The investigators are conducting the planned work through the HIV and Alcohol Research Center focused on Polypharmacy, or HARP, and aim to recruit 60 adults receiving care at the Atlanta Veterans Affairs Infectious Disease Clinic. Twenty participants are planned for each medication-specific pilot. Eligibility criteria include alcohol use disorder, a phosphatidylethanol, or PEth, concentration above 20 mg/nL, and polypharmacy, defined in the protocol as taking more than five medications. Each study medication would be prescribed for 12 weeks by an addiction physician. Participants would also meet with a clinical pharmacist for a motivational interviewing-based counseling session concerning their personal health risks associated with alcohol use in the context of polypharmacy.

Feasibility will be evaluated through recruitment, enrollment, retention, visit attendance and adherence to the study medication. The protocol identifies the proportion of patients offered participation who complete enrollment as the primary feasibility outcome. Acceptability will be examined through a participant satisfaction questionnaire and analysis of qualitative information from a subset of participants. The qualitative material is intended to capture participants’ views of the intervention’s different components and their perceived impact on alcohol consumption. These measures address whether the intervention can be delivered in the intended clinic and whether participants regard it favorably, rather than whether it produces a clinically proven reduction in drinking.

Safety and tolerability will be assessed by reviewing clinical and laboratory information and recording the frequency of adverse events. The investigators will also make descriptive comparisons before and after the 12-week intervention. Planned measures include readiness to change, self-reported and laboratory-based indicators of alcohol consumption, PEth concentration, polypharmacy, self-reported and laboratory-based measures of tobacco use, bothersome symptoms, and biomarkers of health related to HIV. The absence of a randomized comparison group and the open-label design mean that any before-and-after differences cannot establish that a medication caused a change in alcohol consumption. The protocol also does not provide evidence that any of the three medications is safe, tolerable or effective for adults with HIV and polypharmacy.

The researchers hypothesize that the three off-label medications, each combined with the pharmacist-delivered behavioral intervention, will be feasible, acceptable, safe and tolerable and will be associated with changes in alcohol consumption. Those statements are prospective expectations, not observed findings. The study’s limited scope—three separate pilots, 60 participants in total, 20 per medication, one Veterans Affairs clinic and a 12-week treatment period—means that it is intended to provide preliminary operational and descriptive information. The investigators state that future research will evaluate the most promising intervention package in randomized controlled trials. Until such trials produce comparative results, the protocol supports planning and feasibility assessment, not conclusions about the clinical benefit of spironolactone, varenicline or semaglutide for this population.

Subject of Research: Three planned open-label pilot studies of off-label medications for alcohol use disorder in adults with HIV and polypharmacy

Article Title: Feasibility, acceptability, safety, tolerability, and changes in alcohol consumption associated with off-label medications for alcohol use disorder among patients with HIV: protocol for an open-label pilot study

Article References: Haque, L. Y., Maisto, S. A., Weiss, J., Marconi, V. C., Hsieh, E., Garcia, A., Womack, J. A., Kidwai-Khan, F., Tang, Y., Dziura, J., Leggio, L., Bryant, K., Justice, A. C., Fiellin, D. A., & Edelman, E. J. (2026). Feasibility, acceptability, safety, tolerability, and changes in alcohol consumption associated with off-label medications for alcohol use disorder among patients with HIV: protocol for an open-label pilot study. Addiction Science & Clinical Practice. https://doi.org/10.1186/s13722-026-00728-5

Image Credits: AI Generated

DOI: 10.1186/s13722-026-00728-5

Keywords: HIV, alcohol use disorder, polypharmacy, spironolactone, varenicline, semaglutide, open-label pilot, clinical protocol, PEth, Veterans Affairs, Feasibility, acceptability

The research team, led by Sarah C. Keithly of the VA Puget Sound Healthcare System’s Center of Innovation for Veteran-Centered and Value-Driven Care, set out to fill a gap in the scientific record. Early studies of the VA transition documented profound disruption to care during the initial implementation phase, including clinician burnout, frustrated patients, and confusion over redefined roles. Far less was known about what happened after the dust settled. To find out, the investigators used a mix of purposive and snowball sampling to recruit direct care clinicians across a range of professions at the first five sites to adopt the new federal system. Of 104 clinicians invited, 30 — a participation rate of 28.8 percent — agreed to semi-structured interviews. The team then applied a hybrid inductive-deductive content analysis, combining templated summaries with matrix analysis, a method designed to surface both expected and unexpected patterns in qualitative data.

What emerged was a portrait of a workforce that has learned to survive a difficult technology by routing around it. The analysis generated four interlocking themes. First, ongoing EHR-related challenges continued to impede clinicians’ job performance long after go-live. Second, workarounds emerged in direct response to those persistent challenges. Third, clinicians perceived these workarounds as necessary but risky — to patients, to users themselves, and to the health care system as a whole. Fourth, and perhaps most troubling, as the underlying EHR problems persisted, the workarounds stopped feeling like temporary fixes and became routine practice. In other words, the improvisations that clinicians adopted to keep care moving were not fading away as the system matured; they were hardening into standard operating procedure.

The concept of the workaround occupies a well-studied niche in health informatics research. Prior work, including Koppel and colleagues’ influential analysis of barcode medication administration systems and subsequent scoping reviews of EHR workarounds, has shown that clinicians frequently develop alternate pathways when technology conflicts with clinical reality. These can range from harmless efficiency tricks to genuinely dangerous practices, such as documenting medication administration before it occurs or sharing login credentials to save time. The sociotechnical perspective, formalized in frameworks like Sittig and Singh’s model for studying health information technology in complex adaptive systems, holds that such behavior is rarely a simple failure of individual discipline. Instead, workarounds are signals — diagnostic clues that the interaction between technology, workflow, and organization has broken down somewhere. The new VA study treats them exactly that way, as a window into where the federal EHR is still failing its users.

The technical stakes of an EHR-to-EHR transition are considerable. Unlike a first-time implementation, a transition requires migrating years of clinical data, rebuilding decision-support rules, recreating order sets and documentation templates, and retraining a workforce that had achieved fluency in the old system. Systematic reviews of EHR transitions, including a 2023 review in the same journal, have catalogued recurring pitfalls: data loss during migration, mismatched workflows, degraded usability, and communication breakdowns. The VA’s homegrown system, known as VistA, had decades of local customization and a devoted user base, which made the switch to a commercial vendor product especially jarring. Previous mixed-methods evaluations of the transition documented clinicians fighting burnout for the first time, struggling with role-specific workflows, and fielding frustrated patients who bore the brunt of scheduling and documentation errors. The new study extends that timeline, showing that the problems did not resolve once the initial crisis passed.

The persistence of workarounds years into implementation carries specific safety implications. When a clinician devises an informal path around a system limitation, that path typically bypasses the safeguards built into the official workflow — the hard stops, the required fields, the verification steps. A workaround that saves thirty seconds on an order entry screen may also skip a drug-interaction check. One that speeds up documentation may leave critical information in a place where the next clinician cannot find it. The study’s participants were acutely aware of this tension. They described their workarounds as necessary to deliver care at all, yet simultaneously risky to patients and to the integrity of the medical record. That dual perception — beneficial and dangerous at once — is precisely what makes workarounds so difficult to manage through policy alone. Banning them without fixing the underlying problems simply pushes the improvisation further underground, where it becomes invisible to safety monitoring.

The normalization of workarounds also has implications for how health systems evaluate technology. If informal practices become routine, then the data flowing into the EHR increasingly reflects not actual clinical processes but the distorted output of patched-together workflows. Quality metrics, utilization data, and clinical decision support all depend on the assumption that documentation mirrors reality. When that assumption erodes, the organization loses visibility into its own operations. The VA researchers argue that this is why evaluating the role and impact of workarounds should be a formal part of EHR-to-EHR transitions, not an afterthought. Systematic workaround analysis, such as the SEWA framework for sociotechnical analysis of EHR workarounds, can identify which workarounds indicate design flaws that need engineering fixes, which reflect training gaps, and which reveal workflow mismatches that require organizational redesign rather than software changes.

The timing of these findings matters for the VA’s broader modernization program. The department has paused and restarted rollouts in recent years, and officials have announced early-stage planning for the next phase of federal EHR deployment while continuing improvement efforts at existing sites. The study’s conclusions suggest that the lessons from the first five sites should inform those decisions. If persistent EHR challenges continue to generate workaround reliance years after go-live, then simply extending the same implementation model to new sites risks replicating the same pattern. The authors emphasize that many of the transition’s challenges have persisted beyond the initial implementation phase, and that this persistence — not the transition itself — is what sustains the workaround culture. That distinction reframes the problem from a temporary disruption to be endured into a chronic condition to be treated.

For the wider health informatics community, the study adds an important longitudinal dimension to a literature dominated by snapshots taken during or immediately after implementation. Most organizations that swap one EHR for another — hospitals consolidating, health systems merging, national programs modernizing — face the same technical and human factors: interface usability, documentation burden, workflow fragmentation, and the sheer cognitive cost of relearning. The VA experience, documented with methodological care through information-power-guided sampling and rigorous qualitative analysis, offers a preview of what the years after a big-bang implementation can look like when problems are not fully resolved. The message from clinicians is not that the new system is unusable, but that using it as designed has become the exception rather than the rule. Closing that gap, the researchers argue, requires treating workarounds not as clinician misbehavior but as actionable intelligence — a map, drawn by the people closest to the work, of exactly where the system still needs to be fixed.

Subject of Research: Clinician workarounds and persistent challenges following the VA's transition to a federal electronic health record system

Article Title: “Most of what I do is a workaround now”: Clinician Use of Workarounds Following an EHR Transition

Article References: Keithly, S. C., Sulc, C., Cole, E., Sterling, R., Lin, Y.-L., Obara, E., Shirley, S., Wong, E. S., Rinne, S. T., & Young, J. (2026). “Most of what I do is a workaround now”: Clinician Use of Workarounds Following an EHR Transition. Journal of General Internal Medicine. https://doi.org/10.1007/s11606-026-10840-6

Image Credits: AI Generated

DOI: 10.1007/s11606-026-10840-6

Keywords: electronic health record, EHR transition, workarounds, Veterans Affairs, health informatics, clinician burnout, patient safety, workflow, qualitative research, health IT, documentation burden, sociotechnical systems

The intervention at the heart of the Whole Health Options and Pain Education, or wHOPE, study is the Whole Health Team, an interdisciplinary unit composed of a medical provider, a complementary and integrative health provider, and a health coach. Together, these clinicians provide holistic, non-pharmacological pain care grounded in VA’s broader Whole Health approach, which begins with open-ended inquiry into what matters most to each patient and proceeds through collaborative Personal Health Planning. Over twelve months, patients attended five or more collocated visits with the team’s medical and integrative providers, supplemented by eight or more health coaching visits, while weekly team huddles supported case management and care planning. In a national randomized controlled trial of 764 veterans with moderate to severe chronic pain, the Whole Health Team outperformed both modified Cognitive Behavioral Therapy for Chronic Pain and usual care in reducing pain interference and increasing use of non-pharmacological pain services, with patients also reporting greater improvements in overall health status and treatment satisfaction.

Given that demonstrated effectiveness, the research team led by Natalie Purcell, Liliana C. Moore, William C. Becker, and Karen H. Seal turned to a critical follow-up question: can this model actually be scaled? Because the Whole Health Team approach is not simply multimodal but also team-based, interdisciplinary, and integrated, requiring collocated clinical visits, routine coaching, and weekly huddles, it is more complex and resource-intensive than many other pain interventions. To investigate, the researchers conducted semi-structured interviews with 43 clinicians and staff involved in implementing the intervention, including 14 health coaches, 6 primary care providers, 6 integrative-trained providers, 5 other clinical professionals, 8 local site investigators, and 4 study coordinators. Guided by the Practical Robust Implementation and Sustainability Model, a framework that maps contextual factors from planning through sustainment, the team used template-based rapid analysis to distill themes from interviews lasting 30 to 60 minutes each.

The first major theme concerned team composition and collaboration, and here the clinicians were emphatic. They praised the interdisciplinarity of the model and described working in a genuinely integrated fashion rather than in silos. One medical provider captured the spirit of the collaboration vividly, recalling that the team was working with patients together, talking together, interrupting each other, and asking questions rather than operating separately. Collocated patient visits served as a central venue for this active collaboration, but so did the weekly huddles between visits, where hearing one another’s perspectives helped the team generate multiple options when patients faced challenges. A complementary and integrative health clinician noted that a single lens might not be the best thing for the patient, and expressed appreciation for the ability to hear the same piece of information and encounter completely different perspectives on how to manage it. Clinicians also believed that visible collaboration increased veteran engagement, with one coach observing that simply knowing the team was working together on their behalf gave patients another layer of buy-in.

Consistency of team membership emerged as another essential ingredient. Clinicians stressed that building trust with patients requires time and continuity, and that the twelve-month structure of regular clinical and coaching visits cultivated increased trust, deeper rapport, and genuine continuity of care. Patients came to depend on a familiar team they got to know, which in turn facilitated active involvement in care planning. Yet sustaining that consistency proved difficult. Because clinicians were volunteers lending their time from other duties, they were sometimes pulled off the study to devote resources elsewhere, a problem amplified during the COVID-19 pandemic during which all study interventions were delivered virtually. Clinician turnover interrupted care relationships and left key roles vacant at times, burdening remaining team members and making it harder to practice with a Whole Health approach. Interviewees stressed that team stability must be prioritized if relationship-based care is to survive contact with real-world staffing pressures.

Adequate, formally allocated clinician effort was perhaps the most contested resource of all. The Whole Health Teams operated in an institutional environment focused on optimizing productivity, where bookable hours were measured closely and every clinic scheduling grid was scrutinized. Both clinicians and site investigators emphasized the importance of protected time for team work, including dedicated clinic hours, time for writing notes, and time for the weekly huddles they considered critical. All participating sites did secure protected time, but doing so required staunch advocacy amid competition for clinical resources, and maintaining it remained an ongoing challenge. One site investigator described it as probably the biggest obstacle the team had faced. Clinicians also valued formal orientation to the team, which covered roles, visit protocols, and documentation requirements, though some, including several medical providers, retained uncertainty about their prescribing role relative to patients’ primary care providers, underscoring the need for clearly delineated responsibilities in interdisciplinary teams.

The second major theme involved organizational infrastructure and integration, beginning with the need to fill gaps rather than duplicate existing services. Because some VA health systems already offer pain-management and wellness programs, clinicians and investigators argued that the more resource-intensive Whole Health Team model must demonstrate unique value to make a viable business case for sustainment. They found that value in delivering an integrated, consistent message to each patient. One medical provider lamented that the health system is so fractured that patients see different people who tell them different things, and described the team as an efficient and effective way to help patients with a coherent care plan, noting that veterans like to see that their clinicians are all on the same page. The model also improved the clinicians’ own work experience, fostering mutual support and confidence when caring for patients with complex needs. At the same time, interviewees identified shortcomings: coordination with primary care sometimes felt informal, relying on discretionary co-signature of notes that primary care providers did not always read, and referral pathways to wellness and complementary modalities were often poorly mapped, forcing coaches to act as conduits to information that higher-level staff knew less and less about.

The third theme centered on administration and documentation, an unglamorous but decisive factor. Implementing collocated visits and concurrent health coaching is administratively complicated, and each site benefited from a study-funded, full-time coordinator who scheduled meetings and patients, set up clinic grids, collected point-of-care measures, tracked visits, completed documentation, made reminder calls, and served as an information hub for the whole team. One coordinator cautioned bluntly that if the model were implemented elsewhere, the level of administrative support provided in the study simply would not be available in a clinical service. Clinicians also chafed against standardized clinical note templates designed for study data collection, which felt ill-suited to personalized whole-person care. One provider asked why they needed to do math during a visit and take time away from listening to a veteran’s story, while another complained that templates force a robotic style that annoys patients. The consensus favored simpler, more flexible documentation that could adapt to each visit’s focus.

Perhaps the most striking finding was the depth of clinicians’ belief in the Whole Health model despite every implementation hurdle. Interviewees described practicing in line with their own values, connecting with patients more authentically, and witnessing emotional exit visits in which patients felt deeply cared for and equipped with new resilience and tools. One provider offered a sentiment that captures the model’s philosophy: patients are people, more than just a list of diagnoses, and they are fun and complicated. These accounts align with broader evidence that Whole Health practice may reduce clinician stress and burnout, and with VA survey findings that clinicians engaged in Whole Health view their workplaces more favorably and are less likely to resign. Yet many participants doubted the system would retain and spread the teams, perceiving the model as resource-intensive in an environment that rewards volume and perceived efficiency over quality, experience, and outcomes. They saw the teams as an upstream investment with downstream benefits, but acknowledged that a comprehensive longer-term cost-effectiveness analysis may be needed, particularly as an alternative to interventional pain care.

The study’s lessons amount to a practical blueprint for any health system contemplating integrated, person-centered pain care. Success requires consistent team membership, sufficient protected clinical effort, well-defined roles, team-based training, routine huddles, and skilled administrative support that could be provided by a nurse care manager or medical support assistant in the absence of a study coordinator. It also demands organizational readiness: accessible complementary and integrative health modalities, wellness programs, and health coaching, along with clear referral pathways connecting pain teams to those resources. Deeper integration with primary care, through periodic in-services or coaches already embedded in primary care, could strengthen both patient care and sustainability. As VA continues its transformation into a Whole Health System of Care, and as other integrated systems such as Kaiser Permanente pursue similar holistic models, the wHOPE findings illuminate both the promise and the price of treating chronic pain as a whole-person problem, offering hard-won insight into a care model that the clinicians who delivered it clearly believe is worth sustaining.

Subject of Research: Implementation of interdisciplinary whole-person chronic pain care in the Veterans Affairs Whole Health Team model

Article Title: Implementing Integrated Whole-Person Care for Chronic Pain: Lessons from VA’s Multisite wHOPE Study

Article References: Purcell, N., Moore, L. C., Becker, W. C., & Seal, K. H. (2026). Implementing Integrated Whole-Person Care for Chronic Pain: Lessons from VA’s Multisite wHOPE Study. Journal of General Internal Medicine. https://doi.org/10.1007/s11606-026-10825-5

Image Credits: AI Generated

DOI: 10.1007/s11606-026-10825-5

Keywords: chronic pain, Whole Health, Veterans Affairs, interdisciplinary care, implementation science, complementary and integrative health, health coaching, multimodal care, biopsychosocial, qualitative research, primary care, clinician burnout

Researchers led by Andrea L. Nevedal of the VA Center for Clinical Management Research at VA Ann Arbor Healthcare System and colleagues, including senior author Donna M. Zulman of VA Palo Alto and Stanford University, interviewed 25 veterans between July and October 2024. All participants had endorsed at least one social risk, such as food insecurity or financial strain, in a national survey administered across the Department of Veterans Affairs between March and June 2024, and all had agreed to a follow-up interview. Rather than asking a simple yes-or-no question about comfort with screening, the team structured their semi-structured interviews around the Theoretical Framework of Acceptability, a rigorous model that describes seven distinct determinants of whether patients judge a health care intervention to be acceptable: affective attitude, burden, ethicality, intervention coherence, opportunity costs, perceived effectiveness, and self-efficacy. The analysis used rapid directed content analysis, an approach designed to distill themes quickly while preserving fidelity to the guiding framework.

The headline finding is strikingly positive. Veterans in the study found social risk and needs screening to be acceptable, and many framed it in terms of duty and reciprocity. The ethicality determinant aligned with a core value the researchers describe as serving those who served: veterans viewed the VA’s interest in housing, food, and financial stability as consistent with the institution’s mission, provided staff explain how such questions belong in health care at all. That conditional is crucial. Veterans told the researchers they feel comfortable disclosing needs only when staff make clear that screening is an integral part of VA health care rather than an administrative intrusion. Without that framing, the same questions could feel invasive or bureaucratic.

Perceived burden, one of the framework’s seven determinants, was low, but again with a condition attached: screening must not interfere with the goals veterans bring to a health care visit. This is a technical point with real implementation consequences. When a patient arrives for a diabetes management appointment or a mental health session, additional questionnaires compete for limited visit time. The study suggests that screening tools embedded seamlessly into existing workflows, rather than layered on top of them, preserve the goodwill that makes disclosure possible. Similarly, veterans’ affective attitudes toward screening were dependent on what happened afterward. Screening that leads to resource receipt generates positive emotional responses; screening that leads nowhere risks breeding cynicism.

One of the most consequential findings concerns information risk. Opportunity costs did not outweigh screening benefits in the aggregate, but veterans worried that sensitive information could be used against them. This concern has particular resonance in the VA context, where disability compensation and eligibility are tied to documented conditions and histories. Patients who fear that disclosing food insecurity or financial strain might somehow jeopardize benefits have a rational incentive to underreport, and underreporting would quietly dismantle the entire screening enterprise. The study’s implication is that trust-building measures, including transparent explanations of how data are stored, who sees them, and how they relate to clinical care, are not optional extras but structural requirements for valid screening programs.

Intervention coherence, the degree to which patients understand how an intervention works, emerged as another area ripe for improvement. Veterans wanted clarification on how social risks actually impact health. This may sound like a communication detail, but the science behind it is substantive. A large body of literature links social determinants such as housing instability, food insecurity, and social isolation to measurable outcomes including cardiovascular disease, hospital utilization, and mortality, and organizations from the National Academies of Sciences, Engineering, and Medicine to the American College of Physicians and the American Heart Association have issued position statements urging clinical integration of social care. The Joint Commission has even established a National Patient Safety Goal aimed at improving health care equity. Veterans asking how a missed meal connects to a chronic disease diagnosis are asking a question the field has spent a decade learning to answer, and clinics that can answer it credibly are more likely to earn honest responses.

Perceived effectiveness was the final hinge. Veterans anticipated that screening would be worthwhile if the VA provided timely and appropriate resources in response to disclosed needs. Prior research has documented exactly why this matters. A systematic review in Health Equity found that social needs screening and interventions in clinical settings show variable effects on utilization, cost, and clinical outcomes, and commentators in JAMA Network Open have warned that screening is increasing faster than the infrastructure to act on results. A screening program that identifies needs without referral capacity is not merely ineffective; it can actively erode the patient trust that the VA study identifies as the foundation of acceptability. Prior qualitative work with primary care patients and caregivers, including studies in American Journal of Preventive Medicine and Journal of the American Board of Family Medicine, has reached consistent conclusions across populations: patients accept social screening when it comes with a credible pathway to help.

The study’s practical recommendations distill into three design principles. First, explain the purpose of screening and its relevance to health, so veterans understand why a clinician is asking about rent alongside blood pressure. Second, offer appropriate resources in response to disclosed needs, closing the loop between identification and action. Third, designate a point of contact and provide multiple avenues to access support, a recommendation aimed at the self-efficacy determinant of the framework. When patients know who to talk to and can reach help by phone, in person, or digitally, the psychological cost of acting on a disclosed need drops. Related VA programs, such as the Assessing Circumstances and Offering Resources for Needs, or ACORN, screening and referral initiative described in earlier work in the same journal, suggest the health system is already building toward these mechanisms.

Methodologically, the study is notable for its disciplined use of theory. By anchoring each interview and each analytic code to a named determinant of acceptability, the researchers converted a diffuse question, do patients like this?, into a structured map of the cognitive and emotional responses that determine program viability. The team applied purposeful sampling and information-power principles to guide sample size, and followed consensus-based standards for rigor in rapid qualitative analysis. The authors note the limits inherent in the design: participants were veterans who had already endorsed social risks on a national survey, meaning the findings speak most directly to the population screening programs are intended to reach, and anonymized quotations rather than full datasets were shared to protect confidentiality. The study was approved by the VA Central Institutional Review Board, and the views expressed are those of the authors, not necessarily the Department of Veterans Affairs.

The broader significance of this work extends well beyond the VA. Health systems nationwide are now embedding social risk screening into electronic health records, quality measures, and even accreditation standards, sometimes faster than evidence about patient receptivity can accumulate. This study supplies that evidence from a population that is often assumed to be guarded about personal hardship, and the verdict is encouraging: veterans welcome these conversations when they are explained honestly, embedded respectfully, and answered with real help. The title phrase the researchers borrowed from a participant, that screening would be a burden off my back, captures the essential insight. Patients do not experience questions about social hardship as the burden; the hardship itself is the burden, and a health system that asks, listens, and responds can genuinely lift it.

Subject of Research: Veterans' acceptability of social risk and needs screening in the Veterans Affairs health system

Article Title: “It Would be a Burden off My Back”: Veterans’ Perceptions of Social Risk and Needs Screening Acceptability

Article References: Nevedal, A. L., Koselka, E., Rao, M., Cohen, A. J., Chaudary, C., Greene, L., Slightam, C., Kimerling, R., Maciejewski, M. L., & Zulman, D. M. (2026). “It Would be a Burden off My Back”: Veterans’ Perceptions of Social Risk and Needs Screening Acceptability. Journal of General Internal Medicine. https://doi.org/10.1007/s11606-026-10805-9

Image Credits: AI Generated

DOI: 10.1007/s11606-026-10805-9

Keywords: veterans, social risk screening, social determinants of health, health-related social needs, Veterans Affairs, qualitative research, acceptability, food insecurity, patient-centered care, health equity, Theoretical Framework of Acceptability, Journal of General Internal Medicine

The study, published in EClinicalMedicine by Yan Xie, Taeyoung Choi, and Ziyad Al-Aly of the VA St. Louis Health Care System, drew on the electronic health records of the U.S. Department of Veterans Affairs, an integrated system spanning 172 health systems, 142 hospitals, and 1,241 outpatient sites. The researchers identified 1,401,492 participant-trials among veterans who attended an in-person primary care visit between September 15, 2025, and February 28, 2026, the period when the seasonal vaccine was widely available across the VA. Within this cohort, 526,350 participant-trials involved vaccination at the index visit and 875,142 involved no vaccination at that visit or during follow-up, and the cohort collectively contributed more than 635,000 person-years of observation, with a median follow-up of roughly six months.

What sets this analysis apart from the interim estimates issued by surveillance networks in England, Canada, and the United States is its design. Most seasonal vaccine effectiveness figures come from test-negative case-control studies, which compare vaccination rates between patients who test positive and those who test negative for influenza among people seeking care for acute respiratory illness. These designs efficiently control for care-seeking and testing behavior but estimate only relative protection among tested patients. The VA team instead emulated a target trial, a framework that asks what would happen if eligible people were, hypothetically, randomized to vaccination or no vaccination at a real clinical encounter. Because vaccination occurs throughout the season while influenza activity rises and falls, the investigators did not run a single trial spanning the entire season. They instead emulated 24 sequential 7-day trials, assigning vaccination status at the start of each window and following vaccinated and unvaccinated participants concurrently so that both groups faced the same circulating viruses at the same calendar time.

This structure was engineered to blunt two well-known distortions in observational vaccine research. Immortal time bias arises when follow-up time during which a person cannot experience the outcome is misattributed to one group, and healthy-vaccinee bias arises because people who choose to get vaccinated tend to be healthier and more engaged with care than those who do not. To reduce the latter, the team restricted eligibility to veterans with a primary care visit in the previous 18 months, guaranteeing comparable engagement with the health system, and excluded participant-visits involving acute illness, recent hospitalization, end-of-life care, advanced organ failure or cancer, recent surgery, and very high predicted short-term risks of hospitalization or death. The result was a comparison between people who plausibly could have been vaccinated and people who plausibly could have remained unvaccinated at the same visit.

Statistical refinement went further. The researchers applied marginal structural models with inverse-probability weighting, estimating propensity scores from a comprehensive covariate set that included demographics, comorbidities, frailty indices, laboratory values, healthcare utilization, vaccination histories across five prior influenza seasons, COVID-19 vaccination records, and algorithmically selected high-dimensional variables drawn from diagnoses, medications, laboratory results, and procedures. Veterans in the unvaccinated group who later received the vaccine were censored, with time-varying inverse probability of censoring weights correcting for the informative nature of that departure. Outcomes were strictly defined by laboratory confirmation: an influenza-associated emergency department or urgent care visit within one day of a positive test, or a hospitalization within 30 days of a positive test.

The headline numbers were sobering but far from discouraging. Vaccination was associated with a vaccine effectiveness of 22.25 percent against laboratory-confirmed influenza-associated emergency department visits, 31.84 percent against influenza-associated hospitalizations, and 21.95 percent against the composite of the two outcomes. In absolute terms, vaccination prevented approximately five emergency department visits and one hospitalization per 10,000 vaccinated persons over the follow-up period. Protection appeared consistent across time windows, with effectiveness against the composite outcome of roughly 21 to 24 percent during the intervals from 31 to 120 days after vaccination, and it held across prespecified subgroups defined by age, split at 65 years, and by immunocompromised status.

To gauge how much the subclade K mismatch mattered, the researchers ran the identical design on the 2024–2025 season. The contrast was clear: effectiveness in the prior season reached 31.03 percent against emergency department visits, 48.57 percent against hospitalizations, and 32.15 percent against the composite outcome. The ratio between seasons worked out to roughly 0.7, meaning relative effectiveness in 2025–2026 was about 30 percent lower than in the year before, a statistically significant decline consistent with the antigenic drift of subclade K. Yet the direction of benefit remained firmly positive, echoing interim estimates from the CDC VISION network, which reported about 30 percent protection against adult influenza-associated hospitalization, and from England and Canada, which found meaningful if reduced protection against medically attended H3N2 illness.

The authors deployed an unusually thorough robustness program. Thirteen sensitivity analyses varied the follow-up horizon, cohort exclusion criteria, outcome definitions, target populations, model specifications, weight truncation thresholds, grace periods, and landmark exposure definitions, and the estimates held steady throughout. Negative outcome control analyses provided an additional check for residual confounding: vaccination showed no association with all-cause hospitalization within 14 days of follow-up or all-cause death within the same window, exactly the null results expected if the design were not systematically biased. These controls cannot prove the absence of confounding, but they strengthen confidence that the observed protection reflects a genuine vaccine effect rather than an artifact of who chooses to be vaccinated.

Limitations remain. The VA population skews older, whiter, and more male than the general United States population, which may limit generalizability. Outcomes required laboratory confirmation within VA data, so infections tested or treated elsewhere were likely missed, meaning the absolute reductions probably represent a lower bound on the vaccine’s real-world impact. Vaccinations received outside the VA system may also have been incompletely captured, a form of misclassification that would tend to bias effectiveness estimates downward. The study did not evaluate influenza-associated death, because event counts were too small for adequate statistical power, nor did it estimate effectiveness against specific viral subtypes separately.

The public health message, however, comes through clearly. Even in a season when the predominant virus drifted away from the vaccine strain after strain selection, vaccination continued to reduce emergency department visits and hospitalizations attributable to laboratory-confirmed influenza. Given that seasonal influenza causes an estimated 9.4 million to 51 million illnesses, 120,000 to 710,000 hospitalizations, and 6,300 to 52,000 deaths annually in the United States, absolute reductions of even a few events per 10,000 people translate into substantial averted morbidity across the tens of millions of doses administered each year. The findings argue against letting an imperfect antigenic match undermine vaccination campaigns, and they make the case for timely, season-specific effectiveness monitoring using complementary designs. As the authors conclude, the 2025–2026 vaccine was less effective than its predecessor by roughly 30 percent in relative terms, but it still did its most important job: keeping veterans out of emergency departments and hospital beds during a challenging influenza season.

Subject of Research: Real-world effectiveness of the 2025–2026 seasonal influenza vaccine against influenza-associated emergency department visits and hospitalizations among U.S. veterans during an H3N2 subclade K-dominated season

Article Title: Effectiveness of the 2025–2026 seasonal influenza vaccine among U.S. veterans: an observational study

Article References: Xie, Y., Choi, T., & Al-Aly, Z. (2026). Effectiveness of the 2025–2026 seasonal influenza vaccine among U.S. veterans: an observational study. eClinicalMedicine, 100, Article 104183. https://doi.org/10.1016/j.eclinm.2026.104183

Image Credits: AI Generated

DOI: 10.1016/j.eclinm.2026.104183

Keywords: influenza vaccine, vaccine effectiveness, H3N2 subclade K, target trial emulation, Veterans Affairs, antigenic drift, hospitalization, emergency department, observational study, marginal structural models, 2025–2026 season, public health