Journal of Clinical and Translational Science

Poor retention of physician-scientists in the work force is a major impediment to progress in biomedical research, and the leaky pipeline of junior physician-scientists was exacerbated after the COVID-19 pandemic. We report the results of a multi-institutional survey aimed at assessing hiring practice patterns among academic deans and department chairs, with 34 responses before and 70 responses after the COVID-19 pandemic. We found that private institutions tend to provide greater startup support across all areas of research, including basic science, translational, and clinical arenas, with NIH funding and publication volume predicting the level of support. We found that half of respondents provide research RVUs. The COVID-19 pandemic adversely impacted the availability of supplemental internal funding and bridge funding, which catalyzed institutions to support junior faculty through endowments. Yet, we found that junior faculty had to rearrange clinical schedules to increase clinical productivity. We also found that childcare policies were more robust at private institutions. These data highlight hiring practices across a cohort of academic deans and department chairs to improve transparency of the hiring process for junior faculty candidates approaching their first independent position. Providing greater transparency in hiring practices can help physician-scientist trainees find a good fit for their faculty position and can help stave off attrition from this pipeline.

Digital health technologies are powerful-enhancing data collection, participant engagement, and personalized health interventions-yet their rapid proliferation has outpaced guidance for research participant protection. Current practice assists researchers in identifying risks but provides limited support for comprehensive risk management. To address this gap, we developed the Digital Health Checklist-Risk Management (DHC-RM) Tool, which integrates the established Digital Health Checklist with approaches from safety risk management. We conducted a study (n=40) comparing the DHC-RM Tool with current practice using a randomized experimental difference-in-differences design. Primary outcomes were the quantity, variety, and novelty of risks identified; secondary outcomes were the same constructs applied to risk control development. Compared with current practice, use of the DHC-RM Tool resulted in dramatically improved performance across all primary outcomes. Users identified on average 14.7 additional risks (compared to baseline) versus 0.26 in the control group and a higher number of risks in each of six pre-identified risk domains. Half of all distinct risks identified in the comparison phase were identified exclusively using the tool. The tool also improved risk control design, producing 9.63 additional risk control strategies per participant compared with 0.15 for current practice and yielding substantially greater novelty and variety. User feedback was also positive: 75% of participants reported they would use the tool again, citing its structured workflow, just-in-time examples, improved insight into risks, and its value for IRB communication. Suggestions for refinement focused primarily on expanding training examples and providing additional support for risk control development. The DHC-RM Tool significantly improves risk management practice in digital health research. By embedding structured, ethics-informed risk management into digital health research design, the DHC-RM Tool has the potential to improve participant protection while also streamlining ethics approval. Author SummaryDigital health research can put participants (and others) at risk in ways that dont always occur to the researchers who are designing a study. Researchers also face challenges in prioritizing risks and coming up with ideas to reduce those risks. We developed a new approach, the Digital Health Checklist - Risk Management Tool (DHC-RM Tool), to give researchers the support they need to identify, assess, and address research participant risks in this fast-moving field. Our experimental study found that use of the DHC-RM Tool led to a very large improvement in how well researchers managed the risks of digital health research studies. Using the toolkit, they were able to identify more risks than they identified using current practice-including risks they would not otherwise have considered. They were also able to come up with more changes to reduce the risks associated with digital health research studies, including changes they would not otherwise have considered. Those who used the toolkit found it beneficial and easy to use. The DHC-RM Tool fills an important gap in the science and practice of participant protection in digital health research.

IntroductionPhysician assistant (PA) programs face persistent challenges in recruiting and retaining clinical preceptors due to time constraints, administrative burden, lack of compensation, and limited training. Additional pressures, such as health care consolidation, program expansion, clinician burnout, and financial implications of paid clinical sites, further strain preceptorship capacity. This study examines motivators and barriers influencing clinicians willingness to precept PA students. MethodsThis mixed-methods study used snowball sampling to recruit current, former, and non-precepting PAs across North Carolina. Participants completed surveys with Likert-scale and open-ended items adapted from the 2011 National Survey of Physician Assistants. Four virtual focus groups, selected from survey respondents, underwent semi-structured interviews informed by Self-Determination Theory (SDT). Quantitative data were analyzed using descriptive statistics and ordinal logistic regression; qualitative data underwent thematic analysis with deductive SDT coding and inductive refinement. Triangulation integrated findings. ResultsRespondents (N = 158) represented diverse clinical experience. Top motivators included student quality (66%), program support (53%), and financial compensation (51%). Key barriers were student quality (61.29%), burnout (53.23%), and lack of compensation (46.77%). From the focused group discussion, four themes emerged: Student Quality, Financial Compensation, Non-Financial Incentives, and Administrative Support. Student preparedness acted as both motivator and barrier; compensation concerns focused on fairness. DiscussionPreceptorship relies on relational and professional factors, student quality, recognition, and institutional alignment, rather than financial incentives alone. System inefficiencies, inadequate preparation, and misaligned compensation hinder engagement. Improving student readiness, enhancing institutional support, and implementing transparent, layered incentives may strengthen recruitment and retention.

BackgroundParticipating in research during medical school is supported by institutional programs and may influence subsequent professional development. ObjectiveWe aimed to describe the current status and heterogeneity of scholarly research programs for medical students in the United States, including expectations, support, and key structural features. MethodsWe conducted a cross-sectional web audit of official webpages for all accredited US MD- and DO-granting medical schools (search performed September 2024 to January 2025). Extracted variables included participation requirements, mentorship, timing and duration (overall and dedicated research time), expected scholarly outputs, funding sources, stipend information, and stated program goals. We compared Carnegie tier R1 (Very high research activity) versus other institutions, QS Top-50 versus other institutions, and MD versus DO schools using {chi}2/Fisher exact tests for 2x2 tables and exact trend or Freeman-Halton tests for multicategory variables. ResultsPrograms were identified for all 202 institutions. Funding was explicitly mentioned by 61.9% (125/202) of programs, 27.0% (51/189) were compulsory, 98.9% (188/190) reported faculty mentorship, and 91.0% (171/188) were exclusive for medical students. Program duration, dedicated time, expected outcomes, stipend reporting, funding sources, and stated goals varied widely. Carnegie R1 institutions had longer duration (P=.002) and tended to report external funding more often than other institutions (25/104, 24.0% vs 9/98, 9.2%; OR 3.13, 95% CI 1.38-7.10; P=.008). QS Top-50 institutions were more likely to require compulsory participation than other institutions (11/19, 57.9% vs 40/170, 23.5%; OR 4.47, 95% CI 1.68-11.87; P=.003). No significant differences were observed between MD and DO programs across most measured characteristics. ConclusionsScholarly research programs for medical students are ubiquitous across US medical schools but heterogeneous in structure, expectations, and support. Research-intensive and top-ranked institutions may have more external funding and sometimes may put together longer and compulsory programs Further evaluation of student experiences and outcomes is warranted.

Improving diversity in U.S. Alzheimers disease (AD) research is a pressing need. By 2050, Hispanic and Latino Americans will comprise 30% of the population. Hispanics are 1.5 times more likely and Blacks are twice as likely to develop AD compared to Whites, yet both remain vastly underrepresented in clinical trials research. Aging and AD research mentorship of underrepresented STEM undergraduates is designed to promote entry into related professions by students committed to decreasing disparities in AD research participation and clinical care. The NIA-funded MADURA program recruited 93 students from backgrounds historically underrepresented in STEM majors and/or from NIH-defined disadvantaged backgrounds. Trainees were placed in aging/AD research labs and received weekly training and mentorship from faculty research PIs and other types of supervisors (postdoctoral researchers, graduate students, research assistant staff...) Our study examined student ratings of the program and mentor behaviors, using a program-specific survey and the Mentoring Competency Assessment-21 (MCA-21). Trainees were highly satisfied with both mentoring relationships and the overall program. Student rated MCA-21 competency areas were quite high for both P.I.s and other types of research mentors. However, there were striking differences in associations between competencies and relationship and program satisfaction, by mentor type. For PI mentors, no MCA-21 competencies were associated with relationship satisfaction, but five of six competencies were associated with relationship satisfaction for other mentor types. Similarly, no PI mentor competencies were significantly correlated with overall placement satisfaction, but all six competencies were correlated with overall placement satisfaction for other mentor types. The authors discuss the likelihood of differing student expectations of faculty PI versus other types of research mentors, recommendations for assessing role-specific student expectations (including functions primarily possible only for senior faculty PIs), and utilizing nearer-peer plus PI faculty mentors to comprehensively address the gamut of mentee needs.

BackgroundEvidence supports the key role research mentors play in bolstering the success of early stage investigators (ESI). However, there are limited data about the impact of supplemental, cross-disciplinary career mentorship and professional development opportunities for ESIs seldom included during academic training. We assessed the perceived value of this approach among post-doctoral fellows and early career faculty who participated in a multi-component career mentoring program organized by the University of California, San Francisco Center for AIDS Research (UCSF CFAR). MethodsWe surveyed past program participants (2005-2020), assessing demographics, current career status, perceived impact of the program, and feedback on program elements. We performed thematic analysis on open-ended responses to explore program benefits. ResultsOf 146 program participants contacted, 102 responded (70% response rate). Over two thirds (65%) were female, and 38% self-identified as underrepresented minority (URM) investigators. A majority of respondents now dedicate >70% of their time to research. All would recommend the program to ESI colleagues, and over 80% reported that their CFAR mentors influenced their career trajectories in several ways, including help with grant writing, linkage to researchers sparking new collaborations, and support through personal challenges or navigating conflict with primary research mentors. While 90% of URM ESIs valued advice from CFAR mentors, only a third reported receiving specific support around challenges faced as minoritized investigators. ConclusionsA career mentoring program designed to complement the support offered by research mentors positively influenced the career trajectory of ESIs. Focused efforts are needed to support URM investigators who face ongoing structural barriers to success in academic settings.

Background: Cardiac rehabilitation (CR) is a cost-effective, evidence-based intervention that improves outcomes for patients with heart failure (HF), yet access remains inequitable, particularly among Medicaid enrollees. This study evaluates the state-by-state variability in Medicaid coverage for CR services and examines the implications for health equity in vulnerable populations. Methods: We conducted a cross-sectional policy analysis of all 50 U.S. states to assess Medicaid coverage for outpatient CR services billed under CPT codes 93797 (without ECG monitoring) and 93798 (with ECG monitoring). Publicly available Medicaid documents were reviewed and supplemented with direct communication with state Medicaid agencies. States were categorized into full, partial/inconclusive, or no coverage. Geographic trends were visualized through heat maps and contextualized using state-level Medicaid enrollment data. Results: Marked disparities in CR coverage were identified. Only 41 states reimbursed for CPT 93797, and 43 for CPT 93798. Eight states lacked coverage for either code, predominantly in the South and Mountain West, including Arkansas, Georgia, Louisiana, Mississippi, Nevada, and Utah. States with the highest Medicaid enrollment (e.g., Louisiana, Arkansas) often provided no CR coverage, compounding access barriers for high-risk, low-income populations. Conclusions: The absence of standardized Medicaid coverage for CR contributes to systemic inequities in cardiovascular care, disproportionately impacting disadvantaged communities. Aligning Medicaid policies to ensure universal CR access--particularly through tele-rehabilitation and value-based care models--could reduce hospitalizations, improve survival, and promote health equity across the U.S.

Structured AbstractO_ST_ABSImportanceC_ST_ABSRemote sampling technologies are invaluable for protecting both participants and researchers when studying highly infectious diseases. When leveraged for longitudinal studies, remote sampling with transcriptomic readouts is a powerful tool for studying the host immune response. Additionally, remote study flexibility circumvents common barriers to research participation including length of commute, transportation, and scheduling, thereby expanding access to clinical research. ObjectiveIn this work, we investigate the effectiveness of a remote study model for reaching women from underrepresented, underserved, and underreported (U3) populations. We sought to recruit individuals who qualify as underrepresented in clinical research, who are located in rural areas, or who come from disadvantaged backgrounds per the NIH definition. DesignIn this longitudinal study, U3 women positive for COVID-19 were enrolled and followed over the course of 6 months. In the first month of the infection, participants (n = 40) self-collected a set of 5 nasal swabs, 5 homeRNA-stabilized blood samples, and 2 additional unstabilized blood samples at first and last sampling. Sampling time points were spaced 5 days apart, so that the total of the 5 time points was completed within 25 days. homeRNA is a platform for remote self-collection of blood samples with subsequent RNA stabilization. A subset of participants likely to develop post-acute sequelae of COVID-19 (PASC) and their age-matched controls were selected to self-collect an additional set of 5 nasal swabs and 5 homeRNA-stabilized blood samples during month 3 of study participation, with the same sampling frequency. All participants were resurveyed at months 4, 5, and 6 about their symptoms. Participants also completed surveys at each sampling and a more comprehensive survey about study experience after each set of 5 time points. SettingThis was a fully remote study with all sampling supplies and instructions shipped to the participants. Participants self-collected blood and nasal swabs at home and shipped these back to our lab for further processing. Surveys were administered electronically using REDCap. ParticipantsFor this study, we enrolled women who were 18 or older, met the NIH criteria for U3, and who had tested positive for SARS-CoV-2 within a week of enrollment. Further, we excluded protected populations including individuals who were pregnant and/or incarcerated. Of the 334 individuals who completed the screening process, 65 were invited into the study based on the eligibility criteria and balancing age, race/ethnicity, and state of residence to closely correspond to the demographics of the United States. Of the 65 invited individuals, 40 were fully enrolled in the study and 39 completed all study components. Main Outcomes and MeasuresPrior to the study, we proposed that the increased flexibility of a remote study design would allow for participation of populations underrepresented in clinical research. The primary measurements planned for this study consisted of usability data and general experience in a longitudinal study. These data were collected by self report using electronically administered surveys. The Consolidated Framework for Implementation Research (CFIR), a well-established implementation science framework, was used to guide the development of questions about usability and study experience. Results40 women were recruited from 19 states, with diverse racial backgrounds (62% White, 15% Black or African American, 10% Asian, 5% American Indian or Alaska Native, 5% Other, 3% More than one race), a mostly even age distribution (26% ages 20 - 29, 15% ages 30 - 39, 31% ages 40 - 49, 28% ages 50+), and most of whom (80%) are categorized as having a disadvantaged background per the NIH. Survey responses show high satisfaction with the study, where all participants who completed the study (100%, n = 39/39) indicating that they would be willing to participate in a similar study again, with most (n = 32/39) indicating a willingness to participate for up to 4 years with around 15 samples collected per year. We note that 4 years was the longest time period that participants were able to select in their surveys, suggesting that participants may be willing to participate for even longer periods. Most (>90%) either agreed or strongly agreed that all components of the kit were easy to use. Conclusions and RelevanceThe high retention (98%, n = 39/40) and satisfaction of participants in this study indicates the utility of a remote study design for longitudinal research. We also find that study topic, flexibility of study, and positive interactions with the study team are important factors for participant recruitment and retention. This work suggests that the increased flexibility of a fully remote design enables engagement of individuals who may otherwise be excluded from clinical research.

BackgroundThe sharing of data generated through the course of clinical genetic and genomic testing without explicit patient consent is increasingly important for timely diagnosis and treatment. While many jurisdictions permit the sharing of identifiable data for direct patient care, institutional policies vary in how clearly they specify key elements. When do policies permit sharing of data without explicit consent? What data types may be shared, with whom, and under what safeguards? Greater clarity around these elements may support responsible data sharing while balancing timely care with transparency and appropriate protections. MethodsWe conducted a qualitative content analysis of data-sharing and privacy policies from 33 clinical genomic institutions across 17 jurisdictions. Using a predefined analytical framework, we assessed how policies document key governance elements relevant to sharing without explicit consent. Two independent reviewers extracted information about clinical contexts, data types, justifications, and protections, documenting areas of inconsistency across institutions. ResultsAlthough 70% of institutions described circumstances permitting data sharing without explicit consent, most policies did not clearly define the scope or governance of such sharing. Policies also rarely distinguished clinical from research or secondary use and inconsistently specified privacy and security safeguards. While sharing was commonly justified for clinical care (78.3%) or testing services (43.5%), recipient roles, access conditions, and onward-sharing expectations were often left undefined. ConclusionThis uneven documentation could make it difficult for clinical teams, laboratories, and institutional decision-makers to identify and justify key decisions about what is permitted and under what conditions. A guidance framework specifying core policy elements and corresponding protections could help institutions communicate their governance choices more clearly while supporting more comparable baseline practices for responsible data sharing across settings.

BackgroundDelivering timely, high-quality feedback on resident scholarly projects is labour-intensive, especially in large programmes. We developed an AI-assisted evaluation system, powered by the open-weight LLaMA-3.1 large-language model (LLM), to generate formative feedback on Family Medicine residents scholarly projects and compared its performance with expert human evaluators. MethodsWe evaluated whether the AI-generated feedback achieves comparable quality to expert feedback. The tool ingests heterogeneous resident submissions (PDFs, scans, photographs) via OCR and produces section-by-section feedback aligned with programme rubrics. In a three-phase study we evaluated 240 feedback reports (Short, Question and Timeline, Final; n = 80 each). Within each phase, 40 reports were AI-generated and 40 produced by research experts across four project types: Quality Improvement, Survey-Based, Research, and Literature Review. Blinded raters used a 25-item survey across five constructs: understanding & reasoning, trust & confidence, quality of information, expression style & persona, safety & harm. ResultsSurvey reliability was high across phases ( = .71-.98). Human feedback generally out-scored AI. In short reports, humans led on quality (Mean {+/-} SD; 4.14 {+/-} 0.57 vs 3.09 {+/-} 1.05) and trust (3.96 {+/-} 0.71 vs 2.78 {+/-} 1.15). In final reports, differences become small for quality (4.09 {+/-} 0.65 vs 3.49 {+/-} 0.68) and persona (4.16 {+/-} 0.40 vs 3.91 {+/-} 0.50), while AI was preferred for safety (4.50 {+/-} 0.60 vs 4.36 {+/-} 0.56). Performance varied by project type: in survey-based final reports the AI led on quality (4.28 {+/-} 0.50 vs 3.98 {+/-} 0.44) and safety (4.58 {+/-} 0.40 vs 4.24 {+/-} 0.67), whereas in quality-improvement short reports humans were markedly superior in reasoning (4.27 {+/-} 0.68 vs 2.33 {+/-} 1.00). ConclusionsAn open-weight LLM with curated prompts can generate rubric-aligned feedback at scale that approaches the quality of expert human feedback. While expert feedback remained superior overall, AI surpassed humans in selected contexts and safety assessments. Performance of the tool will increase over time as newer and more capable open-weight models are released. Our code and systems prompts are open source.

BackgroundHigh workload among healthcare workers has increasingly been correlated with poor patient outcomes, inefficient operational and financial outcomes, and burnout. Despite growing literature exploring causes of attending physician workload, there is limited understanding of trainee-specific measures. ObjectiveWe aimed to characterize elements contributing to trainee workload and perceived challenges and satisfiers to the trainee workday as a foundation for better understanding and measuring trainee work experience. MethodsInternal Medicine and Medicine-Pediatrics residents at an academic medical center were invited to participate in focus groups discussing contributors to inpatient workload and work experience between March and April 2024. A qualitative content analysis identified key metrics of trainee workload and work experience, which were then consolidated into overarching domains. A structured, multi-round rating process ranked the perceived relevance of each metric. ResultsTwenty residents participated across six focus groups. Analysis of focus groups yielded 297 workload metrics across 28 unique domains. Seventeen domains had metrics identified as highly relevant (median 6-7; IQR < 1) including autonomy, communication, disruptions, task switching, documentation, emotional burden, patient factors, professional fulfillment, rounding, teaming, and work-life balance. ConclusionsResident physicians highlighted complex interactions between clinical factors, work design, and psychosocial dynamics that contribute to their sense of workload. This creates opportunities to develop unique measures of workload to understand the trainee experience better. Further studies are needed to capture the generalizability of these findings and the relationship between these workload domains and patient, organizational, and trainee outcomes with the aim of implementing evidence-based work design.

BackgroundAdvanced Practice Providers (APPs) in emergency and urgent care settings experience high burnout rates, yet limited research examines cognitive factors influencing professional fulfillment. The Empowerment Dynamic framework suggests outcome-oriented thinking may protect against burnout compared to problem-oriented patterns. ObjectiveTo examine relationships between cognitive mindset orientation, professional fulfillment, and burnout among APPs while providing preliminary validation of a novel cognitive assessment instrument. MethodsCross-sectional survey of licensed APPs working in emergency departments and urgent care facilities across two health systems (July-October 2025). Professional fulfillment and burnout were measured using the Stanford Professional Fulfillment Index; cognitive orientation was assessed using a newly developed 22-item instrument. ResultsAmong 98 respondents (19.5% response rate), mean professional fulfillment was 5.8 and mean burnout was 4.5; 40.8% met burnout criteria. Professional fulfillment and burnout were inversely correlated (r = -0.62; P < .001). Problem orientation correlated positively with burnout (r = 0.56) and negatively with fulfillment (r = -0.36), while outcome orientation showed opposite patterns (burnout: r = -0.57; fulfillment: r = 0.44). In multivariable models, outcome orientation remained independently associated with lower burnout ({beta} = -1.51; P = .003) and higher fulfillment ({beta} = 1.73; P = .002). ConclusionsCognitive mindset orientation is associated with burnout and professional fulfillment among APPs. The novel assessment instrument demonstrates acceptable psychometric properties. Future longitudinal studies are needed to establish causality and evaluate cognitive interventions for burnout prevention.

BackgroundClinical research coordinators play a crucial role in ensuring the scientific rigor, regulatory compliance, and operational integrity of clinical trials. However, in Africa, they often lack access to structured, competency-based training, especially in operational, regulatory, and trial management domains. This study evaluated the effectiveness of a comprehensive training intervention designed to standardize and enhance core competencies of clinical trial coordinators. MethodsWe conducted a prospective pre-post interventional study among cohorts of clinical research professionals completing a 10-week, internationally-accredited, Moodle-based clinical trial operations training program aligned with the Joint Task Force Core Competency Framework, covering 10 lessons and 25 domains. Self-reported competence was evaluated at baseline and post-training. Data analyses included paired t-tests for aggregate scores, McNemars exact test for domain-level proportions, multivariable logistic regression for predictors of improvement, and Cohens d for effect size. ResultsAmong the 166 participants enrolled from 19 African countries and completed the pre-training survey, 152 who completed the program and post-training survey were included. The training significantly increased the mean aggregate competence from 12.24{+/-}7.85 (out of a maximum of 25) to 23.35{+/-}2.73 (mean difference: 11.11; 95% CI 9.86-12.36; p<0.001; Cohens d=1.41). Score variance decreased, with the median score increasing from 12.0 (IQR: 6.0-19.0) to 24.5 (IQR: 23.0-25.0). All 25 domains improved (p<0.001), with the largest gains in complex, low-baseline domains: managing external partners (+59.2%), project management (+58.6%), financial management (+55.3%), and trial close-out (+57.2%). (+57.2%). Ethical principles and informed consent that had high baseline competence reached near-universal levels at 99.3% and 98.7%, respectively. No differences were observed by country or gender (p>0.05). ConclusionStructured, competency-based training strengthens clinical trial coordinators capabilities, particularly in technical and administrative domains that are often overlooked. Accredited, framework-aligned clinical trial training programs promote consistent trial quality, strengthen research capacity, and sustain excellence in clinical trial delivery. WHAT IS ALREADY KNOWN ON THIS TOPIC- Clinical research coordinators play a crucial role in ensuring the scientific rigor, regulatory compliance, and operational integrity of clinical trials WHAT THIS STUDY ADDS- The study evaluated the effectiveness of a comprehensive training intervention designed to standardize and enhance core competencies of clinical trial coordinators in Africa, where they often lack access to structured, competency-based training HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY- This study should encourage the design and delivery of internationally-accredited, Moodle-based clinical trial operations training programs in Africa that enhance clinical trial competency.

ImportanceFunding of womens health research has been low, with a narrow focus on what is considered womens health. Understanding which lifespan stages and areas of womens health are funded is essential to determine the breadth of womens health research and identify where gaps in research are concentrated. ObjectiveTo examine which lifespan stages and areas of womens health were more likely to be funded in open Canadian grant competitions. Evidence ReviewPublicly available funded Canadian Institutes of Health Research (CIHR) Project Grant abstracts from 2009 and 2023 were coded for mention of a hormonal transition period (puberty, menstrual cycle, pregnancy/postpartum, perimenopause/menopause), exogenous hormone use (hormonal contraception, fertility treatments, menopause hormone therapy), and/or a female-specific health condition. Abstracts were also coded for Indigenous health and Two Spirit, Lesbian, Gay, Bisexual, Trans, Transgender or Trans Identified, Queer, Intersex, Asexual, Plus (S2/LGBTQIA+) populations. Remaining grant abstracts were grouped by common theme.Abstracts were analyzed for changes in research representation and funding over time and whether funding was lower than expected based on population prevalence or proportion of the lifespan spent in that stage. FindingsNearly 50% of female-specific research focused on cancers (breast, gynecologic) or pregnancy and did not significantly increase in funding or representation over time. Of the funded grant abstracts that focused on pregnancy, ~22% examined outcomes pertaining only to the fetus/offspring, not the birthing parent. Over 15 years, 2.37% of all CIHR abstracts over 15 years were devoted to pregnancy, whereas only 0.24% was devoted to other hormonal life stages (menstrual cycles, menopause). For all hormonal transition stages except pregnancy, the proportion of grants and funding devoted to that stage was lower than expected based on the proportion of the lifespan spent in that stage. Conclusions and RelevanceThese findings reflect the narrow breadth of womens health, which largely focused on cancers (breast, gynecologic) or pregnancy, rather than being distributed across key life course stages that shape womens health. To advance science for all, the heterogeneity and complexity in womens health across the lifespan must be embraced and barriers for womens health research must be removed. Key PointsO_ST_ABSQuestionC_ST_ABSWhich areas and life stages of womens health are most likely to be funded in Canadian open grant competitions, and where are funding gaps concentrated? FindingsNearly half of female-specific grants focused on cancer or pregnancy, with little change over time. Pregnancy dominated hormonal-stage research, often excluding maternal outcomes, while menstrual and menopausal stages were rarely funded. For most life stages, funding was lower than expected based on lifespan representation. MeaningWomens health research funding remains narrowly focused. Broader, life-course-inclusive investment is needed to address critical gaps and advance equitable health science.

BackgroundThe physician assistant (PA) workforce has expanded rapidly in the United States, increasing the importance of effective physician-PA collaboration. Although PAs improve patient outcomes and access to care, the determinants of effective collaboration has not been well studied. North Carolina provides a relevant context due to its growing PA workforce and supervisory regulatory structure, in which physicians retain administrative responsibility for PA supervision across practice settings. This study examines determinants of effective physician-PA collaboration in ambulatory care settings in North Carolina. MethodsFour virtual focus groups were conducted with practicing physicians (n=7) and PAs (n=9) across multiple specialties in NC. Transcripts were analyzed using thematic analysis to identify facilitators and barriers to collaboration. ResultsThematic analysis identified six major themes reflecting relational, organizational, and systemic influences on teamwork. Findings demonstrate collaboration evolves over time through early-career mentorship, continuity of working relationships, and progressive trust development. Differences in professional identity, power dynamics, and misunderstanding of PA scope of practice influenced autonomy and delegation. Systemic factors such as reimbursement structures and organizational supervisory policies hindered efficient teamwork. LimitationsFindings are based on a small, purposive sample within a single state and may not be generalizable to all ambulatory settings or regulatory environments. Perspectives may also reflect self-selection bias among participants with strong views on collaboration. ConclusionsEffective physician-PA collaboration depends on intentional onboarding, role clarity, interprofessional education, and alignment of organizational policies with regulatory standards to support team-based care.

BackgroundArtificial intelligence and machine learning (AI/ML) are among the fastest-growing domains in NIH research funding, but whether children have shared equitably in this expansion is unknown. We characterized pediatric representation in NIH AI/ML funding from fiscal years (FY) 2020 to 2024. MethodsNIH grant data were obtained from Research Portfolio Online Reporting Tools Expenditures and Results bulk files for FY2020 to FY2024. AI/ML grants were identified using the NIH Research, Condition, and Disease Categorization "Machine Learning and Artificial Intelligence" category, and pediatric grants using the "Pediatric" category. Subprojects were excluded. Grants were deduplicated within each fiscal year by core project number for trend analyses and across all years retaining the most recent fiscal year for cross-sectional totals. Disease areas were identified by keyword searches of titles and abstracts. ResultsAcross FY2020 to FY2024, 5,624 unique NIH AI/ML grants totaling $3,371 million were identified. Of these, 836 grants (14.9%) were classified as pediatric, representing $401 million (11.9%) of total NIH AI/ML funding. Although this share was consistent with the historically reported overall NIH pediatric funding baseline of approximately 10% to 12%, it remained substantially below the US pediatric population share of approximately 22%. The pediatric share of NIH AI/ML funding declined from 12.3% in FY2020 to 10.8% in FY2024, despite growth in absolute pediatric funding. Indexed to FY2020, pediatric AI/ML funding grew approximately 2.6-fold compared with 3.0-fold growth in the total portfolio. Across disease areas, unadjusted adult/general-to-pediatric funding ratios ranged from 2.0-fold in mental health to 9.8-fold in cancer. ConclusionsPediatric representation in NIH AI/ML funding remained low and declined over time as the overall portfolio expanded. These findings suggest that growth in NIH AI/ML investment has not been matched by proportional gains for pediatric research.

Background: Palliative care services improve quality of life and health outcomes for individuals living with chronic and life-limiting illnesses. Although these services have expanded considerably in urban areas, their availability remains limited in many rural communities. This study aimed to identify key components of integrated palliative care services and examine how these elements are implemented within rural healthcare systems in southern Minnesota. Methods: A qualitative case study using deductive content analysis was conducted. Semi-structured interviews were carried out with healthcare professionals involved in palliative and hospice care serving rural communities in southern Minnesota. Results: Participants identified several essential components of integrated palliative care, including multidisciplinary care teams, continuity of care across healthcare settings, interprofessional collaboration, and early identification of patients who may benefit from palliative care. Existing services in southern Minnesota incorporate several integrated elements, such as coordinated care teams, individualized care plans, nurse-led case management, professional training, and the use of virtual visits for geographically distant patients. However, participants also identified important gaps, including limited availability of palliative care services in rural areas, fragmented continuity of care, challenges in early patient identification, funding and insurance barriers, and the absence of a unified palliative care network. Conclusions: While palliative care services in southern Minnesota demonstrate important strengths, further efforts are required to improve service integration, coordination, and access for rural populations. Strengthening integrated PCSs may help reduce disparities in access to care and improve service delivery for rural patients and their families. These findings may inform the development of integrated palliative care models in rural healthcare systems beyond the study setting.

IntroductionEighteenth-century medical texts document a formative period in the evolution of clinical reasoning, yet their integration into modern medical education is limited. The traditional approach to learning the history of medicine has naturally focused on passive reading, but new approaches using AI could enable learners to interrogate and simulate the historical diagnostic logic and therapeutic paradigms. More specifically, large language models (LLMs) offer an opportunity to create interactive simulations that allow experiential engagement with historical medical reasoning. MethodsWe developed a historically constrained LLM-based educational platform designed to emulate the diagnostic reasoning, language, and conceptual frameworks of an 18th-century physician. A modern GPT architecture was customized using strict instruction-based constraints and limited exclusively to a curated corpus of six foundational 17th- 18th century medical texts. Guardrails were implemented to prevent anachronistic terminology and modern medical concepts. Model outputs were evaluated qualitatively by comparing the models diagnoses and treatment plans with published diagnoses and treatment from original 18th century sources. We also applied the simulation to modern clinical vignettes for an illustrative contrast between modern and 18th century approaches. ResultsThe model generated responses that closely aligned with 18th-century medical and rhetorical style, as well as therapeutic reasoning. When presented with historical cases, the simulation demonstrated strong concordance with original diagnoses and management strategies. Secondly, when applied to modern cases, the model described period-appropriate reasoning, highlighting clear contrasts with contemporary biomedical reasoning. ConclusionsAI broadly, and more specifically LLMs configured as historically constrained simulators, can function as effective tools for learning in medical history. This approach could enable active engagement with historical clinical reasoning, fostering critical reflection on the contingent and evolving nature of medical knowledge. Such temporal simulations hold promise for medical humanities education and interdisciplinary teaching.

BackgroundThe 340B Drug Pricing Program was established to expand access to care for low-income and uninsured patients by allowing safety-net hospitals and clinics to purchase outpatient drugs at discounted prices. Over time, the program has expanded substantially, raising questions about whether participating hospitals are meeting the programs intended objectives. MethodsUsing 2023 hospital financial data from the RAND Corporation, we conducted cross-sectional descriptive comparisons of 340B and non-340B hospitals nationwide. Key measures included charity care as a percentage of operating expenses, Medicaid admissions as a share of hospital days, uncompensated care, and costs associated with uninsured patients approved for charity care. Subgroup analyses also examined the performance of Disproportionate Share Hospitals (DSH), Critical Access Hospitals (CAH), Rural Referral Centers (RRC), Sole Community Hospitals (SCH), and National Cancer Institute (NCI) designated hospitals. ResultsAmong 3,999 hospitals analyzed, 340B hospitals provided, on average, lower levels of charity care than non-340B hospitals (2.16% vs. 2.82% of operating expenses) and lower costs of charity care for uninsured patients (1.60% vs. 2.26%). However, 340B hospitals served a higher proportion of Medicaid patients (19.69% vs. 17.76%). Substantial variation was observed across 340B subcategories: DSH hospitals reported the highest Medicaid utilization, while CAH hospitals reported the lowest levels of charity care and Medicaid days. ConclusionsParticipation in the 340B program does not uniformly correlate with greater provision of charity care or uncompensated care. These findings suggest a misalignment between program intent and outcomes and support the need for greater transparency, standardized eligibility criteria, and minimum charity care requirements to ensure that 340B savings directly benefit underserved populations.

BackgroundChronic Care Management (CCM) services represent an underutilized Medicare benefit with potential to reduce healthcare costs and improve care coordination for beneficiaries with multiple chronic conditions. ObjectiveTo evaluate the real-world impact of CCM services on healthcare expenditures and patient out-of-pocket costs in a large multi-specialty outpatient practice. DesignPragmatic retrospective cohort study comparing Medicare beneficiaries enrolled in CCM services versus eligible non-enrolled beneficiaries. SettingLarge multi-specialty outpatient clinic in Alabama with 77 physicians across more than 20 specialties. ParticipantsTreatment group (n=6,093) consisted of patients continuously enrolled in CCM services between January 1, 2024 and December 31, 2024. Comparison group (n=30,432) included eligible patients who were not enrolled in CCM services during the same period. InterventionStructured CCM program delivered by licensed practical nurses (LPNs) providing monthly telephone or video encounters focused on care plan implementation, medication reconciliation, care coordination, preventive health maintenance, and social determinants of health. Main MeasuresPer-member-per-year (PMPM) paid amounts and patient out-of-pocket expenditures, adjusted for age and sex differences. ResultsThe CCM treatment group demonstrated 13.6% lower unadjusted healthcare costs compared to the comparison group ($96 vs. $110 PMPM). After adjusting for demographic differences, cost savings increased to 17.1% ($75 vs. $89 PMPM). Patient out-of-pocket expenses were 16% lower in the treatment group ($29 vs. $34 PMPM). These savings were achieved despite the treatment group being 2% older on average and including 10% more female beneficiaries--both factors typically associated with higher healthcare costs. ConclusionsImplementation of structured CCM services in a real-world multi-specialty practice setting is associated with reductions in both total healthcare expenditures and patient out-of-pocket costs. These findings support CCM as a practical, cost-effective approach to chronic disease management that benefits patients.