Melissa Skanderson

Background: Steatotic liver disease (SLD) is highly prevalent in people with HIV (PWH), but factors influencing progression to hepatocellular carcinoma (HCC) and hepatic decompensation (HD) remain unclear. It is unknown if the risk of these outcomes associated with SLD differs by HIV status. Methods: Patients from the Veterans Aging Cohort Study-HIV (includes matched people without HIV [PWoH]) who underwent an ultrasound, computed tomography, or magnetic resonance imaging between 2001–2017 were included. Patients with diagnosed cirrhosis or chronic viral hepatitis were excluded. SLD was defined by a natural language processing algorithm; primary outcome of composite of HCC or HD was defined using International Classification of Diseases 9/10 codes and national cancer registry. Follow-up began on imaging study date and continued until incident HCC/HD, death, or 31 December 2024. Adjusted hazard ratios (aHRs) with 95% confidence intervals (CIs) of HCC/HD associated with SLD and HIV status were calculated. Results: Among 19 546 patients (mean age: 54 years; 96.6% male; 28.6% PWH), 13 617 (69.7%) had SLD identified by natural language processing. Rates of HCC/HD were lowest in PWoH and no SLD (18.0/10 000 person-years) and highest among PWH and SLD (46.8/10 000 person-years). When compared to PWoH without SLD, risk of HCC/HD was increased among PWH with SLD (aHR: 2.71; 95% CI: 2.10–3.49) and PWH without SLD (aHR: 1.62; 95% CI: 1.14–2.29), although no interaction between HIV and SLD was observed (P = .25). Conclusions: Among people without cirrhosis or chronic viral hepatitis, radiographic findings of SLD were associated with increased rates of HCC/HD, with the highest rate among PWH and SLD, independent of cardiometabolic factors, alcohol, and tobacco.

The Veterans Aging Cohort Study (VACS)‐National is a large, longitudinal real‐world data resource derived from electronic health records within the Department of Veterans Affairs (VA), the largest integrated healthcare system in the United States. As of December 2025, VACS‐National includes > 14.9 million Veterans who have received care in the VA since 2000. It captures information on VA‐related outpatient and inpatient care and includes structured (e.g., diagnostic codes, laboratory results, vital signs, dispensed medical products), semi‐structured (e.g., radiology and pathology reports) and unstructured (e.g., progress notes) fields, collected from over 1300 points of care nationwide. Its longitudinal structure supports extended follow‐up across demographically and clinically diverse populations within an integrated healthcare system. Key features for pharmacoepidemiological research include near real‐time availability of data on dispensed medications, including biologics, vaccines, and devices; routinely‐collected laboratory measurements; and computable phenotypes, including validated natural language phenotypes. The resource includes linkages to Centers for Medicare and Medicaid Services (CMS) data, VA Community Care data, National Death Index, and deeply phenotyped VACS sub‐cohorts with an extensive library of biomarkers and survey data. VACS‐National has supported a wide range of research, including drug utilization, drug safety, comparative effectiveness, and epidemiologic and health outcomes research. Strengths include its national scale, longitudinal follow‐up, and rich clinical record; limitations include a small proportion of women and potential incomplete capture of care outside the system or not recoverable through linked datasets. VACS‐National provides a comprehensive platform for generating real‐world evidence to inform clinical, regulatory, and public health decision‐making.

INTRODUCTION: Early detection of pancreatic ductal adenocarcinoma (PDAC) improves survival. However, screening recommendations are limited to individuals with hereditary risk, accounting for only 10% of PDAC. We explore the feasibility of developing and validating an electronic health record-based model to identify high-risk individuals for PDAC screening within the asymptomatic general population. METHODS: Using multivariable Cox regression, we developed a diagnostic model to predict time to PDAC within 3 years in the Veterans Health Administration. We evaluated the final model using internal and temporally separate data sets using Akaike Information Criterion, Harrell c statistic, calibration curves, and sensitivity/specificity corresponding to a 3-year risk screening threshold of 1%. RESULTS: Among 9,351,261 individuals, 26,119 (0.3%) developed PDAC (107.6 cases per 100,000 person-years) within 3 years. The final model included age, pancreatic cyst, pancreatitis, smoking status, history of a localized solid tumor, race/ethnicity, and body mass index. Glucose and albumin values were highly important, in addition to other metabolic, inflammatory, and liver-related laboratory values. The c statistic (95% CI) was 0.75 (0.75–0.76) in development, 0.75 (0.75–0.76) in internal validation, and 0.74 (0.73–0.75) in temporal validation. At a 3-year risk threshold of 1.0%, 11% of the population would undergo screening, capturing 30% of the PDAC cases. DISCUSSION: We demonstrate good model discrimination in independent data. Compared with current screening practices targeting only genetically predisposed individuals, its implementation could identify 3 times as many PDAC cases. However, predictors beyond the electronic health record (EHR) may be needed to further improve the feasibility of generalized screening.

Background: Intimate partner violence (IPV) is a significant public health problem with far-reaching consequences. The health care system plays an integral role in the detection of and response to IPV. Historically, the majority of IPV screening initiatives have targeted women of reproductive age, with little known about men’s IPV screening experiences or the impact of screening on men’s health care. The Veterans Health Administration (VHA) has called for an expansion of IPV screening, providing a unique opportunity for a large-scale evaluation of IPV screening and response across all patient populations. Objective: In this protocol paper, we describe the recently funded Partnered Evaluation of Relationship Health Innovations and Services through Mixed Methods (PRISM) initiative, aiming to evaluate the implementation and impact of the VHA’s IPV screening and response expansion, with a particular focus on identifying potential gender differences. Methods: The PRISM Initiative is guided by the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) and Consolidated Framework for Implementation Research (CFIR 2.0) frameworks. We will use mixed methods data from 139 VHA facilities to evaluate the IPV screening expansion, including electronic health record data and qualitative interviews with patients, clinicians, and national IPV program leadership. Quantitative data will be analyzed using a longitudinal observational design with repeated measurement periods at baseline (T0), year 1 (T1), and year 2 (T2). Qualitative interviews will focus on identifying multilevel factors, including potential implementation barriers and facilitators critical to IPV screening and response expansion, and examining the impact of screening on patients and clinicians. Results: The PRISM initiative was funded in October 2023. We have developed the qualitative interview guides, obtained institutional review board approval, extracted quantitative data for baseline analyses, and began recruitment for qualitative interviews. Reports of progress and results will be made available to evaluation partners and funders through quarterly and end-of-year reports. All data collection and analyses across time points are expected to be completed in June 2026. Conclusions: Findings from this mixed methods evaluation will provide a comprehensive understanding of IPV screening expansion at the VHA, including the implementation and impact of screening and the scope of IPV detected in the VHA patient population. Moreover, data generated by this initiative have critical policy and clinical practice implications in a national health care system. International Registered Report Identifier (IRRID): PRR1-10.2196/59918

Background: Steatotic liver disease (SLD) is a growing phenomenon, and our understanding of its determinants has been limited by our ability to identify it clinically. Natural language processing (NLP) can potentially identify hepatic steatosis systematically within large clinical repositories of imaging reports. We validated the performance of an NLP algorithm for the identification of SLD in clinical imaging reports and applied this tool to a large population of people with and without HIV. Methods: Patients were included in the analysis if they enrolled in the Veterans Aging Cohort Study between 2001 and 2017, had an imaging report inclusive of the liver, and had ≥2 years of observation before the imaging study. SLD was considered present when reports contained the terms “fatty,” “steatosis,” “steatotic,” or “steatohepatitis.” The performance of the SLD NLP algorithm was compared to a clinical review of 800 reports. We then applied the NLP algorithm to the first eligible imaging study and compared patient characteristics by SLD and HIV status. Results: NLP achieved 100% sensitivity and 88.5% positive predictive value for the identification of SLD. When applied to 26,706 eligible Veterans Aging Cohort Study patient imaging reports, SLD was identified in 72.2% and did not significantly differ by HIV status. SLD was associated with a higher prevalence of metabolic comorbidities, alcohol use disorder, and hepatitis B and C, but not HIV infection. Conclusions: While limited to those undergoing radiologic study, the NLP algorithm accurately identified SLD in people with and without HIV and offers a valuable tool to evaluate the determinants and consequences of hepatic steatosis.

BACKGROUND Intimate partner violence (IPV) is a significant public health problem with far-reaching consequences. The health care system plays an integral role in the detection of and response to IPV. Historically, the majority of IPV screening initiatives have targeted women of reproductive age, with little known about men’s IPV screening experiences or the impact of screening on men’s health care. The Veterans Health Administration (VHA) has called for an expansion of IPV screening, providing a unique opportunity for a large-scale evaluation of IPV screening and response across all patient populations. OBJECTIVE In this protocol paper, we describe the recently funded Partnered Evaluation of Relationship Health Innovations and Services through Mixed Methods (PRISM) initiative, aiming to evaluate the implementation and impact of the VHA’s IPV screening and response expansion, with a particular focus on identifying potential gender differences. METHODS The PRISM Initiative is guided by the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) and Consolidated Framework for Implementation Research (CFIR 2.0) frameworks. We will use mixed methods data from 139 VHA facilities to evaluate the IPV screening expansion, including electronic health record data and qualitative interviews with patients, clinicians, and national IPV program leadership. Quantitative data will be analyzed using a longitudinal observational design with repeated measurement periods at baseline (T0), year 1 (T1), and year 2 (T2). Qualitative interviews will focus on identifying multilevel factors, including potential implementation barriers and facilitators critical to IPV screening and response expansion, and examining the impact of screening on patients and clinicians. RESULTS The PRISM initiative was funded in October 2023. We have developed the qualitative interview guides, obtained institutional review board approval, extracted quantitative data for baseline analyses, and began recruitment for qualitative interviews. Reports of progress and results will be made available to evaluation partners and funders through quarterly and end-of-year reports. All data collection and analyses across time points are expected to be completed in June 2026. CONCLUSIONS Findings from this mixed methods evaluation will provide a comprehensive understanding of IPV screening expansion at the VHA, including the implementation and impact of screening and the scope of IPV detected in the VHA patient population. Moreover, data generated by this initiative have critical policy and clinical practice implications in a national health care system. INTERNATIONAL REGISTERED REPORT PRR1-10.2196/59918

Objective: To determine changes in opioid prescribing among veterans with headaches during the coronavirus disease of 2019 (COVID‐19) pandemic by comparing the stay‐at‐home phase (March 15 to May 30, 2020) and the reopening phase (May 31 to December 31, 2020). Background: Opioid prescribing for chronic pain has declined substantially since 2016; however, changes in opioid prescribing during the COVID‐19 pandemic among veterans with headaches remain unknown. Methods: This retrospective cohort study utilized regression discontinuity in time and difference‐in‐differences design to analyze veterans aged ≥18 years with a previous diagnosis of headache disorders and an outpatient visit to the Veterans Health Administration (VHA) during the study period. We measured the weekly number of opioid prescriptions, the number of days supplied, the daily dose in morphine milligram equivalents (MMEs), and the number of prescriptions with ≥50 morphine equivalent daily doses (MEDD). Results: A total of 81,376 veterans were analyzed with 589,950 opioid prescriptions. The mean (SD) age was 51.6 (13.5) years, 57,242 (70.3%) were male, and 53,464 (65.7%) were White. During the pre‐pandemic period, 323.6 opioid prescriptions (interquartile range 292.1–325.8) were dispensed weekly, with an median (IQR) of 24.1 (24.0–24.4) days supplied and 31.8 (31.2–32.5) MMEs. Transition to stay‐at‐home was associated with a 7.7% decrease in the number of prescriptions (incidence rate ratio [IRR] 1.077, 95% confidence interval [CI] 0.866–0.984) and a 9.8% increase in days supplied (IRR 1.098, 95% CI 1.078–1.119). Similar trends were observed during the reopening period. Subgroup analysis among veterans on long‐term opioid therapy also revealed 1.7% and 1.4% increases in days supplied during the stay‐at‐home (IRR 1.017, 95% CI 1.009–1.025) and reopening phase (IRR 1.014, 95% CI 1.007–1.021); however, changes in the total number of prescriptions, MME/day, or the number of prescriptions >50 MEDD were insignificant. Conclusion: Prescription opioid access was maintained for veterans within VHA during the pandemic. The de‐escalation of opioid prescribing observed prior to the pandemic was not seen in our study.

Background: The association between cannabis use and HIV-1 RNA (viral load) among people with HIV (PWH) engaged in care is unclear. Methods: We used data collected from 2002 to 2018 on PWH receiving antiretroviral therapy (ART) enrolled in the Veterans Aging Cohort Study. Generalized estimating equations were used to estimate associations between self-reported past-year cannabis use and detectable viral load (≥500 copies/mL), with and without adjustment for demographics, other substance use, and adherence. Results: Among 2515 participants, 97% were male, 66% were Black, the mean age was 50 years, and 33% had detectable HIV viral load at the first study visit. In unadjusted analyses, PWH with any past-year cannabis use had 21% higher odds of a detectable viral load than those with no past-year use (OR = 1.21; 95% CI, 1.07–1.37). However, there was no significant association between cannabis use and viral load after adjustment. Conclusions: Among PWH engaged in care and receiving ART, cannabis use is associated with decreased adherence in unadjusted analyses but does not appear to directly impact viral control. Future studies are needed to understand other potential risks and benefits of cannabis use among PWH.

The lack of a reliable approach to assess quality of pain care hinders quality improvement initiatives. Rule-based natural language processing algorithms were used to extract pain care quality (PCQ) indicators from documents of Veterans Health Administration primary care providers for veterans diagnosed within the past year with musculoskeletal disorders with moderate-to-severe pain intensity across 2 time periods 2013 to 2014 (fiscal year [FY] 2013) and 2017 to 2018 (FY 2017). Patterns of documentation of PCQ indicators for 64,444 veterans and 124,408 unique visits (FY 2013) and 63,427 veterans and 146,507 visits (FY 2017) are described. The most commonly documented PCQ indicators in each cohort were presence of pain, etiology or source, and site of pain (greater than 90% of progress notes), while least commonly documented were sensation, what makes pain better or worse, and pain's impact on function (documented in fewer than 50%). A PCQ indicator score (maximum = 12) was calculated for each visit in FY 2013 (mean = 7.8, SD = 1.9) and FY 2017 (mean = 8.3, SD = 2.3) by adding one point for every indicator documented. Standardized Cronbach alpha for total PCQ scores was 0.74 in the most recent data (FY 2017). The mean PCQ indicator scores across patient characteristics and types of healthcare facilities were highly stable. Estimates of the frequency of documentation of PCQ indicators have face validity and encourage further evaluation of the reliability, validity, and utility of the measure. A reliable measure of PCQ fills an important scientific knowledge and practice gap.