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 scale of the problem the study addresses is hard to overstate. Documentation in the electronic health record is frequently cited as a primary driver of physician burnout, a phenomenon that has worsened across the American medical workforce in recent years. National surveys have tracked rising burnout and declining satisfaction with work-life integration among physicians compared with the general working population, and health services researchers have estimated the enormous expenditures attributable to burnout-related turnover in primary care. Burnout is not merely a matter of professional misery; systematic reviews have linked it to degraded quality and safety of care, and studies of electronic health record use have connected heavy documentation loads to clinician stress, reduced productivity, and even physician turnover.

Residents occupy a particularly exposed position in this landscape. These are physicians in post-graduate training, typically in their second or third year of residency when working in continuity clinics, and they must learn to navigate the electronic health record while simultaneously learning medicine itself. Prior research has shown that physicians receive little formal training in efficient record use, that there is enormous variability in how individual clinicians document, and that this variation carries potential consequences for patient harm. Earlier studies have also documented the phenomenon known as note bloat—the progressive swelling of clinical notes with copied text, redundant information, and boilerplate that obscures the signal a busy clinician actually needs.

The Mount Sinai team designed their study to test whether standardization could attack these problems directly. They compared fifty-two second-year and fifty-five third-year internal medicine residents who practiced under the new standardized system with historical control groups of fifty-five second-year and forty-nine third-year residents who had worked in the same urban academic clinic before the change. The intervention itself had three components: standardized documentation templates, standardized medication ordering practices, and mandatory training on how to use them, supplemented by incentivized opportunities for residents to practice the new documentation methods. The design was a pre-post difference-in-differences evaluation, a quasi-experimental approach that compares changes over time in the intervention group against changes in the control group, helping to separate the effect of the intervention from broader trends in documentation behavior.

What makes the study technically interesting is that the researchers did not rely on self-reported time savings, which are notoriously unreliable. Instead, they mined objective electronic health record efficiency metrics, measuring the time residents spent per appointment on chart review, note writing, and placing orders. They also measured the length of notes in characters and, critically, tracked the number of characters of text copied from prior notes and pasted into current notes—a direct window into how much of each note was genuinely new clinical thinking versus recycled text. These granular behavioral metrics, increasingly available through vendor analytics platforms, allow researchers to dissect exactly where documentation time goes and how interventions change clinician behavior at the keystroke level.

The results were striking. The intervention was associated with an 18.8-minute decrease in per-encounter documentation time for residents during their second post-graduate year and a 12.0-minute decrease during their third year, both statistically significant at p less than 0.0001. To put that in perspective, a resident seeing a full panel of patients in an afternoon clinic could recover well over an hour of previously lost time each session. Note length collapsed as well: second-year residents produced notes shorter by 3,650 characters, a 43.3 percent reduction, while third-year residents trimmed 1,608 characters, or 17.7 percent. Perhaps most telling was the fate of copy-paste text, the hallmark of note bloat, which fell by 66.7 percent among second-year residents and 74.6 percent among third-year residents.

The pattern across training years is itself informative. Second-year residents, who were encountering the standardized system as relatively fresh users of the outpatient record, showed larger absolute and relative improvements than third-year residents, who had already spent a year forming documentation habits under the old system. This is consistent with what learning scientists have long described about skill acquisition: early habits are more malleable, and interventions that shape practice from the start of a training stage may have an easier time than those asking experienced users to unlearn entrenched workflows. It suggests that residency programs considering similar reforms may get the biggest returns by introducing standardization at the moment residents first begin outpatient continuity work.

The well-being findings, however, are a cautionary coda. The researchers administered the Mini-Z survey, a validated instrument for assessing worklife and burnout in medical settings, before and after the intervention. Among the forty-two residents who completed the pre-intervention survey and the twenty-eight who completed the post-intervention survey, there were no significant changes in overall Mini-Z scores. There was one encouraging signal: a single-item burnout question improved from 3.2 before the intervention to 3.7 afterward, a statistically significant shift on a scale where the direction of improvement reflects lower burnout. But the authors are candid about the limitation—response rates to the well-being questions were low, and the analysis was underpowered to detect anything but large effects. Efficiency, in other words, demonstrably improved; whether that efficiency translated into residents feeling better about their work remains an open question.

This ambiguity matters because the relationship between documentation time and burnout is not a simple one-to-one pipeline. Prior studies have found associations between electronic health record design and use factors and clinician stress, and between after-hours record time and turnover intentions, but burnout is a multidimensional phenomenon shaped by workload, autonomy, meaning in work, and organizational culture. Freeing up nineteen minutes per visit may reduce one specific stressor without moving global well-being scores, especially over the relatively short window of a pre-post study. It is also possible that the residents who felt most burdened were the least likely to complete the follow-up survey, biasing the results in either direction. The study was deemed quality improvement by the Mount Sinai Department of Medicine Quality Improvement Committee and exempted from informed consent, reflecting its operational rather than experimental framing.

The findings arrive at a moment when the field is wrestling with how to reduce documentation burden at scale. Ambient artificial intelligence scribes, which listen to clinical encounters and draft notes automatically, have shown promising effects on documentation time in recent studies across primary care and emergency settings, and systematic reviews of artificial intelligence tools for clinical documentation are accumulating rapidly. But such technologies are expensive, raise new questions about accuracy and oversight, and remain unevenly deployed. The Mount Sinai study is a useful counterweight: a structured, low-cost intervention of templates, ordering standards, and training—implemented within an existing commercial record system—produced large, objectively measured efficiency gains without waiting for artificial intelligence to mature. For residency programs and clinics confronting documentation overload today, the message is that a meaningful share of the burden is not inherent to the software but to how it is used, and that how it is used can be taught, standardized, and measured.

Subject of Research: Effect of standardized outpatient electronic health record documentation on internal medicine resident efficiency and well-being

Article Title: The Impact of Outpatient Documentation Standardization on Internal Medicine Resident Efficiency and Well-Being

Article References: Kutscher, E., Halket, D., Feinberg, A., Blum, C., Koransky, A., Tamler, R., Federman, A., & Fishman, M. (2026). The Impact of Outpatient Documentation Standardization on Internal Medicine Resident Efficiency and Well-Being. Journal of General Internal Medicine. https://doi.org/10.1007/s11606-026-10858-w

Image Credits: AI Generated

DOI: 10.1007/s11606-026-10858-w

Keywords: electronic health records, documentation burden, physician burnout, internal medicine residency, note templates, clinical efficiency, copy-paste text, Mini-Z survey, graduate medical education, difference-in-differences, ambulatory care, well-being