Health Policy

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

Abstract Objective To describe variation in hospital costs among children with different combinations of health conditions, special educational needs or disability (SEND) and children social care (CSC) indicators. Study Setting and Design This cross-sectional study used regression analysis to test whether two-way and three-way interactions of cross-public sector service use (health, education and social care) are associated with higher hospital costs in England. Data Sources and Analytic Sample Hospital care costs between April 2022 and March 2023 for the 8.9 million children aged 5-18 years were obtained from linked administrative hospital, education or social care data in the ECHILD database. Children were classified into eight categories based on combinations of indicators of chronic health conditions, SEND or CSC. Principal Findings Over one-third (35.4%) of children had some hospital costs during the year. Average costs were 317GBP for all children and 895GBP for children with non-zero hospital costs. By age 18, few children had no indicator in any sector (35.1% of boys, 43.7% of girls) and indicators in all three sectors were not rare (7.1% of boys, 6.2% of girls). At age 5, children with indicators recorded in all three sectors had the highest hospital costs (2,952GBP for boys and 3,674GBP for girls). At age 18, males and females with indicators in all three sectors accounted for 21% and 23% of hospital costs, respectively. SEND and social care indicators without chronic health conditions were associated with only slightly higher hospital costs. Hospital costs were much higher for children with SEND if they also had a chronic health condition. Hospital costs were only higher for children with social care if they also had both a chronic health condition and SEND. Conclusions. Taking account of additional support from non-health sectors is important for understanding health sector costs. The compounding associations between use of other public sectors on health sector costs indicates scope for targeting of integrated care.

Background: Clinician-scientists translate clinical observation into discovery, trials, and policy, yet this workforce is shrinking across health systems worldwide. Integrated MB-PhD training, pausing medical training to complete a PhD before clinical exposure or specialisation, is one route into this career. We aimed to evaluate the long-term value of MB-PhD training and the barriers to clinical-academic careers these face after graduation. Methods: We evaluated all 131 graduates (29.8% female) who entered the University College London (UCL) MB-PhD programme over a 25-year period (1994-2018). Bibliometric outputs were collated via an inter-linked information system. Concurrently, all 131 graduates were invited to respond to open-ended questions on career benefits and structural barriers; 99 (75.6%) responded, and responses were independently coded into themes, which were then reviewed and confirmed by a Study Group of 107 individuals, including the 91 respondents who agreed to participate further. Results: Graduates produced 5,877 publications (1,141 first-author, 819 corresponding-author), attracting 350,754 citations, with a mean relative citation ratio of 3.30 {+/-} 0.47, approximately three times the field average and sustained across three decades of programme entry. Graduates secured an estimated $157.55 million across 99 grants, released 465 public datasets, and were named investigators on 31 clinical trials across five continents. Among the 99 survey respondents, 49.5% held consultant-grade posts, 72.7% remained research-active, and 25.3% had reached senior academic grade. Open-ended responses were coded into five recurring structural barriers, subsequently confirmed by the Study Group: insufficient protected research time (72.2% of responses), unsupportive training structures and limited career opportunities (36.7%, 24.4% of responses), funding and pay barriers (22.2% of responses), and lack of mentorship or geographical/family constraints (14.4%, 13.3% of responses). Conclusions: Integrated MB-PhD training generates sustained academic productivity and leadership, but structural barriers threaten retention of graduates within clinical-academic careers. Protecting research time, stabilising funding and pay, and reducing geographic instability are needed to retain the clinician-scientists that health systems have already invested in training.

Objectives Emergency department (ED) crowding is recognised as an important public health concern internationally, and is driven principally by exit block, the shortage of inpatient beds for patients requiring admission. This study aimed to evaluate whether a complex intervention targeting hospital occupancy improved ED patient flow, and quantified the change in attendances. Methods A controlled interrupted time series using weekly, publicly reported Public Health Scotland data from 1 January 2022 to 1 February 2026. The multi-component intervention focused on reducing hospital occupancy and included additional adult social care funding; engagement with regional social care providers; accelerated implementation of the Discharge without Delay programme; re-evaluation of whole-hospital escalation thresholds and response; resource and data supporting inpatient department reductions in length of stay; and additional investment in remote clinical assessment. The intervention commenced at a large tertiary ED on 01 February 2025. Primary outcomes were the proportions of attendances spending [&ge;]4, [&ge;]8 and [&ge;]12 hours in the ED. The secondary outcome was attendance volume. Segmented regression was fitted with a contemporaneous control series, seasonal terms and autoregressive moving average errors. Long waits were additionally illustrated as potentially avoided deaths. Results The analysis covered 161 pre-intervention and 52 post-intervention weeks. Relative to pre-intervention levels, the proportion of attendances waiting over 4 hours fell by 10.4% (95% CI 1.6 to 19.2%), by 16.4% (95%CI 1.3 to 31.5%) over 8 hours and by 24.3% (95%CI 2.6 to 46.1%) over 12 hours. Using established associations between long ED waits and excess mortality, by one-year the intervention was potentially associated with 54 fewer excess deaths (95%CI 19 to 93). Attendances rose by 3.8% (95%CI 1.3 to 6.4%) against the counterfactual. Conclusions A complex intervention targeting hospital occupancy was associated with a reduction in long ED waits despite rising attendances. Interventions addressing hospital occupancy can meaningfully improve ED crowding.

Background: Under the DRG/DIP payment reform, the cost structure and its driving factors for laparoscopic cholecystectomy (LC) in resource-limited plateau regions remain unclear. Methods: Based on a single-center cohort of 605 plateau LC patients from May 2020 to October 2025, natural log transformation was applied to total hospitalization costs. Pearson/Spearman correlation, multivariate linear regression (traditional clinical model vs system-driven model with year dummies), and quantile regression were used. Results: Mean hospitalization cost 8097.49+/-936.85 CNY, CV=11.6%, Gini=0.062, demonstrating high homogenization. Traditional six-variable clinical model yielded R^2=0.008 (F=0.78, P=0.587), no significant predictors. The system-driven model achieved R^2=0.143 (F=3.42, P=0.001), with year dummies as dominant predictors. The study proposes the SAO (System-Allocation-Outcome) paradigm to replace the traditional SPO framework.

Background Although often perceived as a technical tool, a data bank is fundamental for district performance management, facilitating integrated coordination, data consolidation, and routine information use for decision-making. However, implementation unfolds within hierarchical bureaucratic systems shaping authority distribution, workload allocation, coordination, and resource use. This study examines the political economy of institutionalizing a district-level health data bank in West Sumbawa District, Indonesia. Method A longitudinal qualitative case study was conducted in West Sumbawa District, West Nusa Tenggara Province, Indonesia, from November 2025 to March 2026 across three evaluation phases (baseline, midline, endline), involving 25 District Health Office (DHO) officers appointed to the Health Data Bank team, representing five organizational units, including the Secretariat, General and Human Resources Unit, and Public Health Division. Data were collected through participatory workshops, focus group discussions, in-depth interviews, observation, and document review, including official decrees, SOPs, meeting minutes, and implementation records, and analysed using Bossert's Decision Space Framework combined with a problem-driven political economy analysis examining how power relations, institutional norms, workload, resource support, and perceived incentives influenced whether technical reforms became operationalized in routine practice. Results The Health Data Bank progressed from strong institutional acceptance to structural formalization. Decision-making authority remained centralized within the Secretariat, enabling coordination but limiting distributed ownership. Resource constraints increased workload, concentrated in the Secretariat and division coordinators responsible for data consolidation and validation, without dedicated financing or staffing, despite improved analytical capacity. Accountability mechanisms were established through governance instruments, though enforcement and feedback loops remained underdeveloped. Data submission, validation, and use were not yet fully institutionalized, resulting in a gap between structural readiness and functional use. Conclusion Data institutionalization involves both technical and organizational processes, requiring collaborative negotiation of authority, workload, and resources. Continued attention to these factors will help structural formalization translate into sustainable operational outcomes.

Background: Internationally, workforce planning models are focussed on balancing supply and demand, rarely addressing factors such as demographic shifts and evolving health needs. There is a clear imperative for improved workforce planning to ensure adequate staff numbers to deliver audiology safely and effectively but there is still no consensus on safe minimum staffing levels or the optimal skill mix for high-quality audiology services. Methods: This research aimed to establish markers of quality in audiology service provision and estimate the audiology workforce requirements to meet current and projected demand for services, based on population changes and anticipated changes in demand. Following stakeholder engagement, a needs-based model was developed by (1) analysing NHS England's national Audiology stocktake dataset to determine current workforce, (2) creating an epidemiological model to predict changes in service population over next 5 and 10 yrs (3) use of BAA endorsed estimates delivered in East of England on staff grade required per activity. [SR1.1] Results: The estimates for 10-year adult and paediatric audiology whole time equivalent (WTE) safe minimum staffing levels for England (bands 2-7, current waiting times maintained) based on a population change model (Model 1), and two further models for paediatrics specifically (Model 2 and Model 3) were as follows: for adult audiology Model 1 estimates a 7.40% increase by 2035 (to 1125.18 WTE). For paediatric audiology Model 1 estimates a -6.3% (to 593.47 WTE) decrease due to underlying paediatric population decline in England, whereas the case complexities considered in Model 2 (1072.33 WTE) and Model 3 estimate a 10-year increase of 71.23% ( to 1072.33 WTE) and 59.17% (to 996.82 WTE) respectively. Conclusions: This is the first study to conduct a needs-based assessment of workforce requirements for audiology services. Given the substantial need for audiology staff, investment in workforce recruitment and training is essential to ensure that future activity levels meet population needs. Consideration of changing demographics is required for planning future workforce specialisation. Further analysis to address workforce equity, the impact of changes in skill mix and service delivery models and local area demographics/prevalence variation is required alongside potential efficiencies.

Objectives To assess the concurrent and lagged associations between quality of primary care and planned and unplanned secondary care use for patients with multimorbidity, examining the modifying role of frailty. Design A retrospective cohort study Setting This population-level analysis included 468,172 patients with multimorbidity in England from the Discover research platform (April 2022-March 2024). Participants Patients with multimorbidity Main outcome measures We used principal component analysis to combine a set of quality indicators (QIs) and assessed the impacts of QIs on both planned and unplanned care. Results Generally, patients with higher QI attainment also had higher likelihood of planned (outpatient visits) and unplanned care (emergency admissions and ED visits) utilisation. There was a lower lagged odds of elective hospital admissions in the following 12 months among those with higher attainment of multimorbidity-specific QIs (OR=0.94, 95%CI 0.93-0.95). In the complex multimorbidity cohort ([&ge;]3 conditions), multimorbidity-specific QIs were longitudinally associated with lower odds of elective admissions (OR=0.94, 95%CI 0.92-0.95) and outpatient visits (OR=0.96, 95%CI 0.95-0.98), while generic QIs were related to lower odds of outpatient non-attendance (OR=0.95, 95%CI 0.91-0.99). In non-frail patients with multimorbidity, multimorbidity-specific QIs were longitudinally associated with reduced odds of outpatient visits (OR=0.98, 95%CI 0.97-0.99), elective admissions (OR=0.92, 95%CI 0.90-0.94) and prolonged elective hospital stay (IRR=0.94, 95%CI 0.89-0.99). Conclusions Attainment of generic and multimorbidity QIs was generally associated with slightly increased planned and unplanned care. However, patients for whom we identified higher attainment of multimorbidity-specific QIs had lower odds of elective admissions and outpatient visits, especially for those with complex multimorbidity. Our research suggests that the quality of primary care may influence patients' use of secondary care, with the potential to improve care for people with multimorbidity and warrant further investigation into management strategies.

Objectives: To evaluate the sustainability of Lean Healthcare practices after the implementation phase of a national quality improvement programme and to identify organisational factors associated with maintaining results over time. Design: Multicentre cross-sectional study with a mixed-methods approach. Setting: Twelve public and philanthropic hospitals in Brazil participating in Phase 2 of the Lean in Emergency Departments Project. Participants: Key respondents in managerial or leadership roles from participating hospitals (response rate: 75.0%). Outcome measures: Sustainability of Lean practices and organisational readiness, assessed through a structured survey and triangulated with operational indicators collected across successive implementation cycles at hospital level. Results: During one year of structured follow-up, 66.7% of respondents reported maintenance of Lean practices; this decreased to 33.3% after the end of structured follow-up. Although 66.7% considered professionals capable of maintaining results, only 58.3% positively evaluated institutional structure, indicating a discrepancy between individual capacity and organisational readiness. Operational indicators showed heterogeneous behaviour across hospitals, with no consistent pattern of sustained improvement. Qualitative analysis identified professional and managerial turnover, formal governance structures, and continuous monitoring as key factors associated with sustainability. Conclusions: The sustainability of Lean Healthcare practices is more strongly associated with institutional capacity to embed and sustain changes over time than with isolated individual training. Quality improvement programmes should incorporate structured strategies for the post-implementation phase. Keywords: Lean Healthcare; Sustainability; Quality improvement; Hospital flow; Health systems; Organisational factors

Background Patient-reported satisfaction is a core tracer of health-system responsiveness in Universal Health Coverage (UHC) monitoring, yet its determinants in rural Sierra Leone are poorly characterised. We quantified overall and domain-specific satisfaction and identified modifiable predictors across three rural border districts. Methods We conducted a cross-sectional, population-based household survey in October 2024 in Kailahun, Kambia and Pujehun districts, using a two-stage cluster design (chiefdoms sampled with probability proportional to size; households sampled at random). A validated 29-item instrument measured overall satisfaction and eight patient-experience domains on five-point Likert scales. The primary outcome was the five-level single-item overall satisfaction rating. We fitted a multivariable proportional-odds ordinal logistic regression, with 95% confidence intervals (CIs) obtained by a cluster bootstrap resampling the 20 chiefdom clusters. Robustness was assessed with binary and composite-outcome sensitivity models. Results Of 750 respondents, 679 (90.5%) had used a formal health facility in the previous 12 months and formed the analytic sample (510 [75.1%] female; mean age 28.2 years [SD 13.8]). The instrument showed high internal consistency (Cronbach = 0.87 for the five core domains). Overall, 375/679 (55.2%) were satisfied or very satisfied, ranging from 185/244 (75.8%) in Kambia to 110/224 (49.1%) in Kailahun and 80/211 (37.9%) in Pujehun ({chi}{superscript 2} = 70.8; p<0.001). In the adjusted model, staff attitude was the strongest predictor of higher satisfaction (adjusted odds ratio [AOR] 2.74, 95% CI 2.03-3.70; p<0.001 per one-point increase), followed by waiting-time satisfaction (AOR 1.89, 1.39-2.46) and medicine availability (AOR 1.43, 1.16-2.10). Travel-time category, facility type and sex were not independently associated. Large district disparities persisted after adjustment: relative to Kambia, the AOR for higher satisfaction was 0.27 (0.15-0.50) in Kailahun and 0.33 (0.20-0.66) in Pujehun. Adjusted probabilities of high satisfaction were 0.72, 0.48 and 0.43, respectively. Conclusions Respectful provider behaviour, shorter waits and reliable medicine supply, all amenable to district-level management, were the dominant and actionable drivers of patient satisfaction, whereas geographic distance was not. Persistent between-district gaps call for tailored quality-improvement in Kailahun and Pujehun. Institutionalising routine patient-experience measurement would strengthen accountability for people-centred care and support equitable progress towards UHC.

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

Background Effective communication during consultations is facilitated by clinical empathy and realistic optimism, and can enhance patient satisfaction with care, alleviate symptoms, and improve quality of life. However, primary care systems are under significant strain and changing rapidly, which may affect practitioners' ability to communicate empathically and convey realistic optimism, with implications for the patient-practitioner relationship and patient outcomes. Understanding patients' perspectives of healthcare communication in the current clinical context is therefore important. We aimed to explore patients' experiences and perceptions of communication in UK primary care consultations, focussing on the communication of clinical empathy and realistic optimism. Methods A qualitative interview study was conducted as part of a multi-centre cluster-randomised trial of EMPathicO, a brief e-learning package for Primary Care Practitioners (PCPs) on communicating clinical empathy and realistic optimism. Participants were not aware whether their general practice had access to EMPathicO or not. Interviews were conducted within 7-14 days of participants' consultations, explored their views and experiences of clinical empathy and realistic optimism, and were transcribed verbatim. Interviews were analysed using Ritchie and Spencer's Framework Method. Results We conducted semi-structured audio-recorded qualitative telephone interviews with 71 participants from 29 primary care practices taking part in the EMPathicO trial. Following comprehensive mapping of data to the framework derived following initial analysis, four themes were agreed. Overall, most participants described positive empathic consultations with their PCPs, however, participants' experiences were shaped by wider systemic and contextual factors. They described a stretched and inefficient primary care system impacting empathy and optimism; the impact of PCP 'preparedness' as a marker for empathy; how consultation modality (i.e. in-person or telephone) shaped perceptions of empathy, and how PCPs sharing next steps in participants' treatment and management could foster realistic optimism. Conclusions While clinical empathy and realistic optimism may be experienced by patients during consultations with practitioners, the wider contextual challenges of accessing and navigating primary care systems can threaten overall perceptions of feeling cared for. Future primary care policy and workforce training must consider these system pressures to preserve effective communication in consultations and positive patient-practitioner encounters.

Inappropriate antibiotic use presents a major global health challenge, particularly in low-resource settings where access to quality care is limited but antibiotics remain relatively unrestricted. This study estimates the causal effect of frontline primary care quality on inappropriate community antibiotic use, combining detailed community-based data from approximately 100 rural villages in rural China with an instrumental variable (IV) approach embedded within a double/debiased machine learning (DML) framework. We linked objective measures of village doctor clinical practice quality, measured through unannounced standardized patient visits, to household-level antibiotic use data collected from the same villages. To identify the causal effect, we constructed multiple candidate instruments from extensive provider characteristics and used an ensemble of machine learning algorithms within a flexible DML-IV framework to approximate an optimal instrument, addressing a many-weak-instruments problem. We found that improving village provider clinical practice quality reduced both antibiotic receipt during healthcare encounters for common diseases and household antibiotic storage for future self-medication. Our findings suggest that strengthening frontline primary care quality can meaningfully reduce inappropriate community antibiotic use without restricting access to essential treatment. More broadly, this study illustrates how causal machine learning can strengthen conventional causal estimation in complex observational settings in global health economics research.

Abstract Objective. To identify and rank the leadership traits most valued by medical staff in public hospitals, and to compare them with an established generic instrument and a generative artificial intelligence source. Design. Sequential exploratory qualitative-quantitative (QUAL QUAN) mixed-methods study: focus groups followed by an online ranking survey, with cross-comparison against the Northouse Leadership Traits Questionnaire (LTQ) and a ChatGPT derived list (LAIT). Setting. Major public hospital affiliated with Monash University, Melbourne, Australia, in 2023. Participants. Twenty-four senior medical staff (16 men, 8 women; 18 clinicians, 6 administrators) recruited through opportunistic sampling. Main outcome measures. Weighted ranking of the ten most desired leadership traits (Leadership Enabling Traits Survey, LETS); internal consistency (Cronbach s alpha); agreement between LETS and LTQ self-scores; and strong overlap with the AI-derived list. Results. The first most-weighted LETS traits were integrity (1.526), communication (1.435), compelling vision (1.404), emotional intelligence (1.040) and empathy (0.969), the same five identified by the AI source. Integrity was weighted 3.6 times more heavily than rebelliousness (0.424). Both LETS and LTQ achieved Cronbach s alpha > 0.7. Unweighted total self-scores did not differ between LETS (77.4 +/- 7.6) and LTQ (78.4 +/-6.9); weighted emotional intelligence related and other-trait sub-scores diverged significantly (p<0.001). Survey power was 45% at alpha=0.05.

Objectives: To examine the conformance to type 2 diabetes NICE guidelines across cardiovascular risk strata; and to quantify geographical variation in treatment pathways following the COVID-19 pandemic, encompassing guideline changes. Design: We carried out a retrospective observational study using linked electronic health records across England. Process mining, a data driven method that can reconstruct clinical treatment pathways, was applied to map 12-month treatment trajectories after treatment initiation. Conformance with NICE NG28 (2022) was quantified using a structural similarity index. Further, behavioural and entropy-based similarity (capturing treatment variability and complexity) measures were used to assess sequencing and heterogeneity of treatment. Setting: Primary and secondary care in England datasets within the National Health Service England Secure Data Environment (NHSE SDE), analysed first at national level and then across 42 Integrated Care Boards (ICBs) which are the devolved health care geographical delivery regions in England. Participants: 822,650 individuals with newly diagnosed T2DM between 1-February-2022 and 1-November-2025, stratified into low cardiovascular risk (LR-C; QRISK3<10), high risk (HR-C; QRISK3>=10 or receiving statins/blood pressure lowering treatment), and established cardiovascular disease (eCVD-C). Participants were followed for 12 months after first dispensed glucose lowering therapy. Main outcome measure: First line therapy, treatment intensification and switching within 12 months; change in glycated haemoglobin (HbA1c); quantified conformance to NICE recommended pathways; and regional variation in broader similarity measures. Results: Metformin monotherapy was the dominant initiation strategy in LR-C and HR-C cohorts (92.4% and 90.2%, respectively), whereas eCVD-C showed lower uptake of metformin (68.9%) and higher uptake of SGLT2 inhibitors (26.3%). Intensification from metformin to combination therapy was infrequent across all cohorts (<1%), although HR-C demonstrated the highest treatment transitions and switching behaviour. Dispensed SGLT2 inhibitor use was nearly threefold higher in eCVD-C (26.7%) than in LR-C (9.0%) or HR-C (10.7%). Overall, conformance to NICE-recommended pathways remained modest nationally, particularly in LR-C and HR-C. Across 42 ICBs, substantial regional heterogeneity in treatment pathways and guideline conformance was observed, with conformance ranging from 0.29 to 1.00 in LR-C pathways, 0.40 to 1.00 in HR-C pathways, and 0.54 to 0.92 in eCVD pathways. Conclusion: National T2DM treatment pathways for post-pandemic showed higher alignment to NICE guidelines in eCVD-C compared to the other risk groups, with ongoing gaps and large regional variations in other risk groups. Process mining offers a scalable approach to monitor implementation of guideline recommended care that could support learning health systems. Using T2DM during and post COVID-19 pandemic as a case study, this work demonstrates how these methods can assess the use of existing and innovative therapies, identify gaps and guide future adoption to ensure recommended treatments reach the right patient groups.

Mobile clinical-support applications can facilitate access to evidence-based information at the point of care, but evidence on their usability and perceived usefulness among newly graduated physicians working in health facilities with limited capacity is scarce. We assessed physicians experiences with BMJ Best Practice using a convergent mixed-methods study. All 81 eligible physicians assigned to rural facilities were invited; 32 enrolled and received application access and training. After three months, participants completed an online survey, and 23 reported using the application. Ten physicians reporting the highest consultation frequency were purposively selected for semi-structured interviews. Survey findings showed a predominantly favorable perception of usability: for most items, 70%-90% of participants agreed or strongly agreed with the statements assessed. Among users, 14 of 23 (60.9%) used the mobile application and 9 (39.1%) used the web version. Interviews indicated that participants valued rapid searches, organized and evidence-based information, and support for diagnostic reasoning, referral decisions, learning, and clinical confidence. Barriers included limited connectivity, difficulties searching in Spanish, automatic updates, challenges locating or using some calculators, and treatment information that was sometimes insufficiently specific. Most importantly, participants could not always implement recommendations because suggested medicines, diagnostic tests, or other resources were unavailable in their facilities. Mobile clinical-support applications may complement decision-making and learning among early-career physicians in rural primary care. However, their practical value depends not only on usability and evidence quality, but also on adaptation to users language, workflow, connectivity, and local service capacity.

Background: Gaps in health financing drive delayed diagnosis, catastrophic health expenditure, treatment discontinuation, and excess mortality and morbidity in breast cancer, effects compounded by gender inequalities that shape household resource allocation, care-seeking behaviour, and spending decisions for conditions disproportionately affecting women. Despite this, the economic burden of breast cancer and the gender dynamics that mediate it remain poorly characterised in middle-income country settings. This study examines the economic burden of breast cancer in India and Kenya and assesses how gender inequalities shape treatment decision-making, health outcomes, and caregiving experiences. Methods: This will be a mixed-methods, longitudinal, prospective cohort study of newly diagnosed breast cancer patients, with a health economics and gender analysis. Participants will be surveyed twice, at baseline and 6-months post treatment commencement either in person or by phone. A sub-sample of participants and their caregivers will participate in semi-structured interviews to explore household economic consequences of treatment, treatment-seeking decisions, and the gendered dimensions of both. Quantitative data will be analysed using descriptive statistics and regression modelling to identify determinants of catastrophic health expenditure and economic burden. Thematic analysis will be conducted and triangulated with quantitative findings to provide a comprehensive account of financial and gendered impacts across both settings. Discussion: The study will generate comparative evidence on the economic burden of breast cancer across two developing health system contexts. Findings will inform priority setting and benefit package design by identifying the drivers of economic burden and treatment discontinuation in these contexts, and making visible the household and caregiving costs that financing policy rarely captures.

Introduction People with severe mental illness (SMI) and learning disabilities (LD) experience significant health inequalities, with diet-related conditions contributing substantially to early and preventable death. Despite high levels of nutritional risk, the presence and effectiveness of nutritional screening in mental health (MH) and LD settings remains under-researched. This study aimed to investigate nutritional screening practices in UK inpatient MH and LD services from the perspectives of dietitians. Methods A cross-sectional mixed-methods study was conducted using a novel 22-question online survey. Data was collected via the British Dietetic Association Mental Health Specialist Group (April-June 2025). Quantitative data was analysed descriptively and qualitative data by reflexive thematic analysis. Findings were integrated and presented thematically. Ethical approval was granted by Teesside University (2025Mar26544). Results Forty-seven dietitians participated, most with substantial dietetic experience, from a range of MH settings. Screening practices were widely established and supported by policy and audit. However, participants reported low confidence in screening translating into meaningful patient care. Barriers to screening included appropriateness of available tools, time constraints, difficulty engaging distressed patients and poor prioritisation of physical health. Digital integration and wider infrastructure were also important. Dietitians rarely undertook screening directly, instead holding secondary or leadership roles, while screening was most often completed by nursing staff who were often perceived to place limited importance on the process. Existing tools, particularly the Malnutrition Universal Screening Tool (MUST), were viewed as insufficiently capturing the broader nutritional risks relevant to MH/LD populations, leading some services to adopt bespoke, unvalidated tools. Conclusion Concerns regarding the suitability of existing nutritional screening tools in MH/LD settings are consistent with previous literature. However, we suggest cautious use of unvalidated bespoke tools. Whilst there was no clear front runner, MH specific tools such as the St Andrews Nutrition Screening Instrument (SANSI) and the NutriMental Screener warrant further evaluation. Importantly, findings indicate that optimising tool choice alone is unlikely to improve screening effectiveness. Nutritional screening must be embedded within clear care pathways, supported by organisational leadership, digital infrastructure, and multiprofessional engagement to move beyond procedural completion and support meaningful clinical action to improve patient care.

Background: Cancer is a growing public health challenge in Ghana, with 27,385 new cases and 17,944 deaths recorded in 2022. Ghana developed a National Cancer Control Strategy (NCCS) in 2011 to guide prevention, early detection, treatment, and palliative care. The strategy expired in 2016 and has not been formally evaluated or renewed, leaving cancer control efforts without a guiding policy framework for nearly a decade. This study examined how the strategy was implemented, what barriers were encountered and what stakeholders recommend for a strengthened national cancer response. Methods: We conducted a qualitative descriptive study using semi-structured key informant interviews. Fifteen participants were recruited through purposive sampling, supplemented by snowball referrals, representing three groups: Ministry of Health policymakers, frontline healthcare providers and representatives of cancer-focused non-governmental organisations. Data were collected between June and September 2025 and analysed using Braun and Clarke's six-phase thematic analysis framework, guided deductively by the WHO Health Systems Building Blocks framework Results: Three themes emerged: NCCS interventions and systems implemented, capturing progress in cancer awareness, HPV vaccination and pilot screening programmes alongside persistent geographic and financial inequities in access; barriers to implementation, including inadequate financing, infrastructure and workforce shortages, the absence of a national cancer registry and governance failures, among them the finding that no frontline healthcare provider interviewed had any awareness of the NCCS; and recommended implementation strategies, including co-production of a renewed strategy, establishment of a dedicated National Cancer Control Programme, expanded health insurance coverage and decentralisation of oncology services. Conclusion: The NCCS was not operationally embedded in the health system. The evidence points to failures in policy dissemination as a constraint that precedes resource constraints. Addressing Ghana's rising cancer burden requires renewed political commitment, co-produced governance structures and accountability mechanisms. These findings have relevance for other low- and middle-income country settings facing similar challenges.

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