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.

Objectives: Women's empowerment is a key determinant of health and well-being and may shape how women access and benefit from publicly-funded health insurance (PFHI). We aimed to examine whether different levels of women's empowerment were associated with 1) verification in India's PFHI Pradhan Mantri Jan Arogya Yojana (PM-JAY), 2) outpatient care utilization, and 3) resultant out-of-pocket expenditure. Design: We conducted a cross-sectional observational study. We analyzed data from a household survey, created a composite empowerment index using structural equation models, and used multivariate regression models to test associations between women's empowerment and the outcome variables. Setting: The study was conducted between December 2019 and February 2020 among PM-JAY eligible households in six Indian states (Bihar, Chhattisgarh, Gujarat, Meghalaya, Tamil Nadu, and Uttar Pradesh). Participants: 14,378 women across the six states. Results: Three main findings emerged: First, high levels of women's empowerment were associated with higher odds of completing PM-JAY verification (AOR: 1.22, 95% CI: 1.09-1.36). Second, women's empowerment was not associated with outpatient service utilization. And third, either medium levels of empowerment (coef = -0.49, p = 0.020) or PM-JAY verification (coef = -0.37, p = 0.034) was associated with lower OOPE for outpatient services. Women who had both, PM-JAY verification and medium levels of empowerment, experienced higher OOPE (coef = 0.45, p = 0.058). Conclusions: Women's empowerment is an important factor related with PM-JAY verification, but not with outpatient service use. OOPE varied depending on whether women were both empowered and PM-JAY verified or not. Our results suggest that institutional and structural barriers may play a greater role in healthcare access than individual factors pertaining to empowerment alone. Achieving equitable access therefore requires gender-responsive systems that reduce administrative barriers and support women in navigating the healthcare pathway. Our findings highlight the importance of integrating outpatient care into PM-JAY to increase financial protection, streamlining verification processes to improve women's engagement with PM-JAY and the broader health system, and advancing health financing reforms that better support women.

Background: While health system costs of COVID-19 are well documented, evidence on out-of-pocket costs to patients and families, including non-medical and time burden, is limited. This study aimed to estimate out-of-pocket medical, non-medical, and time burden of COVID-19 illness directly from patients and caregivers. Methods: Two cross-sectional surveys were fielded to national nonprobability samples of U.S. adults in Fall 2023: a personal burden survey (adult sample) and a caregiver burden survey (child sample). Surveys collected data on care setting, visit duration including travel and wait time, and medical and non-medical out-of-pocket costs. After applying quality-based exclusion criteria, 409 adult sample and 52 child sample responses were analyzed. Results: Over 87% of respondents were insured. Median out-of-pocket medical costs per visit were low, ranging from $5 (emergency department) to $10 (urgent care) in the adult sample, and from $0 (emergency department) to $75 (hospitalization) in the child sample. Median non-medical costs were $28 or less across care settings. Median time spent receiving care ranged from 90 minutes (primary care, child sample) to 300 minutes (emergency department, adult sample). Despite the relatively low reported out-of-pocket costs, COVID-related financial challenges were reported by 34% of the adult sample and 29% of the child sample, with the most common difficulty being paying non-medical bills (11% and 15%, respectively). Twelve percent in both groups reported problems paying COVID-19-related medical bills. Conclusions: In this post-pandemic non-probability sample, individual out-of-pocket costs for COVID-19 illness were relatively modest. However, time burden was substantial and one-third of respondents reported financial hardship. These estimates, including non-medical and time burden not captured in administrative data, can support more robust economic evaluations of COVID-19 prevention and treatment interventions.

Background: Lean Healthcare has been adopted as an approach to reducing waste, enhancing process efficiency, and optimizing clinical and administrative workflows. However, empirical evaluations aimed at establishing a causal relationship between Lean Healthcare interventions and outcomes remain limited. This evidence gap is particularly pronounced in the context of large-scale implementations in low- and middle-income countries, where more efficient allocation could yield substantial improvements in population health. Methods: We conducted an impact evaluation study employing a staggered difference-in-differences approach to estimate the effects of the Lean Healthcare in Emergency Departments (ED) initiative in the Brazilian context. The intervention was implemented between January 2017 and December 2025 across 309 hospitals. We analyzed hospital-level indicators of the number of hospitalizations and the average length of stay (in days) among patients admitted through urgent or emergency pathways. Results: Our estimates suggest that the intervention was associated with an average increase of 38.6 admissions per hospital per month (p = 0.033), corresponding to approximately a 5.9% increase relative to the monthly admission volume. We also observed a reduction of 0.184 days in the average length of stay (p = 0.058), equivalent to an approximately 3.0% decrease in hospitalization time. These effects exhibited distinct temporal dynamics: the effect on the number of hospitalizations emerged gradually and increased with the duration of the intervention, whereas the reduction in length of stay became evident earlier. Conclusion: This study provides evidence of a causal effect of Lean Healthcare implementation in emergency departments on operational performance. The simultaneous increase in admissions and reduction in length of stay suggests improved bed productivity and effective capacity without expanding physical infrastructure. These findings support the use of flow-management methodologies as an effective strategy for mitigating emergency department overcrowding while increasing service capacity.

This paper examines the impact of Cancer Care Ontario's regionalization of lung cancer surgery on blood transfusion use for thoracic surgery at The Ottawa Hospital. Using aggregate data scraped from the paper ''Changing trends in blood transfusion: an analysis of 244,013 hospitalizations'' by Shehata et al. (2014) we estimated the effect regionalization on the log mean number of blood transfusions among thoracic surgeons (who treat lung cancer), utilizing other surgical specialties as controls. We found that the average number of blood transfusions increased significantly among thoracic surgeons following the opening of a new cancer care centre at the hospital in December 2009, while control specialties showed no parallel change. Contextualizing these results in a modified ''population level'' treatment threshold model, it is argued that the main driver of this increase in blood transfusions among thoracic surgeons was due to the influx of less skilled thoracic surgeons to The Ottawa Hospital, and the closing of thoracic surgery units at smaller hospitals which was part of the broader regionalization process.

Background: This study focused on adults with complex care needs due to problems on multiple life domains and consequent high acute care use. The Hotspotters Project was undertaken to assess the effects of proactive integrated care on health outcomes and healthcare costs in this group. We evaluated the reach, effectiveness, adoption, implementation and maintenance (RE-AIM) of the Hotspotters Project in order to identify factors that influenced implementation and outcomes. Method: This mixed method study followed the RE-AIM-framework, using validated questionnaires, routine care data and semi-structured interviews. Qualitative data from patients and care providers offered insight in the quantitative outcomes. Quantitative data were analyzed descriptively (SPSS), and interview transcripts were analyzed using inductive thematic content analysis (Atlas.ti). Results: As acute care use was lower than expected, few patients were eligible (153/1403) and subsequent low enrollment (n=30) limited conclusions regarding effectiveness. Nevertheless, the intervention improved collaboration with social work, and the structured intake was valued for the overview of patients complex needs. Many practices adopted the intervention into regular care, despite the complex inclusion process. Care providers proposed revising the target population and recruitment to better reflect the Dutch context. Conclusion: Although cost-effectiveness could not be assessed, this study nonetheless provides insights that can help future interventions and trials to better match patients needs, adapt to local context and reduce patients study burden. Adapting the definition of patients with complex needs to a local context can strengthen the rationale for implementation and enhance patient motivation.

Background: Mobile outreach initiatives have emerged to address persistent barriers to care for people experiencing homelessness, substance use, and mental illness. Although these models show promise, less is known about how and under what conditions they enable engagement and coordinated care. This study explains how, why, and under what circumstances a mobile, cross sector outreach model enables access to care for marginalized populations. Methods: We conducted a realist evaluation of Supportive Outreach Services (S.O.S.), a mobile, cross sector outreach program in Grey County, Ontario. Data included 31 semi structured interviews with outreach providers, partner organizations, system leaders, and clients, supplemented by document review and stakeholder feedback. Using retroductive reasoning and constant comparison, we developed and refined context mechanism outcome configurations to construct an explanatory program theory. Results: Five interconnected realist explanations account for how the model enables access to care. Trust built through repeated, non judgmental encounters supports engagement; proximity reduces barriers to participation; accessible support enables timely help seeking; cross sector relationships enable adaptive coordination; and visible results build legitimacy that sustains participation and resources. Together, these explanations provide a linked explanatory account of how mobile outreach reduces friction between marginalized populations and fragmented services while identifying the structural conditions that constrain its effectiveness. Conclusions: The effectiveness of mobile outreach depends less on the services delivered than on its capacity to reduce friction, sustain relationships, and adapt care across organizational boundaries. The resulting program theory offers transferable explanations for designing coordinated community based services while highlighting the structural conditions required for durable change.

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.

Introduction Primary care productivity and performance are hard to measure because patient health is not measured systematically and consistently. In England, productivity is measured using output (appointment volume) and two value-based metrics: waiting times and patient satisfaction. Higher productivity should improve all these metrics: more appointments should shorten waits, and shorter waits should raise patient satisfaction. However, little evidence tests how output and value-based metrics are associated. Methods We conducted a retrospective observational study of NHS primary care in England, 2018 to 2024, using Appointments in General Practice and the GP Patient Survey. Across Integrated Care Boards (ICBs), we examined the relationship between changes in appointment volume, waiting times, and patient dissatisfaction over two periods, 2018-2022 and 2022-2023, stratified by staff group and appointment mode. Results Completed appointments rose between 2018 and 2024, with care shifting towards non-GP staff and virtual delivery. Across ICBs in 2018-2022, per million additional appointments, waiting time changed by -0.04 days (95% CI: -0.10, 0.03) and dissatisfaction by 0.02 percentage points (95% CI: -0.36, 0.40). Per additional day of waiting, dissatisfaction changed by -1.40 percentage points (95% CI: -3.21, 0.42). In 2022-2023, the corresponding estimates were -0.31 days (95% CI: -0.57, -0.04), -0.75 percentage points (95% CI: -3.05, 1.56), and 2.85 percentage points (95% CI: 1.20, 4.51). Conclusion Increased appointment volume was not associated with shorter waiting times or lower patient dissatisfaction, and shorter waiting times were not associated with lower patient dissatisfaction. Either quality metrics do not respond to output, the key factor providers control, or they do not capture the dimensions of quality that matter. Performance frameworks that assess primary care productivity through these metrics should be reviewed.

Importance: The 2026 public charge rule could discourage immigrants from accessing health coverage programs, creating a chilling effect that potentially leads to negative health outcomes; However, its long-term health impact is poorly understood. Objective: To model potential impacts of the 2026 public charge rule on primary care and premature mortality among immigrants in New York City (NYC). Design, Setting, and Participants: The simulation used a deterministic compartmental model with Ordinary Differential Equations (ODEs) using 2023 NYC Vital statistics data and American Community Survey, and estimates obtained from 2 previous studies about effects of healthcare access on primary care and Medicaid expansion on premature mortality. Main Outcomes and Measures: Rates of primary care outcomes (access, doctor's visits) in 5 years, and premature mortality in 5 and 20 years, projected by the model under conservative, moderate, and aggressive scenarios of avoidance/disenrollment due to the public charge rule, known as the 'chilling effect'. Effects of the avoidance/disenrollment on primary care outcomes and premature mortality were obtained from 2 previous studies. Projected rates of the outcomes under each scenario were compared with counterfactuals to estimate the health impacts of the chilling effect. Results: Implementation of the public charge rule was projected to decrease the primary care access rate by 4.1% (conservative) to 9.9% (aggressive) over 5 years, relative to the counterfactual scenario without the rule. The rate of doctors' visits was projected to decrease over 5 years by 5.1% (conservative) to 12.2% (aggressive). Premature mortality was projected to increase by 4.4% (conservative) to 10.6% (aggressive) in 5 years and 7.4% (conservative) to 17.4% (aggressive) in 20 years. Legal noncitizens and Black immigrant New Yorkers were predicted to experience higher burdens of premature mortality attributed to the chilling effect, compared with other immigrant groups and racial/ethnic groups, respectively. Conclusions and Relevance: This study demonstrates adverse health consequences of federal public charge rule changes among immigrants in NYC. The model projected a decrease in primary care visits and increase in premature mortality across various scenarios. These findings suggest urgent reconsideration of a regulatory change that disproportionately increases risk of premature mortality among immigrants in NYC.

Background: Spatial accessibility measures estimate how much hospital capacity a community can reach but do not show how that capacity is distributed across health systems. A community may have several reachable hospitals but still depend on one or a few systems. Methods: We used the enhanced two-step floating catchment area method to estimate staffed-bed spatial accessibility for New Jersey census tracts. We included short-term acute care hospitals in New Jersey and neighboring states within a 30-minute drive of at least one New Jersey tract. For each tract, we grouped hospital-level accessibility contributions by health system and calculated a Herfindahl-Hirschman Index (HHI). Spearman correlations examined associations of E2SFCA and HHI with tract-level sociodemographic characteristics. Results: Of 163 reachable hospitals, 94 were outside New Jersey and supplied 62.7% of reachable staffed beds. Across 2,172 tracts, the mean E2SFCA score was 1.98 beds per 1,000 distance-weighted residents; among 2,161 tracts with positive scores, the median HHI was 0.31. Using cutoffs of E2SFCA <2.0 and HHI [&ge;]0.18, 934 tracts met both criteria, while an E2SFCA-only rule missed 655 tracts with higher accessibility but high concentration. E2SFCA and HHI correlations had opposite signs for seven of eight sociodemographic characteristics. Conclusions: E2SFCA and HHI classified New Jersey tracts differently under the illustrative cutoffs. Contribution-based HHI identifies tracts in which a closure, service relocation, or capacity reduction involving a major contributing system could affect a large share of modeled accessible capacity. Keywords: Spatial accessibility; hospitals; E2SFCA; health systems; Herfindahl-Hirschman Index

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.

Objectives To investigate the association between time spent in NHS Type 1 emergency departments (EDs, consultant led 24 hour services with full resuscitation facilities) and risk of leaving employment and hospitalisation after leaving the department alive up to two years after attendance. Methods We conducted a retrospective cohort study using linked administrative data from the NHS Emergency Care Dataset, Hospital Episode Statistics, Census 2021, and mortality records. ED length of stay was categorised from under 2 hours to 12 hours or more. Cox proportional hazards models were fitted to estimate the association between ED length of stay and subsequently leaving employment or being hospitalised over a two year follow-up period, adjusting for demographic, socioeconomic, and clinical characteristics. Results Our study population comprised 3,347,008 individuals aged 25 to 64 who attended a Type 1 ED in England between April 2021 and March 2023. For leaving employment, adjusted hazard ratios (aHRs) increased from 1.04 (95% CI 1.03 to 1.06) for stays of 2 to <4 hours to 1.21 (1.17 to 1.24) for 12 hours or more, compared with stays under 2 hours. A similar but more pronounced gradient was observed for post-discharge hospitalisation, with aHRs rising from 1.06 (1.04 to 1.07) at 2 to <4 hours to 1.95 (1.91 to 1.99) for stays of 12 hours or more. Conclusions Prolonged time spent in the ED is associated with poorer outcomes among working-age employees, including reduced labour market participation and increased hospital use. These findings suggest that long ED stays may have wider and longer-term implications beyond immediate clinical outcomes, including potentially for national labour markets and economic growth.

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.

This study aims to map significant cold spots of postacute rehabilitation therapy delivery rates for Original Medicare beneficiaries in the U.S. and determine the prevalence of those cold spots in rural areas. Statistical spatial clustering of postacute therapy delivery rates was conducted in ArcGIS Pro using hot and cold spot analyses (Getis-Ord Gi*). County-level therapy delivery volume was defined as the total minutes of physical, occupational, and speech therapy provided by skilled nursing facilities (SNFs), home health agencies (HHAs), and inpatient rehabilitation facilities (IRFs). Therapy delivery rates were then computed as minutes per Original Medicare beneficiary at the county level and adjusted using a county-level Hierarchical Condition Category risk score. Spatial clustering identified cold spots (statistically significant clusters of low rates) and hot spots (clusters of high rates). We also computed the proportion of cold spots in rural counties and the relative percentage difference compared to the national rural county baseline, using two rural classification systems. Identified coldspots varied by provider type. For SNFs, they were notably identified in the Mountain and West North Central US divisions. For HHAs, cold spots appeared across more U.S. Census Divisions, including areas (e.g., Kentucky, Indiana, southern Illinois) where SNFs showed hot spots. Cold spots were more prevalent in rural--and especially in small rural--counties across all provider types. In rural counties, cold spot rates were 42.8% to 71.5% higher than the rural county baseline. In small rural counties, differences were larger, at 69.1% to 95.5% higher. Concluding, cold spots of postacute therapy delivery varied across the continental U.S. by provider type but were more prevalent in rural and especially in rural counties with smaller population size -- across provider types. Identifying these cold-spot locations may support geographically targeted policy responses and the development of alternative service?delivery models in underserved areas.

Importance: The Medicare Physician Fee Schedule values ambulatory services using survey-based estimates of physician time, a costly process vulnerable to inaccuracy. EHR audit logs are passively and universally collected and likely meet the American Medical Association Relative Value Scale Update Committee (AMA RUC) Extant Database Standards for alternative data to inform service valuation estimates. However, audit logs' validity for estimating face-to-face time, a core component of many of the most used procedural codes, is unknown. Objective: To assess whether EHR audit logs can facilitate accurate estimation of physician-patient face-to-face time during ambulatory visits. Design: Single-site validation study pairing EHR audit logs with direct audio/video recordings of ambulatory primary care visits (reference standard). We assessed agreement between audit-log estimates and recorded visit duration with Bland-Altman analysis and mean absolute error. Setting: University of Pennsylvania Observer data repository, a multi-modal database of ambulatory visits to Penn Medicine primary care clinics including video and audio recordings, transcripts, clinical EHR data, and EHR audit-log data. Participants: 75 visits from 12 physicians with data collected between August 2023 and February 2025. Exposures: A rule-based algorithm estimated face-to-face time via clusters of physician EHR activity relative to patient check-in time. Inactivity thresholds were applied to differentiate intraservice time with no EHR activity (e.g., a physical exam) from the end of a visit, with longer thresholds used for longer visits. Main Outcomes and Measures: Duration of recorded face-to-face visit time. Results: Recorded face-to-face time averaged 31.6 minutes (SD, 13.9). The audit-log estimator was unbiased (mean bias: -0.63 minutes; 95% CI: -6.0 to 2.6; mean absolute error: 9.0 minutes) and estimated face-to-face time within approximately 2% (38 seconds) of the recorded visit time with no proportional bias (slope: 0.13; P = .25). The 95% limits of agreement were -25.7 to 24.4 minutes, and 37% of estimates fell within 10% of recorded duration. Conclusions and Relevance: In this validation study, EHR audit logs recovered unbiased estimates of ambulatory face-to-face time. Larger-scale studies are required to verify generalizability, but EHR audit logs offer a scalable means to improve the rigor of retrospective physician work relative value unit estimation. This study represents a first step in a potential paradigm shift for measuring components of the fee schedule across procedures, settings, and provider types.

Health systems increasingly record ICD-10 Z59 social-needs codes for housing, food, transportation, and related hardship to trigger referrals, report quality, and adjust risk. However code documentation occurs at varying rates and no study has separated what the code says about a patient's hardship from what it says about being documented at all. Using a linked electronic health record and claims corpus covering 4.95 million patients in 21 identifiable health systems, we matched 26,153 adults with a first outpatient Z59 code to similar uncoded patients and, as a negative control, repeated the entire design around an administrative code. Coding ranged from 1 percent to 24 percent of patients across systems and remained highly variable after adjustment for patient mix. A hardship code was associated with 67% (95% CI=1.61, 1.74) more emergency department (ED) visits and 43% ( 95% CI=1.38, 1.49) more hospital admissions in the next year (62 versus 49 of every 100 patients with any acute event). The administrative-code reproduced 46 percent of the Z59 association for ED visits and 70 percent for admissions. In the five systems with the most complete stay dates, no hardship-specific admission excess was detectable. Homelessness codes forecast two and a half times the ED visit rate. At national planning prices, excess emergency and preventable hospital care totaled roughly $2,000 to $2,500 per coded patient-year ($2,516 base scenario; about $1,100 under an exploratory assumed-discount scenario (not an estimate of hardship-attributable spending)), with the largest emergency burden among Medicaid patients. The Z code added no increment to clinical and utilization-based risk prediction models in any system.

Objective: to describe the provision of preconception care across publicly funded or contracted health and social care settings in the UK. Design and setting: online cross-sectional survey conducted October-December 2025. Population: healthcare professionals delivering preconception care, recruited via professional organisations and networks. Methods: quantitative data were analysed using descriptive statistics and qualitative free-text responses using inductive content analysis. Outcome measures: preconception care content, target population, frequency of provision, funding and commissioning models, and approaches for reporting and monitoring. Results: Eighty-seven healthcare professionals completed the survey. Most were women (89.3%), aged 41-60 (63.1%) and based in England (84.5%). Participants represented diverse roles, mainly obstetric/maternal-fetal specialists (23.0%), specialist nurses (16.0%), GPs and midwives (13.8% each). Preconception care primarily targeted women [&ge;]20 years (98.9%), with fewer targeting men and adolescents. Care was usually embedded within relevant consultations (69.4%), particularly contraception, medication and health condition reviews, and often a one-off interaction (75.3%). Content focused on condition-related management/medication (68.6%), folic acid (66.3%), risky behaviours (smoking, alcohol, illicit drugs) (40.7%), diet (37.2%) and weight (36.0%). Services were mostly not formally commissioned (62.4%), lacked financial incentives (84.7%) and had no audit/service evaluation requirements (81.2%). Conclusions: Preconception care in the UK is delivered by a wide range of healthcare professionals. Their engagement has improved considerably when compared with studies conducted over a decade ago, but preconception care remains fragmented, opportunistic and poorly supported by commissioning and system infrastructure. Strengthening integrated care pathways, funding mechanisms and use of standardised resources is essential to achieve consistent and equitable preconception care.

Objective: To evaluate the real-world impact of Stage 1 of Australias 60-day dispensing policy on medicine utilisation and contextualise changes in dispensing with medicine shortages. Methods: We conducted an interrupted time series analysis of aggregated national monthly dispensing data from the Pharmaceutical Benefits Scheme and Repatriation Pharmaceutical Benefits Scheme for the 247 medicines included in Stage 1 of the 60-day dispensing policy. Data from January 2020 to October 2025 were analysed, with September 2023 defined as policy implementation. Linear regression assessed changes in monthly dispensing trends before and after implementation, accounting for autocorrelation and seasonal variation. A relative change of at least 5% in the post-intervention dispensing slope compared with the pre-intervention slope was prespecified as a potentially clinically meaningful change. Therapeutic Goods Administration shortage reports were used to contextualise observed changes. Results: Of 247 medicines, 131 (53%) had increasing and 116 (47%) had decreasing post-intervention dispensing trends; of which 86 (66%) and 71 (61%), were statistically significant, respectively. However, only 8 medicines (3%) demonstrated at least 5% relative change in dispensing slope, six of which had reported shortages. Medicine-specific changes coincided with shortages, product deletions and therapeutic substitution, complicated attribution of changes to the 60-day dispensing policy. Conclusion: Stage 1 of Australias 60-day dispensing policy was not associated with widespread changes in dispensing for most included medicines. Limited changes were plausibly influenced by concurrent shortages and other supply-related events. These findings provide reassurance that extended dispensing did not result in major increases in medicine utilisation at the population level, although continued monitoring is warranted as policy uptake expands.