CMAJ Open

Purpose: High clinical workload is associated with worse patient and hospital outcomes and is a well-established driver of clinician burnout. Trainees may be particularly exposed, shouldering both clinical and educational responsibilities. Evidence-based work design offers a data-driven approach to healthcare work but relies on robust workload measurements. Trainee workload remains poorly characterized, as commonly used metrics (e.g., duty hours, patient census) overlook cognitive and contextual dimensions. This pilot evaluated the feasibility of combining survey-based and electronic health record (EHR) data to characterize internal medicine (IM) trainee workload. Methods: A pilot study was conducted including IM and Medicine-Pediatrics residents (postgraduate years 1-4) between March 31 and June 22, 2025. Participants completed daily surveys during a seven-day inpatient schedule assessing workload and work experience domains, including environment, professional fulfillment, psychological safety, autonomy, and rounding experience, using validated instruments where available. Concurrently, EHR data captured chart review, documentation, orders, and secure messaging activity. Associations between survey and EHR data were assessed. Results: Among 37 eligible residents, 28 (76%) participated in the pilot capturing 166 shifts. Trainees spent 4.4 +/- 1.6 (mean +/- SD) minutes completing daily surveys and 8.6 +/- 2.3 minutes completing the final survey. Trainees reported working 11.6 +/- 1.0 hours/day and a median census of 9.0 (IQR 6.0-11.0). NASA-TLX score was 50.8 +/- 12.6. Positive shift ratings were associated with lower NASA-TLX scores and perceived rounding length. First-to-last EHR login duration was 15 +/- 2 hours/day, and EHR data showed 204 +/- 46 active minutes/day. Login duration correlated with self-reported hours (r=0.43, p<0.0001), and notes signed correlated with self-reported team (r=0.19, p=0.013) and personal census (r=0.34, p<0.0001). Conclusions: Integrating survey-based and EHR-derived workload measures provides multidimensional insight into trainee work. This novel approach supports scalable measurement and evidence-based work design interventions to improve trainee well-being, education, and clinical efficiency.

PurposeTo characterize maternal transport patterns in Iowa, a state with levels of maternal care and without formal perinatal regions, and assess whether transport decisions reflect efficient, risk-appropriate coordination. MethodsWe analyzed 2010-2023 Iowa birth records, which included 2,251 maternal transports between obstetric facilities across 106 unique routes. We characterized transport patterns and applied a community detection algorithm to identify "communities" of obstetric facilities that disproportionately transport among themselves. FindingsSuburban and rural counties have elevated transport rates compared to urban counties. 2,189 transports (97%) were from lower-to higher-level facilities. Among these, 2,037 (93%) were to Level III tertiary care centers. 567 transports (25.2%) bypassed a closer facility offering an equivalent or higher level of care than its destination facility. Health system affiliation was associated with bypassing transport, indicating potential organizational rather than purely geographic drivers of transport decisions. Three "communities" of obstetric facilities largely shaped by geographic proximity were identified. ConclusionsAlthough Iowa does not have formal perinatal regions, patterns of maternal transport are mostly in line with three de facto regions. Some potential inefficiencies were identified, such as obstetric facilities transporting to a farther facility when a closer facility offered the same level of care or higher. These findings may help identify opportunities to enhance care coordination among obstetric facilities, optimize maternal transport networks, and improve regionalization of maternal care.

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.

Background Individuals experiencing or at risk of homelessness face substantial barriers to preventive eye care that are poorly addressed by standard service models. Interdisciplinary optometry-social work collaboration offers a rights-based approach to improving engagement and continuity of care. Methods A convergent mixed-methods study was conducted between February and August 2024 at a multidisciplinary community centre. Clients experiencing or at risk of homelessness received integrated optometry and social work assessment and were prioritised as high, medium, or low based on combined clinical and social risk. Social work follow-up was guided by the Triple Mandate and W-Questions framework. Quantitative data were summarised using mean (SD), median [IQR], or n (%). Qualitative case notes were analysed using content analysis with inductive coding and secondary review for consistency. Results A total of 165 clients had priority categories coded (high: 68; medium: 47; low: 154). Demographic data were available for 132 clients (60% male; mean age 49.5 years [SD 16]); 27% had not completed high school, 89% reported weekly income below AUD 1000, and 28% had vision impairment. Two hundred forty-five case-note entries were consolidated into 146 unique records. SMS (46%) and phone calls (38%) were the most documented contact methods, although only 21% of calls were answered; missed calls (13%) and disconnected numbers (7%) were common. Multi-modal contact was more frequently documented for higher-priority clients. Appointment assistance was the most recorded facilitator (71%), while rights-based supports, including interpreter and transport assistance, were infrequently documented (<=5%). Qualitative analysis identified unstable communication, reliance on informal supports, and service fragmentation as key influences on recall outcomes. Conclusion This study supports an interdisciplinary, rights-based optometry-social work model to address barriers to preventive eye care among people experiencing or at risk of homelessness. Embedding structured handovers and tiered recall processes within community-based services may strengthen continuity and accountability for high-priority clients. Future implementation should evaluate outcomes related to equity of reach, service integration, and sustained engagement in care.

Background: The instability-plasticity framework proposes that multimorbidity trajectories periodically enter instability phases that are vulnerable to escalation but also potentially modifiable through relational intervention. Whether such phases commonly resolve without acute care, or predominantly progress to hospitalisation, has not been quantified at scale. Objective: To quantify instability window outcomes across a longitudinal monitoring cohort; to test whether the characteristics distinguishing admitted from resolved windows reflect within-patient trajectory dynamics or between-patient severity; and to characterise which patient-reported and operator-rated signals reliably precede admission, using both a curated pilot sub-cohort and the full monitoring cohort with an explicit cross-cohort comparison. Methods: Two complementary analyses were conducted on data from the MonashWatch Patient Journey Record (PaJR) relational telehealth system. Instability windows were identified algorithmically (>=2 consecutive calls with Total_Alerts >=3) across the full longitudinal dataset (16,383 calls, 244 patients, 2.5 years) and classified by linkage to ED and hospital admission data. Window characteristics were compared at window, patient, and paired within-patient levels. Pre-admission signal cascades were analysed in two configurations: a curated pilot sub-cohort (64 patients, 280 calls, +/-10-day window, 103 admissions, December 2016-September 2017) and the full monitoring cohort (175 patients, 1,180 pre-admission calls, +/-14-day window, December 2016-July 2019). A three-way cross-cohort comparison decomposed differences between the two configurations into pipeline and population effects. Results: 621 instability windows were identified across 157 patients (64% of the monitored cohort). 67.3% resolved without hospital admission or ED attendance, a rate stable across alert thresholds 1-5. In paired within-patient analysis (n = 70), duration in days (p = 0.002) and multi-domain breadth (p < 0.001) distinguished admitted from resolved windows; alert intensity did not. In the pilot sub-cohort, patient-reported illness prognosis (Q21) was the dominant pre-admission signal (GEE beta = +0.058, AUC = 0.647, p-BH = 0.018). This finding did not replicate in the full cohort: Q21 was non-significant (GEE beta = -0.008, p = 0.154, AUC = 0.507). Cross-cohort analysis identified selective curation of the pilot sub-cohort as the primary explanation. In the full cohort, six signals escalated significantly before admission after Benjamini-Hochberg correction: total alerts, health impairment (Q26), red alerts, self-rated health (Q3), patient concerns (Q1), and operator concern (Q34). Health impairment achieved the highest individual AUC (0.605) and showed the longest pre-admission lead. No individual signal exceeded AUC 0.61. Conclusions: Two thirds of instability phases resolve without hospitalisation, providing direct empirical support for trajectory plasticity as a clinically frequent phenomenon. Within the same patient, persistence - in duration and in the consistency of high-severity multi-domain flagging across calls - distinguishes trajectories that tip into admission from those that resolve. The Q21 signal reversal between cohorts illustrates how selective curation can produce compelling but non-replicable findings in monitoring research. In the full population, objective alert signals and operator judgement, rather than patient illness prognosis, carry the pre-admission signal

BackgroundTimely cancer diagnosis in children and adolescents is critical to improving outcomes, yet substantial variation in diagnostic intervals persists across cancer types and care settings. We aimed to quantify time to diagnosis and assess variations by patient, demographic, and system-level factors. MethodsWe conducted a retrospective population-based study of children and adolescents aged 0-19 years diagnosed with one of 12 common cancers between 2010 and 2022 in Quebec, Canada. The diagnostic interval was defined as the time from first cancer-related healthcare encounter to diagnosis. We calculated medians and interquartile ranges (IQR) overall and by cancer type and used multivariable quantile regression to identify factors associated with time to diagnosis at the 25th, 50th, and 75th percentiles. ResultsAmong 2,927 individuals with cancer, diagnostic intervals varied by cancer type and age. Median intervals were longest for carcinomas (100 days; IQR 33-192) and shortest for leukemias (8 days; IQR 3-44). Compared with children living in Montreal, living in regional areas and other large urban centres was associated with longer 50th and 75th percentiles of time to diagnosis for hepatic and central nervous system (CNS) tumours. Diagnostic intervals were shorter in the post-pandemic period (2020-2022) across several cancer sites, with CNS tumours showing reductions across all quantiles. InterpretationDiagnostic timeliness differed by cancer type, age, and rurality, but not by sex, material, or social deprivation. The shorter diagnostic intervals observed in the post-pandemic period suggest that pandemic-related changes in care pathways may have expedited diagnosis for some cancers.

BackgroundThe COVID-19 pandemic significantly accelerated the adoption of telemedicine, but it also exposed gaps in effective remote clinical assessment, particularly for medically vulnerable patients in rural areas. The ORCHARD intervention aimed to address this by providing patients with a Medical Self-Assessment Box to enable self-reporting of vital signs during remote consultations. MethodsA single-centre randomised mixed-methods feasibility trial recruited medically vulnerable patients from a rural general practice in Northeast Scotland. Participants in intervention group received a home medical equipment box for use during telemedicine consultations over six months. Patients and GPs were interviewed and transcripts were analysed using Framework Analysis. ResultsTwelve (15%) of 82 eligible invited patients enrolled. Six each were allocated to intervention and control group. 50%(n=3)patients in intervention group used equipment in 45%(5 of 11)teleconsultations and rated it helpful in all 5 uses (100%). The intervention group had 18% fewer primary care contacts than controls. All remote consultations were by telephone. Framework Analysis of patient interviews identified facilitators such as ease of use, improved triage access, reassurance, and barriers related to GP non-engagement and written instructions. GP interviews identified clinical value in patient-generated readings, alongside concerns regarding workload and patient over-monitoring. ConclusionsHalf of intervention participants used the medical-equipment box during remote consultations, all finding it useful, though frequency of use varied among particpants.A randomised controlled trial to evaluate the effectiveness of the Medical Self-Assessment Box for optimising remote consulting in medically vulnerable rural patients is feasible.Prior to a definitive trial refinements are recommended to patient labelling, GP engagement, and training materials.

BackgroundSouth Africas public healthcare system serves most of the population through approximately 3,900 primary healthcare clinics characterised by long waiting times and high volumes of repeat-prescription visits. No published pre-arrival digital triage system operates across all 11 official South African languages while aligning with the South African Triage Scale (SATS). This paper reports the design and preliminary safety validation of BIZUSIZO, a hybrid deterministic-AI WhatsApp triage system. MethodsBIZUSIZO delivers SATS-aligned triage via WhatsApp, combining AI-assisted free-text classification (Claude Haiku 4.5) with a Deterministic Clinical Safety Layer (DCSL) that overrides AI output for 53 clinical discriminator categories (14 RED, 19 ORANGE, 20 YELLOW) coded in all 11 official languages and independent of AI availability. A five-domain risk factor assessment can only upgrade triage level. One hundred and twenty clinical vignettes in patient language (English, isiZulu, isiXhosa, Afrikaans; 30 per language) were scored against a developer-assigned gold standard with independent blinded nurse review. A 121-vignette multilingual DCSL safety consistency check across all 11 languages and a 220-call post-hoc framing sensitivity evaluation (110 paired vignettes) were also conducted. ResultsUnder-triage was 3.3% (4/120; 95% CI: 0.9%-8.3%) with no RED under-triage; exact concordance was 80.0% (96/120) and quadratic weighted kappa 0.891 (95% CI: 0.827-0.932). One two-level under-triage was observed on a non-RED presentation (V072, isiXhosa burns vignette, ORANGEGREEN); one two-level over-triage was observed (V054, isiZulu deep laceration, YELLOWRED). In the framing sensitivity evaluation, AI-only classification achieved 50.9% RED invariance under adversarial framing; full-pipeline classification achieved 95.0% in four validated languages, with the DCSL rescuing 18 of 23 AI drift cases. ConclusionsA hybrid deterministic-AI triage system with DCSL-based emergency detection achieved zero RED under-triage and consistent RED detection across all 11 official languages. The 16.7% over-triage rate falls within published South African SATS ranges (13.1-49%). A single two-level under-triage event was observed on an isiXhosa burns vignette (ORANGEGREEN) and is discussed in Limitations. Findings are preliminary; prospective validation against independent nurse triage is the necessary next step.

ObjectivesTo evaluate the effect of surgical hubs on the volume of surgeries, patient waiting times, and length of hospital stay for elective hip and knee replacements in the English NHS. DesignA retrospective longitudinal study using a difference-in-differences approach to compare changes in outcomes at NHS trusts that opened surgical hubs with those that did not. SettingThe study was set in the English NHS, using administrative data from NHS acute trusts providing elective hip and knee replacements between April 2014 and September 2024. ParticipantsThe study included 76 NHS trusts. The treatment group consisted of 29 trusts that opened a surgical hub for trauma and orthopaedic surgery during the study period. The control group consisted of 47 trusts that did not. 48 trusts that performed fewer than 1,000 relevant procedures over the ten-year period or that reported data for fewer than 41 of the 42 quarters in the sample period were excluded. InterventionThe phased introduction of surgical hubs dedicated to elective procedures at 29 NHS trusts between Q1 2020 and Q3 2024. Main outcome measuresThe three main outcomes were, measured at the trust-quarter level: the total number of elective primary hip and knee replacements (surgical volume), the average length of stay in hospital, and the average waiting time from being added to the waiting list to hospital admission. ResultsThe opening of a surgical hub was associated with an increase of 43.75 hip and knee replacement surgeries per quarter (95% CI: 22.22 to 65.28), which represents a 19.1% increase compared to the pre-hub mean. Length of stay was reduced by 0.32 days (95% CI: - 0.48 to -0.16), a 7.8% reduction. There was no statistically significant effect on average waiting times (-14.96 days, 95% CI: -33.11 to 3.19). ConclusionsSurgical hubs appear to be effective at increasing the number of hip and knee replacements and reducing the time patients spend in hospital. However, in this study, they did not lead to a statistically significant reduction in waiting times overall.

Importance Missed outpatient appointments, including no-shows and cancellations, may disrupt continuity of care and be associated with worse outcomes, but long-term system-wide patterns and clinical implications are not well characterized. Objective To characterize variation in missed appointment rates in the Veterans Health Administration (VHA) over time and by geographic location, visit modality, and preexisting conditions, and to evaluate associations between missed appointment rates and adverse outcomes among veterans with posttraumatic stress disorder (PTSD) or traumatic brain injury (TBI). Design Cohort study using VHA Corporate Data Warehouse outpatient appointment data from January 1, 2000, through December 31, 2024. Setting National integrated health care system of the VHA. Participants System analysis includes all scheduled outpatient appointments with a valid status, and outcome analysis includes veterans with PTSD (n = 1 429 890) or TBI (n = 554 553), diagnosed before 2023. Exposures For system -level analyses, missed appointment rates were calculated. In outcome analyses, 2023 missed appointment rates were categorized into tertiles within the cohort and appointment type. Main Outcomes and Measures One year risks of all-cause hospitalization, all-cause mortality, and hospitalization or death beginning January 1, 2024. Results Among 2,162,520,880 outpatient appointments from 2000 to 2024, 6.5% were no-shows and 25.4% were canceled. Across facilities, no-show rates ranged from 3.5% to 14.1%, patient-initiated cancellation rates from 9.7% to 26.0%, and clinic-initiated cancellation rates from 8.5% to 17.9%. In 2023, veterans with amputation, Parkinson disease, PTSD, or TBI had higher missed appointment rates than veterans without these conditions. Among veterans with PTSD, the highest no-show tertile, compared with none, was associated with higher mortality (HR, 1.91; 95% CI, 1.84-1.98) and hospitalization or death (HR, 1.07; 95% CI, 1.05-1.08). Among veterans with TBI, the highest no-show tertile was associated with hospitalization or death (HR, 1.65; 95% CI, 1.61-1.69). Conclusions and Relevance Missed outpatient appointments were common in the VHA and varied substantially across facilities and over time. Among veterans with PTSD or TBI, higher missed appointment rates, particularly no-shows, were associated with increased risks of hospitalization and mortality, suggesting that these patterns may help identify high-risk veterans for targeted outreach.

ObjectivesRising temperatures are a major climate-related hazard for U.S. workers, increasing heat-related illness and a broad range of occupational injuries through indirect pathways often overlooked in economic evaluations. We examined the association between temperature and occupational injury and illness and quantified heat-attributable injuries (including illnesses) and costs in New York State. MethodsWe conducted a time-stratified case-crossover study of 591,257 workers compensation (WC) claims during the warm season (2016-2024). Daily maximum temperature was linked to injury date and county and modeled using natural cubic splines, with effect modification by industry and worker characteristics. ResultsInjury risk increased with temperature, becoming statistically significant at approximately 78{degrees}F. Relative to 65{degrees}F, injury odds increased to 1.06 (95% CI: 1.01-1.10) at 80{degrees}F, 1.12 (1.07-1.18) at 90{degrees}F, and 1.17 (1.11-1.23) at 95{degrees}F. Overall, 5.0% of claims (2,322 annually) were attributable to heat. At temperatures [&ge;]80{degrees}F, an estimated 1,729 excess injuries occurred annually, generating approximately $46 million in WC costs. An estimated $3.2 million to $36.1 million in medical expenditures were associated with incomplete claims, likely borne outside the WC system. ConclusionsThese findings demonstrate substantial economic costs not fully captured within WC and support workplace heat protections as a cost-containment strategy that can reduce health care spending and strengthen workforce resilience.

Background Continuous Quality Improvement (CQI) is a core strategy for strengthening health systems, yet documentation and monitoring of CQI activities remain fragmented in many low- and middle-income country (LMIC) settings. In Jamaica, CQI has been institutionalized across priority programs, but it largely relies on paper-based tools and basic digital platforms that limit timely learning and oversight. To address these gaps, Jamaicas Ministry of Health and Wellness (MOHW), in collaboration with the Caribbean Training and Education Centre for Health (C-TECH), adapted a web-based CQI application using a participatory, human-centered design approach. Methods We conducted a formative, convergent mixed-methods evaluation across 24 healthcare facilities to assess early-stage implementation of the CQI app. Guided by the Implementation Outcomes Framework, we examined acceptability, adoption, appropriateness, and feasibility. Quantitative data were collected through a structured survey of healthcare workers (n=43), and qualitative data were gathered through five focus group discussions (n=33) and three key informant interviews with CQI leads. Survey data were summarized descriptively, and qualitative data were analyzed using rapid qualitative analysis. Findings were integrated using joint displays. Results Survey findings indicated moderate to high perceived acceptability and appropriateness of the CQI app, with 70% of participants reporting that it saved time and 67% noting that it aligned with facility goals. However, 19% reported never using it. Qualitative findings highlighted the apps value for improving CQI documentation, visualizing trends, and supporting supervisory oversight. Key barriers to sustained adoption included inconsistent internet connectivity, limited follow-up training, unclear team roles, and challenges integrating app use into routine workflows. Leadership engagement and alignment with existing CQI structures emerged as critical enablers. Conclusion This formative evaluation suggests that a digitally enabled CQI platform can strengthen documentation and oversight of quality improvement activities in resource-constrained health systems when embedded within supportive organizational and infrastructural contexts. Addressing foundational system readiness, including leadership engagement, capacity-building, and workflow integration, will be essential to realizing the CQI apps potential in Jamaica and similar LMIC settings.

Objectives: For suspected hip fractures, prehospital protocols directing patients to an orthopaedic centre rather than the nearest emergency department (ED) could reduce time-to-surgery but may impact EMS travel burden. This study evaluates the impact of transfer protocols by quantifying transport to hospitals from long term care (LTC) facilities across Ontario. Methods: A retrospective cross-sectional analysis of all Ontario LTC facilities and hospitals was performed. Two protocols were modeled: standard transfer to the nearest ED with subsequent transfer if required, and selective transfer based on Collingwood Hip Fracture Rule prehospital screening1 directly to the nearest orthopaedic services (orthoED). Median one-way travel distances were calculated from Google Maps. Results: In Ontario, 15.4% of LTC residents require hospital destination decisions because their nearest ED lacks orthopaedic services; for these facilities, median distances were 2.7km to the ED and 36.0km to the orthoED. Among the 52 LTC facilities where selective transfer was distance-optimal, it substantially reduced travel for patients with hip fracture (31.1km vs 49.6km; P<.01) while only modestly increasing travel for patients without hip fracture. Where standard transfer was distance-optimal, little travel difference was noted for patients with hip fracture, however false positive screened patients traveled significantly further to an orthoED. Greatest negative consequences of selective transfer lie in the 1.3% of residents living farthest (>100km) from an orthoED. Conclusions: EMS direct transportation to hospitals with orthopaedics may improve hip fracture care but can increase EMS burden due to patients identified falsely as having a hip fracture, particularly in remote communities.

Background While a mobile lung cancer screening (mLCS) program can mitigate barriers to access, this study conducted a survey study to assess barriers and facilitators to mLCS which could inform the implementation of new mLCS programs or inform modifications to existing programs. Methods Patient eligibility included current age of 50 to 80 and had undergone any cancer screening at Moffitt Cancer Center (MCC) between January 1, 2023 and December 1, 2024. A web-based survey was administered from May 2025 to June 2025 which collected data on health behaviors, barriers, facilitators, screening preferences, and demographics. Descriptive statistics were used to quantify survey responses. Results Among participants who completed the survey, 73.4% reported no concerns about getting screened in a mobile screening unit, 67.9% reported concerned about the cost or if insurance covered mobile lung cancer screening, and 82.4% reported they would be screened if a voucher or insurance would pay for it. For preferences, 54.1% reported no preference for the time of year for a mobile screening event, 59.6% reported they will be willing to wait up to 30 minutes to get screened, and 44% would travel more than 20 minutes to get screened. There were no statistically significant differences in barriers and facilitators when the analyses were stratified by LCS eligibility. Conclusions We found acceptability of mobile lung cancer screening and preferences that are actionable including daytime weekday events, indoor waiting, short waits, proximity to home, clear cost coverage, and streamlined clinician recommendation.

Study Design: Prospective observational study using a novel digital ledger technology (DLT)-based crowdsourcing platform. Objective: To develop and evaluate Spine Reviews, a blockchain-based platform for aggregating spine treatment recommendations from an international specialist panel, and to validate the clinical coherence of the resulting dataset. Summary of Background Data: Predictive models for low back pain treatment are limited by small, homogeneous datasets that fail to capture inter-clinician variability. Traditional multi-center data collection is expensive, slow, and geographically constrained. DLT-based crowdsourcing with cryptographic credentialing may overcome these barriers. Methods: Five hundred synthetic patient vignettes (digital twins) were generated; 463 retained after quality control. A review platform was built on the Solana blockchain using non-transferable Soulbound Tokens (SBTs) for credentialing and smart-contract compensation. Fifty-two specialists from 7 countries provided 4+ reviews per vignette across four treatment tiers, without access to imaging or physical examination. Mixed-effects regression with reviewer random intercepts partitioned decision variability. Results: The platform collected 2,066 completed reviews (97.7%) over 37 days at USD 0.97/review. Variance decomposition revealed that 36.7% of treatment tier variability was attributable to patient presentation, 19.2% to reviewer practice style, and 44.1% to their interaction. Neurological deficits (beta=0.39), symptom duration (beta=0.12), and pain (beta=0.09) independently predicted treatment escalation (all p<0.001). Gwet's AC1 was almost perfect for emergency (0.92) and substantial for conservative decisions (0.67). Reviewer confidence in treatment recommendations decreased with escalating tier severity (conservative 4.59/5 vs surgical 4.05/5), suggesting appropriate uncertainty calibration. Conclusions: DLT with SBT credentialing enables rapid, global, cost-effective aggregation of clinically coherent expert judgment. The three-component variance structure quantifies clinical equipoise in spine care and establishes that predictive models require diverse, multi-reviewer training data. Keywords: digital ledger technology; blockchain; crowdsourcing; clinical decision-making; low back pain; Soulbound Tokens

Background Emergency departments (EDs) in high-income countries face rising demand, workforce shortages and crowding. We investigated whether prehospital point-of-care blood gas analysis (BGA), used by emergency physicians, is associated with higher ambulatory treatment rates and improved patient selection for hospital admission. Methods We retrospectively analysed routinely collected data from a pilot implementation of a mobile blood gas analyser in physician-staffed emergency medical services (EMS) in Jena, Germany (July 2023 to May 2024). Adult emergency patients receiving prehospital BGA were compared with propensity score-matched EMS controls without BGA. Primary outcomes were the proportion treated on scene and, among transported patients, the hospital admission rate. Secondary outcomes were 30-day safety among ambulatory patients and associations between BGA parameters and disposition. We used standardised mean differences to assess balance and receiver operating characteristic analysis for lactate thresholds. Results Of 109 patients receiving prehospital BGA, 98 met inclusion criteria after excluding 9 patients with missing NACA scores, 1 on-scene death and 1 invalid age record; these were matched to 390 controls (total n = 488). Baseline demographics, severity and vital signs were well balanced. Ambulatory treatment was markedly higher in the BGA cohort compared with matched controls (27.6% vs 8.7%; OR 3.98, 95% CI 2.26 to 7.01; p<0.001). No ambulatory BGA patient required ED re-attendance or repeat EMS contact within 30 days. Among transported patients, 58% in the BGA cohort were admitted to hospital, compared with an overall regional ED conversion rate of approximately 30%. Lactate [&ge;]2.6 mmol/L was the most influential parameter for disposition decisions, with elevated lactate and acid-base disturbances strongly associated with transport and admission. Conclusion Prehospital BGA was associated with fourfold higher ambulatory treatment rates (27.6%) and a twofold higher ED conversion rate among the patients who were transported (58%), indicating improved risk stratification and resource allocation. These findings suggest that integrating objective biochemical data into prehospital assessment may enhance treat-and-refer decision-making and support more efficient use of limited emergency care capacity.

Background Trials in occupational populations, such as surgeons, face feasibility challenges due to high workload, restricted availability, and clinical heterogeneity, which may compromise recruitment, adherence, and retention. Objective To prespecify the feasibility framework and progression criteria for an internal pilot phase embedded within a pragmatic randomized controlled trial (RCT) comparing Mechanical Diagnosis and Therapy with generalized exercise in surgeons with chronic spinal pain. Design Protocol for a prespecified internal pilot phase embedded within a pragmatic, two-arm, parallel-group RCT. Methods The internal pilot will include the first four months of recruitment and aims to randomize at least 12 participants. Feasibility will be assessed across predefined domains, i.e., recruitment, eligibility, consent, intervention uptake, adherence, retention, data completeness, and treatment fidelity. Each domain is operationally defined and linked to prespecified progression criteria to ensure interpretability and decision-making utility. Criteria will be interpreted collectively to guide trial continuation. A minimal qualitative process evaluation will be embedded. Ethics and dissemination The host trial has received ethical approval (N-20240046) and is registered at ClinicalTrials.gov (NCT07293130). The findings from the internal pilot will be reported in a separate feasibility manuscript.

Background and ObjectivesPatient portals have become essential infrastructure for healthcare delivery following the 21st Century Cures Act, yet adoption remains inequitable. Understanding demographic and geographic determinants of portal activation is critical for addressing digital health disparities, particularly among neurology patients who face unique access barriers. We examined the demographic, geographic, and neighborhood-level factors associated with patient portal activation among neurology patients at multiple geographic scales in the Washington, DC metropolitan area. MethodsWe conducted a retrospective cohort study of 72,417 adult neurology patients seen at two academic medical centers sharing an electronic health record in Washington, DC (February 2021-February 2026). We examined portal activation using multivariable logistic regression and geographic analysis at four nested scales: the metropolitan catchment area, DCs eight wards, individual census tracts (via geocoded patient addresses), and individual DC residents. ResultsPortal activation was 64.7% overall. Activation varied by race/ethnicity (Non-Hispanic White 76.1%, Non-Hispanic Black 57.0%, Non-Hispanic Asian 57.6%, Hispanic 55.0%) and geography (DC Ward 2: 82.0% vs. Ward 7: 48.0%). Ward-level educational attainment (r = 0.948), broadband access (r = 0.889), and income (r = 0.811) were strongly correlated with activation. Within individual wards, Non-Hispanic White patients activated at 84-91% while Non-Hispanic Black patients activated at 48-64%, demonstrating that neighborhood resources alone do not explain disparities. DiscussionPatient portal activation is shaped by demographic, socioeconomic, and geographic factors operating at multiple levels. Persistent within-ward racial disparities indicate that geographically targeted interventions must be paired with culturally tailored approaches to achieve digital health equity.

Background Ever since the COVID-19 vaccine became available, vaccinations in adolescents lagged behind adults. Whether adolescent vaccination rates were higher in states with "Minor Consent" policies remains unknown. Methods We accessed adolescent (aged 12-17) county-level vaccine administration data from the CDC (12/2020-05/2023). Our outcomes were COVID-19 vaccination counts for: 1) initial dose, 2) completed series doses, and 3) booster doses. Panel Poisson regression models with state and time random effects, seasonal fixed effects, log-population offsets, and adult vaccination rates were estimated to calculate incidence rate ratios (IRR), testing the association between residing in a state with a Minor Consent policy and COVID-19 vaccine uptake. Results Overall, for the initial dose and complete series, there was no difference in adolescent COVID-19 vaccination between states with or without Minor Consent policies. However, we found that Minor Consent policies were associated with lower COVID-19 booster doses (IRR = 0.582; 95% CI: 0.409, 0.828; p = 0.0026). This association was not found in urban counties (IRR = 0.867; CI = 0.722, 1.043; p = 0.1295), but only in rural counties (IRR = 0.541; CI = 0.401, 0.730; p < 0.0001). Conclusions Minor Consent policies were not associated with higher adolescent COVID-19 vaccination. Rather, we found that Minor Consent policies were associated with lower adolescent vaccination for booster doses in rural counties. Despite minimal evidence of impact, states continue to implement Minor Consent vaccination policies. Future research should investigate not just other vaccines, but also how Minor Consent policies impact parental trust in public health more broadly.

Background/Objectives: Women+ (e.g., women and individuals assigned female at birth) experience disproportionate health risks and persistent gaps in access to care, despite regionally coordinated health systems. Women+ health research remains significantly underfunded and understudied, contributing to inequities in diagnosis, treatment, and outcomes. This study aims to collaboratively identify and prioritize the most pressing unanswered research questions related to women+ health in the Maritime provinces of Canada. Methods: This study will use a modified Priority Setting Partnership (PSP) methodology based on the James Lind Alliance framework. A mixed-methods participatory approach will be used, including bilingual online surveys (French, English) and a one-day consensus workshop. Participants will include women+, healthcare professionals, researchers, policymakers, and the public residing in the Maritime provinces (Nova Scotia, New Brunswick, and Prince Edward Island). An initial survey will collect research uncertainties through open-ended questions. A second interim survey will rank verified uncertainties, followed by a facilitated workshop to achieve consensus on the Top 10 research priorities. Qualitative data will be analyzed using content analysis, and descriptive statistics will summarize participant demographics. Anticipated Results: This project is expected to generate a collaboratively developed, evidence-informed Top 10 list of research priorities for women+ health in the Maritimes. The process will also identify thematic gaps in existing research and assess feasibility considerations to inform future study design and implementation. Conclusions: By centering women+ voices and engaging diverse interest holders, this study will establish a shared regional research agenda to guide future research, funding, and policy initiatives for women+ health research.