Black and Hispanic Veterans undergo lower-limb amputations at higher rates than White Veterans, yet it remains unclear whether they receive equitable access to prosthetic devices within the Veterans Health Administration (VHA). To quantify racial and ethnic disparities in lower-limb prosthesis (LLP) prescriptions among Veterans and identify factors contributing to these disparities. Retrospective cohort study using generalized Kitagawa-Oaxaca-Blinder decomposition and prescriptive disparity analysis with double/debiased machine learning. Veterans who underwent major lower-limb amputation within the VHA from 2010 to 2022 (n=16,157; 66.2% White, 27.4% Black, 6.4% Hispanic). Prescription of any LLP and advanced LLP within 12 months postamputation. Black and Hispanic Veterans were 5.7 percentage points (pp) [95% confidence limits (CLs): 4.0, 7.5] and 5.6 pp (95% CLs: 2.4, 8.8) less likely than White Veterans to receive any LLP prescription, respectively. For advanced LLPs, disparities were 1.7 pp (95% CLs: 0.8, 2.6) for Black Veterans and 3.0 pp (95% CLs: 1.5, 4.5) for Hispanic Veterans. Facility-level factors explained 58.2% of the White-Black disparity in any LLP prescriptions. Measured factors fully explained the White-Black disparity in advanced LLP prescription, with preamputation clinical factors contributing most. Prescriptive analysis revealed that targeted quality improvement at facilities serving high proportions of Black Veterans could reduce disparities by 32.5%, while interventions addressing end-stage renal disease could reduce advanced LLP disparities by 33.6%. Targeted resource allocation to facilities serving high proportions of racial and ethnic minority Veterans and integrated care pathways for Veterans with complex comorbidities represent actionable interventions for reducing prosthetic care inequities.

US maternal mortality and severe maternal morbidity (SMM) are marked by substantial disparities by race, payer, and geography. To the extent that such disparities are driven by differences across hospitals rather than within hospitals, understanding what shapes delivery hospital choice can inform policy responses. To examine how distance, hospital attributes, and maternal characteristics jointly shape delivery hospital choice, and whether patterns differ between urban Atlanta and smaller Georgia markets. Retrospective observational study using a conditional logit model to estimate delivery hospital choice. Hospital markets were defined through community detection on patient-flow data. We report marginal effects on selection probability. Seven hundred ten thousand eight hundred seventy deliveries across 84 Georgia hospitals, 2016-2021. Deterministically linked hospital discharge, birth, and fetal death records, supplemented with American Hospital Association, CMS, and Area Resource Files data. Distance (in miles) strongly deterred hospital selection in both markets, with greater sensitivity in Atlanta (-2.7 percentage points [pp] per additional mile) than outside Atlanta (-1.9 pp/mile). Individuals preferred hospitals with higher perinatal levels of care and teaching status. A hospital's elective C-section rate was negatively associated with its selection outside Atlanta (-1.3 pp) but positively in Atlanta (+2.5 pp). Higher comorbidity was associated with higher-quality hospital selection, though the highest-risk Atlanta individuals showed lower preference for high-elective-C-section hospitals. Delivery hospital choice in Georgia reflects distance, practice environment, insurance, and clinical complexity, with urban/nonurban differences. Medicaid-insured individuals show delivery patterns consistent with provider supply-side constraints, which may raise concerns to the extent that they face an elevated risk of adverse maternal outcomes. Findings inform payment and referral policies improving access to risk-appropriate delivery settings and reducing maternal health disparities.

To estimate the effects of specialty consultations on health and utilization outcomes among general medicine admissions. Specialist physicians are frequently consulted in the inpatient setting to obtain additional expertise or get access to specific treatments. However, the effects of these consults have not been rigorously studied. In this quasi-experimental study, I analyzed the effects of an infectious disease, cardiology, or nephrology consult that occurred within 24 hours of admission. To address patient-level confounding, consultant team workload, defined as consult orders per provider, served as an instrumental variable for consult receipt. I identified general medicine admissions from 3 teaching hospitals in Pennsylvania using electronic health record data spanning March 2017 to August 2024. Primary outcomes were length of stay and readmission, mortality, and specialty outpatient visit within 30 days of discharge. Among admissions whose consult probability varied by consultant workload, a specialty consult decreased 30-day readmission by 29.8 percentage points (pp) (95% CI: -52.0 to -7.7 pp) and increased 30-day outpatient visit by 18.6 pp (95% CI: 7.3-29.9 pp). The decrease in the probability of readmission was primarily driven by infectious disease consults and patients who had not received a specialty consult in the past year. Consults had no significant effects on mortality or length of stay. Specialty consults may reduce readmissions and improve continuity of care without increasing inpatient utilization on average.

Timely postpartum linkage to primary care is important for managing diabetes and hypertensive disorders of pregnancy (HDP), yet linkage remains suboptimal. Medicaid accountable care organizations (ACOs) aim to strengthen care coordination and improve postpartum linkage, although effects may vary by ACO design. Evaluate whether Massachusetts Medicaid ACO implementation was associated with changes in postpartum primary care linkage among enrollees with diabetes or HDP and whether effects differed by ACO model. Retrospective cohort study using the 2016-2023 Massachusetts All-Payer Claims Database (APCD). Using a difference-in-differences approach, we compared outcomes before (2016-2017) versus after (2018-2023) implementation among health system/managed care partnership ACOs, primary care-led ACOs, and non-ACO enrollees. In total, 38,340 Medicaid-covered deliveries among enrollees ages 18-44 with diabetes or HDP, continuously enrolled for at least 60 days before and after delivery. A primary care visit within 3, 6, and 12 months postpartum. Overall, 53.6%, 76.8%, and 90.3% were linked to primary care by 3, 6, and 12 months, respectively. Although positive, ACO implementation was not associated with statistically significant changes at any interval for either model. At 3 months, model 1 was associated with a 2.44 percentage point [PP] increase (95% CI: -1.7 to 6.6) and model 2 with a 3.73 PP increase (95% CI: -0.5 to 8.0) versus non-ACO enrollees. Massachusetts Medicaid ACO implementation was not associated with significant changes in postpartum primary care linkage. Explicit postpartum performance measures and stronger coordination between maternity and primary care clinicians may be needed to improve transitions to ongoing care.

Pulmonary hypertension (PH) care requires extensive resources and support, including expert multidisciplinary teams, advanced diagnostic modalities, and complex pharmacologic therapies. While this infrastructure is standardized within accredited PH centers, less is known about resource availability outside of PH centers, where most patients with PH receive care. To explore PH-specific resource availability across the Veterans Health Administration (VA), which cares for over 250,000 patients with PH. Between November 2024 and January 2025, we surveyed pulmonary and cardiology providers within 66 highly resourced VA medical centers, exploring PH-specific structures, resources, and programs through structured and open-ended questions. We summarized structured responses as counts (percentages) by site and analyzed free-text responses using conventional content analysis. We overlayed maps of VA sites with PH experts and non-VA PH centers and associated 60-minute drive times. Providers at 61 sites responded (site-level response 92.4%). 57.4% of sites had a PH expert physician; few sites had other key personnel or PH-specific programs. Free-text responses highlighted (1) an overall lack of VA PH resources, (2) the value of PH expert physicians, (3) the need for PH support staff, and (4) challenges to providing PH-specific therapies. Geographic analyses revealed insufficient access to PH expertise in many U.S. regions. Within the largest U.S. integrated health care system, there is a paucity of resources vital for PH care. These findings highlight the need for strategies to build PH-specific resource infrastructure within VA and to better understand how these gaps affect PH care quality.

To examine whether Afro-Latino ancestry, nativity, and survey completion language among Latino health care workers are associated with experiences of workplace discrimination, witnessing discrimination against patients, and observing lower-quality care due to patients' race or ethnicity. Cross-sectional observational study using nationally representative survey data from the 2023 Commonwealth Fund, African American Research Collaborative Healthcare Workforce Survey, conducted from March 14 to April 5, 2023. Among Latino health care workers, 49.1% reported personally experiencing discrimination, 57.6% reported witnessing discrimination against patients, and 48.6% reported observing lower-quality care. In adjusted logistic regression models, reporting Afro-Latino ancestry was associated with 2.58 times the odds (95% CI: 1.66-4.02, P<0.01) of reporting personal experiences of discrimination, 2.13 times the odds (95% CI: 1.35-3.38, P<0.01) of reporting witnessing discrimination against patients, and 1.78 times the odds (95% CI: 1.13-2.79, P<0.05) of reporting observing lower-quality care due to a patient's race or ethnicity, compared with workers not reporting Afro-Latino ancestry. Foreign-born status and Spanish-language survey completion were not significantly associated with any of the 3 outcomes. Reported discrimination experiences among Latino health care workers vary substantially by Afro-Latino ancestry. Workers reporting Afro-Latino ancestry face and observe higher levels of racial discrimination, highlighting the importance of disaggregating Latino populations in research and policy efforts aimed at reducing inequities in health care delivery and the health care workforce.

Background:The purpose of this study was to determine the relationship between nurse staffing inadequacy in the emergency department (ED) and inpatient units on objective ED crowding measures.Methods:Three datasets from 2024 were linked: the Penn Nurses4All survey, CMS Hospital Compare, and the AHA Annual Hospital Survey. Nurses4All provided measures of nurse staffing inadequacy. The proportion of nurses reporting staffing inadequacy was the main exposure variable. Crowding measures included the percentage of patients who left the ED without being seen and patient length of stay (in minutes) for patients with and without psychiatric/mental health presentations. The analysis included hospital-level regression models adjusted for hospital characteristics.Results:The sample included 410 hospitals in 10 states. A 1 SD increase in ED nurses reporting staffing inadequacy was associated with higher hospital left without being seen rates (β 0.4, 95%CI 0.2, 0.6, p<.001), longer lengths of stay for ED patients (β 8.5, 95%CI 3.5, 13.6, p<.001), and patients with psychiatric/mental health concerns in the ED (β 18.4, 95%CI 3.6, 33.1, p<.05). A 1 SD increase in inpatient nurses reporting staffing inadequacy was associated with longer ED lengths of stay for patients with psychiatric/mental health concerns (β 18.0, 95%CI 5.8, 30.3, p<.01).Conclusion:Staffing a sufficient number of nurses in both ED and inpatient units is a promising strategy to alleviate ED crowding.

Two quality measures, initiation and engagement in substance use disorder (SUD) treatment (IET), have been adopted by stakeholders. Further evidence is needed to inform optimal use of these measures to support quality improvement efforts. The objective of this study was to examine variability, reliability, and multilevel correlates of IET. Retrospective cohort study of members of a large integrated health system in the Pacific Northwest. Descriptive statistics were used to characterize variation in quality. Mixed-effects models with random intercepts were applied to quantify variability and reliability at different health system levels. We examined associations between quality measures and a wide set of patient-, provider-, clinic-, and area-level characteristics. We examined 32,960 care episodes subject to IET quality criteria between 2017 and 2022. Overall, 30.0% and 7.8% of episodes met the criteria for initiation and engagement in SUD treatment, respectively. Little variation in initiation (2.8%) and engagement (3.9%) was collectively explained at the provider and clinic levels. No providers met the threshold for 70% reliability on an annual basis. Across varying assumptions of provider-level annual episode volume, clinics were unlikely to meet reliability thresholds. Factors consistently associated with IET included insurance type and history of behavioral health conditions. A low proportion of variation explained implies a larger number of episodes is needed to ensure reliable estimates. Stakeholders should apply IET measures cautiously, ensuring sufficient sample sizes to support robust measurement. Factors associated with a lower probability of meeting quality criteria can inform specific patients who may benefit from efforts to increase IET.

This paper introduces a special issue examining data infrastructure for patient-centered outcomes research that addresses health equity. Addressing the persistence and breadth of health inequalities in the United States requires ongoing expansion of the capacity to detect, monitor, and understand them. Data infrastructure is itself an equity policy matter: decisions about what data to collect, on whom, and in what form determine whose health inequities can be observed and, consequently, addressed. The 9 research papers in this issue are organized around 4 themes. The first examines new data sources and standards that extend what health systems can observe about the populations they serve. The second demonstrates how linking data across sectors enables analysis of social determinants that clinical records alone cannot capture. The third addresses strategies for disaggregating populations that are small, internally heterogeneous, or historically excluded from data collection. The fourth considers implementation-the organizational and institutional conditions under which new data systems are successfully adopted in practice. Together, the papers illustrate both the scientific possibilities created by deliberate investment in data capacity and the policy stakes of sustaining it.