 16 (2): e200597. https://doi.org/10.1212/CPJ.0000000000200597.
OBJECTIVES: The objective of this study was to evaluate changes in net and list prices of branded multiple sclerosis (MS) disease-modifying therapies (DMTs) between 2013 and 2021.
METHODS: Using several pharmaceutical pricing and utilization data sources, we estimated list and net (after rebates and discounts) prices for branded monoclonal antibody (MAb) and oral DMTs. We calculated the inflation-adjusted list and net prices for each DMT, the manufacturer discount as a percentage of list price, the average annual change (AAC) in prices, and the cumulative change in list price offset by discounts.
RESULTS: From 2013 to 2021, oral DMT list prices increased from $73,924 to $104,372 (5.3% AAC) while net prices rose from $69,187 to $82,181 (1.5% AAC) because of increasing manufacturer discounts (6.4%-21.2%). From 2014 to 2021, MAb DMT list prices increased from $70,320 to $92,109 (4.1% AAC), with net prices rising from $55,109 to $79,396 (3.0% AAC). Discounts offset 51%-86% of cumulative list price increases for oral DMTs (fingolimod, teriflunomide) vs 0%-35% for MAb DMTs.
DISCUSSION: The divergent net pricing trends between oral and MAb DMTs may reflect increasing brand and generic competition among oral DMTs and a lack of biosimilar options among MAb DMTs.
Solanki, Pooja, Marissa Wirth, Frances M Weaver, Katie J Suda, Stephen P Burns, Nasia Safdar, Eileen Collins, Charlesnika T Evans, and Margaret A Fitzpatrick. (2026) 2026. “Experiences and Quality of Life Impacts Related to Urinary Tract Infections in Veterans With Neurogenic Bladder: A Mixed Methods Study.”. Neurourology and Urodynamics. https://doi.org/10.1002/nau.70246.
AIMS: Urinary tract infections (UTIs) are common long-term complications in people with neurogenic bladder (NB). However, there are limited data on how UTIs impact different aspects of quality of life (QoL) in people with NB. Our objective was to understand UTI-related QoL impacts in Veterans with NB.
METHODS: Twenty-three Veterans with NB and UTI diagnoses in the prior year participated in focus groups to share their perceptions of and experiences with UTIs including QoL impacts. Transcripts were coded using inductive and deductive reasoning. A patient survey was also developed using items modified from existing surveys validated for people with NB and new items generated by the study team using the focus group data. Qualitative results on QoL impacts from focus groups were integrated with the quantitative survey data to provide a more comprehensive understanding of UTI-related QoL impacts in people with NB.
RESULTS: UTIs most significantly impacted daily activities, primarily by impairing mobility and restricting independence which led to more limited participation in social, family, and leisure activities. Psychological impacts were more prominent in the focus groups than the survey data.
CONCLUSIONS: Results suggest that people with NB may experience substantial QoL impacts from UTIs, and patient-centered interventions may be needed to decrease the impact of UTIs.
Richman, Ilana B, Anna Hung, and Timothy S Anderson. (2026) 2026. “Statins for Primary Prevention-The Gap Between Guidelines and Patient Preferences.”. JAMA Internal Medicine. https://doi.org/10.1001/jamainternmed.2025.7955.
Anderson, Timothy S, Linnea M Wilson, and Jeremy B Sussman. (2026) 2026. “Thirty-Year Atherosclerotic Cardiovascular Disease Risk Among US Adults Aged 30 to 59 Years.”. Circulation. Population Health and Outcomes 19 (1): e012348. https://doi.org/10.1161/CIRCOUTCOMES.125.012348.
BACKGROUND: The 2023 Predicting Risk of Cardiovascular Disease Events equations estimate 30-year atherosclerotic cardiovascular disease (ASCVD) risk for adults aged 30 to 59 years to inform preventative treatment decisions. We aimed to characterize 30-year ASCVD risk in the eligible US population.
METHODS: We examined adults aged 30 to 59 without known ASCVD who participated in the National Health and Nutrition Examination Survey, 2017 to March 2020 cycle. Using survey weighting to generate nationally representative estimates with 95% CIs, we described 10-year and 30-year ASCVD risk and risk factor control. We then estimated the absolute risk reduction of statin use in populations at high 30-year risk (≥20%.
RESULTS: The cohort included 3229 participants without known ASCVD (mean [SD] age, 44.6 [8.8] years; 49.8% women), representative of 101.9 million (95% CI, 92.2-111.6) US adults. The mean estimated 10-year ASCVD risk was 2.0% (95% CI, 1.9%-2.1%), and the mean 30-year risk was 9.7% (95% CI, 9.4%-10.1%). Of the 9% of the population with high estimated 30-year ASCVD risk, 32.4% (95% CI, 24.0%-40.7%) reported statin use. Most adults with high 30-year ASCVD risk had multiple uncontrolled risk factors, including elevated blood pressure (70.8% [95% CI, 62.4%-79.2%]), obesity (59.9% [95% CI, 52.6%-67.2%]), and elevated total cholesterol (56.2% [95% CI, 45.5%-66.9%]). Expanding primary prevention statins to adults with high 30-year ASCVD risk would change recommendations for 2.5 million (95% CI, 1.9-3.2) adults not currently receiving statins, with an average number needed to treat over 10 years to prevent 1 ASCVD event of 78.3 (95% CI, 74.6-82.0).
CONCLUSIONS: Use of the Predicting Risk of Cardiovascular Disease Events 30-year ASCVD risk equations would identify a population of US adults with low 10-year but high 30-year risk who may warrant enhanced primary prevention strategies.
Shuey, Bryant, Fang Zhang, Stephanie Argetsinger, Rebecca Costa, Hefei Wen, and Franklin Wharam. (2026) 2026. “Opioid Use Disorder Care Presentations After High-Deductible Health Plan Enrollment.”. Journal of Addiction Medicine. https://doi.org/10.1097/ADM.0000000000001662.
OBJECTIVE: Determine whether employer-mandated transitions from low- to high-deductible health plans (HDHPs) are associated with delays in opioid use disorder (OUD)-related care presentations. Cost-sharing may negatively impact timely diagnosis and treatment of OUD.
METHODS: Using 2003-2017 national commercial insurance claims data, we used a matched time-to-event and difference-in-differences design to examine the association between employer-mandated transitions from low to HDHPs on OUD-related care presentations. Study group included 574,058 adults aged 18-64 years continuously enrolled in low-deductible (<$500) health plans during a baseline year followed by up to 4 years in HDHPs (≥$1000) after an employer-mandated transition (exposure). Control group included 4,386,636 adults contemporaneously enrolled in low-deductible plans matched on employee and employer characteristics. Outcomes included first OUD-related office visit, buprenorphine pharmacy fill, and OUD-related high-acuity visit. The secondary outcome was the yearly number of high-acuity care days.
RESULTS: After an employer-mandated HDHP transition, there were no differences in time-to-first OUD-related office visit (HR, 1.02, 95% CI: 0.94, 1.11) or buprenorphine fill (HR, 1.05, 95% CI: 0.97-1.13) in the HDHP versus control cohort. In contrast, the HDHP transition was associated with delays in time-to-first OUD-related high-acuity visits compared with control members (HR 0.86, 95% CI: 0.79-0.93). HDHP members experienced a 37.4% (95% CI: -57.8, -17.0) relative reduction in high-acuity care days relative to the control group from baseline to follow-up.
CONCLUSIONS: Employer-mandated transitions to HDHPs were associated with delays and reductions in OUD-related high-acuity presentations. Such delays and reductions in timely OUD care could lead to adverse health outcomes.
Pham, Alexander T, Timothy S Anderson, Lona Mody, and Jerard Z Kneifati-Hayek. (2026) 2026. “Reducing Potentially Inappropriate Medication Use for Older Adults in the Emergency Department-A Safer Script.”. JAMA Internal Medicine. https://doi.org/10.1001/jamainternmed.2025.7888.
Wilson, Linnea M, Brianna X Wang, Michael A Steinman, Mara A Schonberg, Edward R Marcantonio, Shoshana J Herzig, and Timothy S Anderson. (2026) 2026. “Concordance of Discharge Materials and Older Adult Patient Understanding Cardiometabolic Medication Changes During Hospitalization.”. Journal of the American Geriatrics Society. https://doi.org/10.1111/jgs.70329.
Sankey diagram of agreement between dischareg summary, discharge instructions, and patient provided reasoning for chronic medication changes made during hospitalization.