Value in Health

Background: The impact of the Inflation Reduction Act (IRA) upon late-stage developments has been assumed to be limited. The Congressional Budget Office's IRA analysis excluded post-approval innovation, potentially overlooking substantial economic risks to drug developers and declines in the availability of treatments in areas of high unmet medical need such as oncology. Methods: A total of 1148 secondary trials from 364 FDA-approved medicines, published from 2018 to 2025, were obtained from Biomedtracker and clinicaltrials.gov. Using fractional multinomial logit, we model the share distribution of secondary indication studies across 19 disease groups and assess the change in this distribution post-IRA. We also assessed the number of secondary treatment studies pre- vs. post-IRA using multiple linear regression. Results: After the IRA's introduction, small molecule follow-on studies in oncology exhibited a statistically significant 35% decline (R2 = .48, p < 0.014) and lead indication small molecule oncology approvals exhibited a statistically significant 27% decline (R2 = .70, p < 0.002). We also find a statistically significant 14% decline in the share of orphan oncology studies pre- vs. post-IRA (p<0.001). Research Conclusions: This study's results refute claims that the IRA would have minimal negative effects on patient access or late-stage biopharmaceutical R&D. We hope this study reinvigorates debate about the law's unintended consequences and encourages thoughtful policy solutions, as the IRA manifestly creates disincentives that negatively impact patients seeking needed new medicines, particularly those requiring cures addressing metastatic late-stage cancers.

Background. Tertiary clinical genomics reports condense layered molecular findings into documents that treating oncologists must read, translate, and act upon; manual summarisation of these reports is time-consuming and variable. Tools that assist summarisation and translation into local languages are emerging, yet the field lacks an agreed methodology for evaluating such tools before any downstream clinical use. The appropriate first endpoint is fidelity of the generated summary to its source report, assessed by qualified human raters under blinded scoring, not downstream variant classification. Methods. QNOMX-VHIR-CPSP-001 Phase 1 is a single-site, non-interventional clinical performance study conducted at Vall d'Hebron Institut de Recerca (VHIR) under ISO 20916:2019 as a Clinical Performance Study Protocol. De-identified tertiary cancer genomics reports from pediatric oncology cases are summarised by the AI-assisted summarisation system under evaluation and, in parallel, by the standard manual workflow. Qualified raters score both summary types against the source genomics report using the Quality Summary Index (QSI), a six-dimension, five-point rubric adapted from the Provider Documentation Summarization Quality Instrument, under a blinded, counterbalanced, two-period crossover with a minimum fourteen-day washout. Two co-primary composite endpoints, content and presentation, are analysed for non-inferiority under a Bayesian hierarchical model, with a frequentist linear mixed model as the convergence check. Inter-rater reliability is reported as Krippendorff's ; a Monte-Carlo power analysis of the fixed clustered design is pre-specified. Discussion. The design isolates summarisation quality from clinical decision-making by scoring both summary types against the same source report under blinding, counterbalancing, and a fourteen-day washout. Conclusion. The QSI rubric, the counterbalanced crossover, and the pre-specified Bayesian primary with frequentist convergence check define a replicable protocol for early-stage evaluation of AI-assisted summarisation in tertiary genomics reporting; observed variance components will inform sample-size determination for Phase 2.

Artificial intelligence (AI) decision support systems for surgery hold promise but face barriers to adoption, particularly around the interpretability of their outputs. We conducted an international cross-sectional survey of 47 neurosurgeons to evaluate perspectives on literature-derived explanation techniques for AI-generated anatomical segmentations, using endoscopic pituitary surgery as a high-risk exemplar. Participants ranked certainty scores, certainty maps, saliency maps, scene similarity scores, and nearest-neighbour illustrations, and rated them using a modified Explanation Satisfaction Scale alongside free-text feedback. Certainty-based techniques were consistently ranked and rated highest for interpretability - valued for aligning with surgical decision-making by conveying confidence (via scores) and anatomical boundaries (via maps). Saliency- and similarity-based methods were judged less clinically relevant and better suited to educational settings. Certainty-based explanations, therefore, appear most acceptable to surgeons for clinical integration of decision support systems, though their impact on AI acceptability, trust calibration, and performance requires prospective evaluation across surgical domains.

Background: Endoscopic endonasal transsphenoidal surgery (EETS) requires navigation around neurocritical anatomy. Today, artificial intelligence clinical decision support systems (AI-CDSSs) can orientate surgeons, but clinician trust in AI remains unclear, limiting safe deployment. This study evaluates how modifiable design affects trust and performance in a real-world pituitary surgery AI-CDSS. Method: Online, 70 clinicians with pituitary surgery experience were randomised evenly to a Basic or Enhanced AI-CDSS which outline the sella on EETS operative video. The Enhanced group additionally received explanation of the model and previous publications, alongside confidence labels depicting outline reliability. Both groups annotated the sella on six video clips, first alone then with the optional AI-CDSS. Clips were ordered by declining AI performance, except for the final clip. Self-reported trust was measured using a 1-7 scale after each annotation, and performance was the DICE overlap between user annotations and the ground truth. Comparisons used Mann-Whitney U and permutation analysis. Results: Sixty-four participants (91%) finished the exercise (31 Basic, 33 Enhanced). When AI performed best, median trust was 5.00 in both arms (U=559, p=.521). However, when AI performed worst, trust was significantly lower for the Enhanced group (3.00 vs 3.67, U=668, p=.035), sustained in the final clip (3.67 vs 4.33 U=687, p=.019). User performance improved with the AI-CDSS, but with no significant difference between the groups on the best or worst AI performing clips. Nevertheless, for the best AI, senior clinicians had higher median performance in the Enhanced group (0.95 vs 0.90, U=75, p=.066). There was also less dispersion in the Enhanced group when AI was inaccurate (IQR: 0.07 vs 0.21, p=.004). Conclusion: Interface design can improve trust calibration in a surgical AI-CDSS and may increment performance in seniors when AI is accurate, and consistency when AI is inaccurate. In future, these features may form important safety checks during translation to the operating room.

BackgroundCell and gene therapies (CGT) represent a transformative class of medical interventions, yet their high production costs limit patient access. Understanding the structure of manufacturing costs is essential for informing policies that can expand access to these therapies. ObjectiveThis study develops and applies a cost-of-goods-sold (COGS) model to analyze the contributors to manufacturing costs for mRNA-based CGT, with application to a wide range of current and future therapies. MethodsAn Excel-based COGS model was constructed based on cost categories for CGT. Two mRNA-based products at commercial scale were used to populate the model: an mRNA vaccine and a therapeutic mRNA gene therapy. Cost inputs were drawn from vendor pricing, peer-reviewed and grey literature, and expert consultation with CGT manufacturing specialists. Three scenarios (worst, base, and best case) were modeled across six cost categories: materials, consumables, capital, labor, licenses, and royalties. A tornado diagram sensitivity analysis was conducted to identify key cost drivers. The mRNA vaccine was used to build and validate the model strucutre using publicly available data sources. The therapeutic mRNA therapy was used as the main use case for illustration and sensitivity analysis. ResultsUnder base-case assumptions, the estimated cost per dose for the therapeutic mRNA product is $56.09, ranging from $3.68 (best case) to $383.22 (worst case). Licensing and royalty fees together account for approximately 83% of total base-case COGS ($6,996,000 and $6,960,000 per production run, respectively, out of $16,825,597 total). Excluding these fees, material costs represent the largest remaining share (61%), followed by consumables (34%), capital (4%), and labor (1%). Sensitivity analysis confirms that licensing and royalty assumptions are the dominant source of uncertainty in the model. ConclusionsLicensing and royalty fees are the primary driver of mRNA-based CGT production costs and represent the greatest opportunity for cost reduction through policy intervention. Strategic priorities for cost reduction should focus on optimizing reagent utilization, increasing platform potency, and expanding use of contract development and manufacturing organizations (CDMOs) to reduce capital and labor costs. Key PointsProducing an example mRNA gene therapy costs about $56 per dose to manufacture, driven almost entirely driven by fees paid to patent holders for the underlying technology. Licensing and royalty fees cost roughly 83 cents of every dollar spent on these new biopharmaceutical products. Until that changes, the gap between what therapies cost to make and what patients and payers are charged will remain very wide.

BackgroundPharmacogenomic testing (PGx) can optimise drug efficacy and minimise toxicity, but the extent of prescriber adherence to PGx recommendations remains unclear. We aimed to quantify clinician adherence to international genotype-guided prescribing recommendations in a cohort of paediatric oncology patients. MethodsWe reviewed files of children enrolled in the MARVEL-PIC (NCT05667766) randomised control trial, who had PGx recommendations available. Patients were included if 12 weeks had passed since their PGx report was released to clinicians. Prescribing events were identified for actionable PGx recommendations, and classified as "explicitly followed", "inadvertently followed", or "not followed". Adherence was assessed by patient, drug, and recommendation. Results2,063 PGx recommendations were available for 216 patients. 64 (3.1%) recommendations were actionable for 44 patients and 10 drugs within the 12-week study period. Recommendations were explicitly followed in 57/288 (19.8%) of prescribing events, inadvertently followed in 145 (50.3%), and not followed in 86 (29.9%). Mercaptopurine demonstrated the highest rate of explicit adherence (87.5%). No significant associations were observed between adherence and age group, cancer type, drug type, or strength of recommendation. ConclusionAdherence to pharmacogenomic recommendations was very low, highlighting the need to understand barriers to PGx implementation, and consideration of clinical decision supports to facilitate adherence. Plain Language SummaryPharmacogenomic medicine (PGx) looks at how our genes affect our response to drugs, including their effectiveness and toxicity. Through genetic analysis we can create recommendations for drug dosing, avoidance, and monitoring. The MARVEL-PIC study aims to understand if having PGx recommendations decreases the rate of adverse events in children with cancer. We aimed to understand how often prescribers follow PGx recommendations after they are made available, in the MARVEL-PIC trial. To do this, we reviewed medical records and identified relevant prescribing events. We marked these as "recommendation explicitly followed", "recommendation not followed", or "recommendation inadvertently followed" (where the recommendation was followed, but it wasnt clear if this due to PGx). We found that when recommendations were available, they were only explicitly followed in around 20% of cases. In 50% of cases, they were followed but it was unclear whether this was due to PGx. In the remaining 30%, they were not followed. We also found that alerts on our electronic system were fired in about 80% of events where the recommendation was not followed, but did not change the outcome. These findings show that prescriber adherence to PGx recommendations is low. We need to better understand why this is the case and implement more specific tools to assist prescribers in following recommendations. Article HighlightsO_LIPharmacogenomic (PGx) testing can reduce adverse drug reactions by guiding drug choice, dosing, and monitoring. C_LIO_LI!Prescriber to PGx recommendation adherence has not been widely investigated. C_LIO_LIRetrospective analysis showed that explicit adherence to recommendations occurred in only 19.8% of relevant prescribing events. C_LIO_LIIn 50.1% of prescribing events, recommendations were followed, but there was no clear reference to PGx. C_LIO_LIMercaptopurine had the highest explicit adherence (87.5%) from the drugs analysed. C_LIO_LIThere were no statistically significant associations between adherence and age group, cancer type, drug type, or recommendation strength. C_LIO_LIRecommendations were explicitly followed in 29% of events where an interruptive alert was fired, and inadvertently followed in 8%. C_LIO_LITailored interruptive alerts have been shown to increase adherence in other studies, suggesting that the specific design of interruptive alerts may influence adherence. C_LIO_LIWe concluded that explicit prescriber adherence to PGx recommendations is very low (19.8%), and further research needs to be done to understand barriers to implementation. C_LI

Background Virtual Hospital (VH) pathways enable early discharge and are promoted across the NHS. However, evidence supporting their safety, effectiveness, equity, and patient acceptability in elective colorectal surgery remains limited. Objective To evaluate implementation of a VH pathway following elective colorectal surgery and its impact on clinical outcomes, patient-centred recovery, and equality, diversity and inclusion (EDI). Design Retrospective service evaluation with a historical comparator. A 1:1 propensity-matched analysis was performed in colorectal cancer patients using age, sex, body mass index, ASA grade, Charlson Comorbidity Index, procedure type, tumour site, and anastomosis. Setting West Hertfordshire Teaching Hospitals NHS Trust. Patients Patients undergoing elective colorectal surgery between November 2023 and March 2025 managed via a VH pathway, compared with a non-VH cohort. Main outcome measures Primary outcomes were inpatient length of stay (IPLOS), VH length of stay (VHLOS), and days alive and at home within 30 days (DAH30). Secondary outcomes were patient-reported experience and EDI characteristics. Results Eighty-one patients were managed via VH. Median [Q1 - Q3] IPLOS was 2 [1 - 2] days and VHLOS was 2 [2 - 3] days, with no deaths. Forty-two colorectal cancer patients were propensity matched 1:1 to a pre-VH cohort. IPLOS was shorter in the VH cohort (2 [1 - 2] vs 4 [3 - 5] days; p<0.001), and DAH30 was higher (28 [28 - 29] vs 25.5 [24 - 27] days; p<0.0001). Patient experience was positive, with mean satisfaction >8.5/10 and over 90% preferring VH-supported recovery. Sex and ethnicity distributions were similar, although VH patients were younger (p=0.028). Limitations This single-centre retrospective evaluation had a modest sample size and non-randomised design. VH patients were carefully selected, limiting generalisability. Conclusions A VH pathway following elective colorectal surgery is feasible, safe, and acceptable. Compared with a pre-VH cohort, VH care reduced inpatient stay and improved patient-centred recovery without compromising safety.

Background Endoscopic pituitary surgery involves navigating high-stakes anatomy where complications, such as carotid artery injury, cause devastating morbidity. While computer vision AI offers potential for real-time anatomical recognition to mitigate these risks, successful translation requires rigorous human-factors and performance evaluation. We present the iterative development and preclinical evaluation of a surgeon-controlled, real-time AI-assisted navigation system. Methods Guided by IDEAL Stage 0 and DECIDE-AI frameworks, the study was conducted in two phases. Phase 1 was an exploratory study where surgeons used the system during high-fidelity simulated surgery and provided feedback via "Think Aloud" protocols and surveys. Following prototype iteration, a Phase 2 randomized crossover comparative trial was conducted with 19 neurosurgeons (15 trainees, 4 experts) performing high-fidelity simulated tumour resections with and without AI assistance, separated by a minimum 2-week washout. The primary outcome was surgical technical performance (OSATS). Workload, educational value, usability, trust, and implementation outcomes were also assessed. Results Phase 1 informed hardware, model, and interface refinements, including optimized pedal-controlled overlays and prediction confidence metrics. In the comparative trial, AI assistance significantly improved overall technical performance (OSATS 19.79+/-4.06 vs. 17.32+/-4.11; p=0.027). This gain was experience-dependent; AI significantly augmented trainee performance (19.20+/-3.76 vs. 16.60+/-3.78), narrowing the proficiency gap, while expert performance remained high and stable. 100% of participants identified the system as a useful training tool. However, subjective workload was significantly higher in the AI arm (SURG-TLX 26.42+/-9.56 vs. 22.26+/-7.81; p=0.014). Despite this, usability (SUS 75.13+/-14.31) and implementation feasibility, acceptability, and appropriateness scores were consistently high (means >4.4/5). Conclusions This study provides a stepwise process for real-time AI development using pituitary surgery as a high-stakes exemplar. The refined surgeon-centric AI system improves training and technical performance, particularly for trainees. Next steps involve first-in-human studies and further exploration of longer-term human factors such as over-reliance, cognitive overload mitigation and trust calibration.

Breast cancer was the leading cause of cancer-related mortality among women worldwide in 2022. In Kenya, more than a quarter of breast cancer patients have the aggressive Human Epidermal Growth Factor Receptor 2 positive subtype. Trastuzumab is recommended for its treatment, but high costs have limited access. This study evaluated the cost-effectiveness and affordability of trastuzumab-based regimens to inform their adoption and use in Kenya. A cost-utility analysis was conducted from the healthcare payer perspective over a lifetime horizon. Five trastuzumab-based regimens of varying durations (9-week, 6-month, 9-month, 12-month, and 24-month) were compared with chemotherapy alone. Direct medical costs were estimated using a bottom-up micro-ingredient approach. All costs were reported in 2022 USD. A cohort Markov state-transition model with a monthly cycle length was used to estimate the costs and outcomes for an open hypothetical cohort. Scenario, deterministic sensitivity and probabilistic sensitivity analyses were conducted. A budget impact analysis estimated the financial implications of each regimen. The 9-week regimen had the lowest incremental cost-effectiveness ratio (ICER) of USD 3,230 per QALY, while the remaining regimens had ICERs ranging from USD 4,046 to 9,846 per QALY. The findings were most sensitive to the price and quantity utilized per cycle of trastuzumab. A reimbursement cap of KES 40,000 per cycle reduced ICERs by up to 61%. Over five years, the 9-week regimen would account for 1.2% of the projected insurers budget, whereas the current recommended 12-month regimen would consume 2.82%. Although none of the regimens were cost-effective at Kenyas WTP threshold (USD 1054.80), the 9-week regimen may still be considered by policymakers given its greater affordability. Further cost reductions can be achieved through negotiating lower drug prices, improving access to biosimilars, and implementing vial sharing.

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.

National digital health platforms are scaling faster than the evidence on how to finance them. This paper develops a welfare-simulation framework that converts a published willingness-to-pay (WTP) distribution into a prescriptive pricing recommendation, applied to Thailands KhunLook maternal-and-child-health application. Predicted WTP values at the 25th, 50th and 75th unconditional quantiles and the OLS mean -- drawn from a survey of n = 680 Thai parents and relatives of young children previously reported in Lounkaew et al. (2025) -- enter the simulation as parametric inputs. Quintile-level WTP is imputed by monotone-cubic interpolation, a population of 250,000 caregivers is drawn from truncated-Normal distributions around the quintile means, and five financing scenarios are compared: full public provision (S1), a flat market-priced fee (S2), freemium (S3), fine-grained income-tiered pricing (S4), and a means-tested subsidy with a flat fee for the top 60% (S5). A thematic reading of Thai digital-health policy documents bounds the institutionally feasible scenario set and anchors the interpretation of the simulation numbers. Full public provision maximises total welfare at 437.4 million THB but runs a five-year fiscal deficit. The means-tested subsidy gives up about 15% of that welfare to recover 198.6 million THB in net producer surplus, distributes consumer surplus toward lower-income quintiles (concentration index -0.258), and plugs into the existing Thai state welfare card register at near-zero marginal administrative cost. The ranking holds across all twelve sensitivity specifications. Administrative simplicity in subsidy targeting, read against the Thai WTP distribution, dominates finer-grained tiering on both welfare and equity grounds. The framework transfers cleanly to other middle-income countries deciding how to price a national digital health platform. Author summaryMany middle-income-country governments now run free national smartphone apps for the health of mothers and young children, but the funding model is increasingly fragile as initial donor and research grants run out. The question this paper asks is simple: if such a platform had to start charging, what pricing structure would raise the most money without locking out the families who need the app most? Using a published Thai survey of 680 parents and relatives of young children, the paper simulates five alternative designs -- free, flat fee, freemium, fine-tiered by income quintile, and a means-tested subsidy -- and finds that offering the bottom 40% of households free access while charging the top 60% a flat 395 Thai baht per year (roughly USD 11) captures 85% of the welfare of the status-quo free model, generates 199 million baht of fiscal surplus over five years, and distributes benefits toward lower-income users rather than toward the well-off. The design works because Thailands state welfare card register already identifies the low-income target population, so means-testing is essentially free to administer. Other countries with comparable social registries can apply the same logic to their own digital health platforms.

IntroductionAlzheimers disease (AD) is imposing an increasing public health and socioeconomic burden. In China, rapid population ageing is sharply increasing disease burden. Previous studies have shown that AD-related costs are mainly driven by long-term informal care. However, evidence in China remains limited by an incomplete cost framework, and insufficient consideration of caregivers burden and indirect costs. Notably, the National Dementia Action Plan (2024-2030), issued by the Chinese government, marks a major shift to early detection and comprehensive care of AD, highlighting the urgent need for nationally representative economic evidence to support policy implementation. This study aims to evaluate the economic burden and quality of life of AD patients and their caregivers in mainland China, and is the first nationwide study to include individuals with amnestic mild cognitive impairment (aMCI), providing foundational data for future health technology assessment (HTA) of early AD interventions. Methods and analysisBaseline characteristics will be presented and compared using t-tests or chi-square tests. Economic burden will be estimated by calculating the per capita cost and weighted national total based on provincial numbers of AD patients. Indirect costs will be assessed using locally adapted replacement cost approach and forgone wages approach. The analysis will be stratified by disease severity and age. Future burden will be projected by linking data from China Statistical Yearbook 2025 and the United Nations World Population Prospects 2024. Unmet care needs, AD-related catastrophic health expenditure (CHE), and AD dependency ratio (ADDR) will also be assessed. Ethics and disseminationEthics approval was obtained from the Ethics Committee of Xuanwu Hospital, Capital Medical University. The study has been registered at ClinicalTrials.gov and the Chinese Clinical Trial Registry (ChiCTR). The results from this study will be actively disseminated through research articles and conference presentations. Trial registration numberNCT05995418; ChiCTR2300074723. Strengths and limitations of this studyO_LIThis study employs a two-stage probability sampling design across 602 cognitive centres in 31 provinces, ensuring strong national representativeness of the Chinese population. C_LIO_LIIt is the first national health economics study to prospectively include patients with amnestic mild cognitive impairment (aMCI), addressing a critical evidence gap in the early stage of disease and providing data for future evaluation of the cost-effectiveness of early screening and interventions. C_LIO_LIThe integration of clinical characteristics, economic burden, and quality of life scales provides a multidimensional framework for future policy evaluations and health technology assessment (HTA). C_LIO_LIThe calculation of indirect costs relies heavily on caregivers self-reported data regarding care time and missed work, which may introduce recall bias. C_LIO_LIThe use of a nested subsample for the 12-month follow-up may introduce loss-to-follow-up bias, although appropriate statistical weighting techniques will be applied to mitigate this. C_LI

Introduction Creativity is important in surgery for problem-solving in the operating room and the development of surgical innovations that improve patient outcomes. However, our limited understanding of what the characteristics and competencies of the highly creative surgeon are has inhibited our ability to develop the tools, programs and interventions necessary for cultivating the creativity of surgeons. We present the protocol for the INSPIRE Study, which aims to identify the factors associated with high creative achievement in surgeons. Methods and Analysis We have designed a sequential mixed-method study, including a cohort study accompanied by qualitative semi-structured interviews. The primary objective of this study will be to identify factors associated with high creative achievement in surgeons, to be assessed through direct involvement in innovation or invention, or a top score (10 out of 10) on any domain in the Inventory of Creative Activities and Achievements questionnaire. We plan to measure 39 different personal, domain-specific, domain-general, and environmental/motivational variables, chosen based on previous literature and on exploratory grounds, to be assessed as possible factors of creative potential. Multivariable logistic regression is planned, with high creative achievement as the dependent variable and all 39 potential factors of creative potential as independent variables. Ethics and Dissemination Ethics approval from the Hamilton Integrated Research Ethics Board has been obtained and no harm is expected due to participation in this study. To facilitate knowledge translation, we plan to publish the feasibility data and results in peer-reviewed journals, and present at international surgical and creativity conferences.

Background High-risk preoperative triage remains fragmented: existing tools often estimate risk without identifying modifiable mechanisms or linking classification to postoperative monitoring, destination planning, and rescue resources. This protocol describes implementation and evaluation of a Reserve-Stress-Rescue (RSR Framework), pathway that operationalizes perioperative high risk as a mismatch among patient physiologic reserve, procedural stress, and system rescue capacity. Approach RSR is a proposed clinician-facing, modular scoring framework for adults undergoing major surgery, especially patients with frailty, multimorbidity, poor functional capacity, anemia or malnutrition, cardiopulmonary disease, or limited postoperative support. Each domain, Reserve, Stress, and Rescue, is scored from 0 to 4 and recorded as both a three-part profile and a total score from 0 to 12. Scores map to Green, Amber, Red, and Crimson triage bands that trigger escalating actions, including targeted optimization, multidisciplinary review, anesthesia and surgical planning, postoperative destination selection, monitoring intensity, and predefined escalation criteria. Validation Plan The initial phase of this study received an exemption determination from the Yale University Institutional Review Board on June 3, 2026, under IRB Protocol ID 2000042729, with exempt categories 2(ii) and 4(iii), including a waiver of HIPAA authorization for access to and use of protected health information as described in the approved protocol. Evaluation will proceed in stages, assessing feasibility, interrater reliability, completeness, acceptability, discrimination, calibration, and clinical utility. Key outcomes include postoperative complications, unplanned escalation of care, intensive care utilization, failure to rescue, mortality, length of stay, triage burden, low-yield testing cascades, and management-changing pathway activation. Conclusion The RSR pathway reframes high-risk status as a modifiable interaction between vulnerability, operative insult, and rescue capacity rather than a fixed patient label. If feasible and valid, RSR may standardize high-risk identification, align perioperative resources with anticipated physiology, improve communication, and support safer, actionable shared decision-making.

As genetic testing becomes increasingly integrated into Parkinson disease (PD) research, including targeted testing for variants in LRRK2 and GBA1, the return of individual research results is becoming more common. However, limited qualitative data exists regarding how research participants experience genetic results disclosure and post-test genetic counseling in PD research settings. We conducted semi-structured qualitative interviews with participants (n=13) enrolled in the Parkinson Precision Medicine Initiative (formerly Parkinson Progression Markers Initiative; PPMI) who had received PD-related genetic test results and post-test genetic counseling. Interviews were conducted 1 to 3 weeks following result disclosure and analyzed using thematic analysis with a primarily deductive coding approach informed by study aims and inductive identification of emergent themes. Four primary themes were identified: (1) personal connection and motivations for participation, (2) centrality of result disclosure and information preferences, (3) emotional experiences and support needs, and (4) communication quality and alignment with participant needs. Overall, our findings underscore the importance of person-centered genetic counseling within PD research. As return of genetic and biomarker results in research and clinical trial contexts expand, thoughtful integration of relational, informational, and communication-focused practices will be essential to support participant engagement and trust.

Objective: Clinical risk scores intended to guide patient-level decisions can show strong average performance. However, predicted probabilities can be systematically too high or too low in specific subgroups even when overall performance is strong. We audited deployment readiness of a strong end-of-surgery postoperative infection model across clinically relevant subgroups and tested mitigation strategies in miscalibrated subgroups. Materials and Methods: We analyzed out-of-fold predictions for 10,719 surgical procedures at a Swiss tertiary hospital, with 504 postoperative bacterial infection events. Prespecified axes were recorded sex, age stratum, and an EHR-derived physiological-reserve proxy. Within subgroups and pairwise intersections, we evaluated discrimination, calibration, threshold-specific errors, and decision-curve net benefit at the prespecified operating threshold. We compared group-specific isotonic recalibration with Wasserstein-barycenter postprocessing and demonstrated portability in SUPPORT2. Results: Overall AUROC was 0.876. While sex-marginal discrimination was similar in women and men (0.878 vs 0.875), age and reserve stratification revealed deployment-readiness failures. Calibration-in-the-large ranged from -0.86 in frail patients to -2.47 in non-frail patients. At the 0.10 operating threshold, decision-curve net benefit was positive in frail patients but negative in pre-frail and non-frail patients. Isotonic recalibration corrected average physiological-reserve-stratified calibration without worsening Brier scores, whereas Wasserstein postprocessing worsened calibration in most procedure clusters. Discussion: Discrimination-only or sex-marginal evaluation would have missed subgroup failures with clinical-utility implications. Conclusion: Subgroup fairness audits for clinical deployment should jointly evaluate discrimination, calibration, and utility. We implemented the audit as the open-source isitfair framework for identifying deployment-relevant subgroup failures, comparing mitigation strategies, and generating structured reports.

Background Lifestyle interventions can increase the probability of remission of prediabetes to normal glucose tolerance, but their economic value remains unclear. We assessed the within-trial and lifetime-horizon modeled cost-effectiveness of intensive and conventional lifestyle interventions in risk-stratified participants with prediabetes. Methods A health economic evaluation was conducted alongside the 12-month multicenter PLIS trial (n=1,105). High-risk participants were randomized to intensive (HR-INT) or conventional (HR-CONV); low-risk participants to conventional lifestyle intervention (LR-CONV) or control (only short single consultation; LR-CTRL) with risk stratification based on insulin secretion, insulin sensitivity, and liver fat content. Within-trial analyses estimated incremental costs per additional remission to normoglycemia and per quality-adjusted life year (QALY). Lifetime cost-effectiveness was modelled using a four-state Markov Model. Findings At 12 months, HR-INT and LR-CONV increased remission compared with their respective comparators. The incremental cost per additional remission was {euro}7,081 (95% CI: dominated-47,277) for HR-INT and {euro}4,278 (1,312-11,793) for LR-CONV from a health insurance perspective. A willingness-to-pay of {euro}22,000 (HR-INT) and {euro}7,500 (LR-CONV) per additional remission corresponded to 90% probability of cost-effectiveness. Neither intervention was cost-effective in terms of QALYs gained within the 12-months period. Lifetime modelling suggested that both HR-INT and LR-CONV are not only cost-effective, but also cost-saving, relative to HR-CONV and LR-CTRL, respectively. Also in the probabilistic sensitivity analysis, most simulations indicated dominance (71.7% for HR and 88% for LR). Interpretation Based on short-term economic evaluation, the interventions assessed were cost-effective regarding additional participants with remission, not for incremental QALYs gained. Lifetime modelling suggests cost savings for both risk groups. Targeting populations with lifestyle interventions to achieve prediabetes remission seems to generate good value for money in the long term.

In many endoscopic surgical procedures, the surgical team must identify and remove pathological tissue while avoiding critical structures such as arteries and nerves. Augmented reality (AR) offers potential support by overlaying visual information about the location of pathology and critical structures directly onto the operative field, enhancing spatial awareness and surgical navigation. However, limited research has evaluated how best to design and present AR overlays in ways that align with surgical workflow and perception. This study investigates surgeons' preferences across three key AR overlay dimensions: Design (how anatomy is visualised: outlines, heatmaps, masks, or centroids), Trigger (how and when overlays are activated: always visible, activated by the user, or triggered by instrument position), and Placement (where the overlay appears: above or below the surgical instrument). We take endoscopic pituitary adenoma surgery as a high-risk exemplar. Using a web-based prototype, 38 neurosurgeons ranked options and provided qualitative feedback. Surgeons preferred outline designs for clarity, user-activated triggers for control of information flow and distraction minimisation, and below-instrument placement for better spatial awareness. Preferences were consistent across experience levels and emphasised the importance of balancing visual saliency with cognitive load, to facilitate surgical navigation without distraction or disruption. These findings inform AR interface design, but require evaluation for impact on surgical performance and safety in further physical simulation and clinical studies.

BackgroundPhenome-wide association studies (PheWAS) can reveal novel associations between variants in drug-target genes and disease and, as such, can be used to predict new drug-indication pairs for repurposing drugs with a known mechanism of action. A platelet-derived growth factor receptor beta (PDGFR{beta}) PheWAS demonstrated that patients with a single nucleotide variant that reduces PDGFR{beta} expression exhibit a higher prevalence of chronic skin ulcers, skin grafts, and reconstructive surgeries. Recombinant human platelet derived growth factor BB (rhPDGF) is a therapeutic that binds to and activates PDGFR{beta} and has received FDA approval for multiple indications, including improving healing of lower extremity diabetic neuropathic ulcers, augmenting periodontal bone and soft tissue reconstruction, and stimulating orthopedic bone regeneration. Leveraging a drug-repurposing methodology informed by PheWAS, we hypothesize that rhPDGF will provide therapeutic benefit in the treatment of other complex wounds, like full-thickness surgical wounds of the head or neck that cannot heal by primary intention following skin cancer excision. MethodsThis prospective, double-blinded, single-site study aims to enroll 40 participants, randomized at a ratio of 1:1, comparing the efficacy of an advanced wound matrix saturated with rhPDGF or saline. Comparisons will be stratified by anatomical location (scalp/forehead versus face/neck) and maximum surgical defect dimensions (< 3cm versus > 3cm). The primary outcome of this study will evaluate the time in days to 81-100% granulation of the wound bed by expert clinical assessment of daily photographs. Secondary outcomes will assess the superiority of the rhPDGF-enhanced wound matrix relative to control with respect to wound granulation rate, epithelialization, complete wound healing, and patient reported outcomes (PROMs). DiscussionAlthough reconstructive techniques are available for healing complex head and neck wounds following skin cancer excision, these procedures are invasive, and older, frail patients are often suboptimal candidates. There remains a need for less invasive therapeutic approaches that reduce the healing time and mitigate the morbidity associated with chronic wounds. A PheWAS analysis identified complex wounds requiring reconstructive surgery as a novel drug-indication pair for repurposing rhPDGF. This protocol is designed to evaluate the efficacy of an rhPDGF-enhanced advanced wound matrix for healing complex head and neck wounds post skin cancer excision that cannot heal by primary intention. Clinical trial registrationThis trial is registered at ClinicalTrials.gov (NCT06634030).

ABSTRACT Introduction Traditional in-person fracture clinics are often overcrowded and inconvenient for patients. Virtual fracture clinics aim to address some of these concerns by improving the efficiency of the orthopaedic service and reducing unnecessary interventions while maintaining safety and quality of care. The RECITAL trial is a non-inferiority randomised controlled trial comparing follow-up care provided at a virtual fracture clinic for people with acute simple fractures to follow-up care provided at an in-person fracture clinic. This study describes the protocol for an economic evaluation of RECITAL where the primary aim is to investigate the cost-effectiveness of a virtual fracture clinic compared with traditional in-person fracture clinic care from a health system perspective. Methods and analysis The RECITAL trial recruited 312 participants with acute simple fractures and randomised them to receive follow-up care provided at a virtual fracture clinic or follow-up care provided at an in-person fracture clinic. We will conduct a within-trial analysis from a health system perspective (primary analysis), as well as a health service, patient and societal perspective. The economic evaluation will estimate the difference in the cost of resource inputs on an intention to treat basis used by participants in the two arms of the trial, allowing comparisons to be made between the in-person and virtual fracture clinics. Data for intervention costs and healthcare utilisation will be collected from trial records, hospital electronic medical records and district performance units. The results of the economic evaluation will be expressed in terms of incremental cost per utility weight gained at 12 weeks and will be plotted on a cost-effectiveness plane. Bootstrapping by resampling will be used to estimate 95% confidence intervals around costs and outcomes, and to calculate the confidence intervals around the incremental cost-effectiveness ratio. A cost-effectiveness acceptability curve (CEAC) will be plotted, which will provide information about the probability that an intervention is cost-effective, given the level of a decision makers willingness to pay for each additional outcome. Ethics and Dissemination The trail was approved by the SLHD Ethics Review Committee (RPAH Zone) (X23-0200 and 2023/ETH01038). The findings will be disseminated through a peer-reviewed journal and conference presentations. Trial registration number The trial was prospectively registered on the Australian New Zealand Clinical Trials Registry (ANZCTR; 12623000934640)