The commentary responds directly to an investigation by Kabbash, Fieber, Shaw, Cochran, Sarosi, and Falcone, who asked a question that sounds almost too obvious to need answering: does more mean better? Their study, published in the same journal, evaluated faculty-to-resident feedback in general surgery by measuring not just how often attending surgeons provided workplace-based assessments, but what those assessments actually contained. The concern underlying the work is familiar to anyone who has sat on a clinical competency committee. Volume of assessment data is easy to count. Quality is not. A resident may accumulate dozens of brief encounter ratings over the course of a rotation, and still graduate with no coherent picture of whether independent performance has been demonstrated in the operating room, on the wards, or in the emergency department.

The American Board of Surgery has embraced EPAs for general surgery precisely to close that gap. Rather than treating every task as a separate competency checkbox, EPAs bundle the discrete skills, knowledge domains, and attitudes required for units of professional work that can be entrusted to a learner. The board’s framework identifies the core activities a general surgeon must be able to perform unsupervised by the end of training, from managing critically ill patients to performing defining operations of the specialty. When an assessor marks a resident as entrusted for one of these activities, the judgment is meant to carry real weight: it is a statement about readiness for unsupervised practice, the same readiness that certification ultimately vouches for.

That weight is exactly why Lipman insists on extensiveness as a first condition. A sparse set of EPA ratings, gathered on only a handful of occasions or from only a subset of a resident’s supervisors, cannot capture the variability inherent in surgical work. Performance fluctuates with case complexity, patient acuity, team dynamics, and the sheer human reality of fatigue and stress. A resident entrusted after three observations on straightforward elective cases may not be equivalent to one entrusted after thirty observations spanning emergencies, revisions, and high-acuity trauma. Extensiveness, in this framing, is not bureaucratic accumulation for its own sake. It is the statistical and practical foundation that allows committees to distinguish a resident having a good week from a resident who is genuinely, reliably ready.

The second condition, that EPAs be practiced, addresses the often-ignored reality that assessment is itself a clinical skill. Faculty surgeons are experts in operating and in patient care, but the act of observing a trainee, anchoring that observation to the specific behavioral anchors of an EPA scale, and translating it into a calibrated trust judgment is a separate craft that requires deliberate rehearsal. Assessment researchers have long documented the hazards of uncalibrated raters: leniency bias, central tendency, halo effects that let a charming resident’s minor lapses slide, and harshness toward trainees whose style differs from the rater’s own. Without regular practice, rater drift is inevitable. Two attendings asked whether the same resident can be entrusted with the same activity should, in principle, reach the same conclusion. In unpracticed systems, they frequently do not.

The commentary highlights a scoring approach developed to address exactly this quality problem. The Quality of Assessment of Learning, or Qual, score, introduced by Chan, Sebok-Syer, Sampson, and Monteiro in Teaching and Learning in Medicine, provides validity evidence for a system that rates short, workplace-based comments on trainee performance. Instead of accepting any narrative feedback as equal evidence, the Qual framework distinguishes comments that contain specific, actionable, behaviorally anchored observations from vague platitudes like good job or needs to read more. Applied to EPA-linked assessments, such scoring gives programs a way to audit not just how many assessments their faculty complete, but how informative each one actually is. It converts the sprawling noise of workplace commentary into something a competency committee can weigh.

The Kabbash study’s central finding, that higher volumes of faculty feedback did not automatically translate into higher-quality feedback, reframes a comfortable assumption in surgical education. Programs have often responded to accreditation pressure by simply demanding more assessments, building dashboards that turn red when completion rates sag, and nudging faculty to submit ratings before their logs expire. But if the additional assessments are generic, unanchored, or copied between residents, the dashboard turns green while the underlying evidence base for trust decisions remains thin. Lipman’s commentary makes the corollary explicit: extensive but inaccurate assessment may be worse than limited assessment, because it manufactures false confidence in an entrustment decision that the data cannot actually support.

Accuracy, the third pillar, is where the technical demands on programs become most serious. For EPA judgments to be accurate, they must be grounded in direct observation of the specific activity in question, made by raters who have seen enough of the resident’s work to generalize, and recorded with enough specificity that a future reader can reconstruct the basis for the decision. This has operational consequences. Assessment must be embedded into the workflow rather than bolted on afterward, ideally captured immediately after a case or shift while observations are fresh. Faculty development must treat entrustment rating as a teachable, coachable skill, with calibration exercises in which multiple raters score the same performance and reconcile their differences. Programs must also resist the seduction of automation that merely counts forms, and instead build review processes that sample and score the narrative content of assessments using validated instruments.

For residents, the stakes of getting this right are personal and immediate. Trainees respond to the feedback culture they inhabit. When they perceive that ratings are arbitrary, they learn to game the system, requesting assessments at convenient moments and from lenient raters. When they perceive that ratings are extensive, practiced, and accurate, feedback becomes a form of coaching rather than surveillance, and the EPA framework starts to do what it was designed to do: tell a resident, in concrete behavioral terms, what they can already be trusted to do alone and what they must still work on under supervision. The commentary’s synthesis suggests that programs which invest in all three pillars will not only produce better data but will change the day-to-day conversation between teachers and learners.

As competency-based medical education continues its march through surgical training, the lessons of this exchange between the Kabbash study and Lipman’s commentary extend well beyond general surgery. Every specialty adopting EPAs faces the same temptation to measure volume instead of value. The evidence now accumulating points toward a more demanding but more defensible standard: build an assessment system that is comprehensive enough to be representative, rehearsed enough to be reliable, and specific enough to be true. Only then can a statement of entrustment mean what it claims, and only then can the programs that certify surgeons honestly say that readiness for independent practice was demonstrated, not assumed.

Subject of Research: Quality and validity of faculty feedback in entrustable professional activity-based assessment of surgical residents

Article Title: The best EPAs are extensive, practiced and accurate

Article References: The best EPAs are extensive, practiced and accurate. (n.d.). https://doi.org/10.1007/s44186-026-00577-5

Image Credits: AI Generated

DOI: 10.1007/s44186-026-00577-5

Keywords: entrustable professional activities, surgical education, general surgery residency, workplace-based assessment, faculty feedback, competency-based medical education, Qual score, rater calibration, resident training, American Board of Surgery, feedback quality, surgical competency committees

EPAs are defined professional tasks that a trainee may eventually be trusted to perform with decreasing supervision. In general surgery, they provide a structured way to document observations made during real patient care rather than relying exclusively on examinations or end-of-rotation impressions. The American Board of Surgery introduced EPAs in 2023, and the commentary describes their arrival as a major shift in workplace assessment. By prompting more evaluations during clinical encounters, the system has generated substantially more data about residents’ performance. That increase responds to a longstanding weakness in surgical education: faculty members often observe trainees frequently but record feedback inconsistently, leaving learners with limited information about their development.

More frequent assessments can improve visibility, but the educational value of each assessment depends heavily on its narrative content. Summative evaluations completed asynchronously, including end-of-rotation reports and competency committee reviews, may arrive too late to guide performance in the moment. They can also be broad, using general language that describes a resident as capable or progressing without identifying the particular behavior that produced that judgment. EPA forms offer more opportunities to capture comments close to the clinical event, but the commentary emphasizes that free-text feedback remains highly variable. A short statement of appreciation may be encouraging, yet it does not necessarily tell a trainee how to handle tissue, anticipate the next operative step, organize a case or respond to an unexpected finding.

The discussion draws on work by Moore and colleagues examining narrative feedback in general surgery through an established classification framework. That analysis found differences in the kind of feedback residents received according to practice readiness, case complexity and trainee and evaluator gender. Residents considered ready for practice and those involved in more complex cases were less likely to receive coaching or formative comments. Male-identifying residents received less evaluative feedback, while male faculty were less likely to provide narrative comments classified as specific or coaching. These findings do not establish why the differences occurred, but they show that assessment language is shaped by the context and people involved. Counting completed forms alone can therefore conceal meaningful variation in what residents are actually being told.

High-quality feedback is often described as forward-looking because it connects observation with a realistic next step. A useful comment might identify a concrete action, explain the clinical reasoning behind it and indicate how the learner can demonstrate improvement. It should be tailored to the task and the individual, constructive rather than merely punitive, and feasible within the pressures of clinical work. Reviews of formative feedback have also recommended validated approaches such as the Quality of Assessment of Learning system and guided workplace-based assessment tools. Such frameworks can help educators move beyond praise or criticism toward comments that support growth and inform future entrustment decisions. The goal is not to make every evaluation lengthy, but to make each one sufficiently precise to be acted upon.

Improving the comments will require faculty development, but the commentary cautions against treating all educators as though they need the same intervention. Some faculty may complete few narrative assessments and first need support understanding the purpose and mechanics of EPA documentation. Others may routinely write comments but rely mostly on evaluative language, such as whether a resident met expectations, without adding coaching that explains how to advance. A precision-based approach would use an educator’s feedback profile to identify the specific skill requiring attention. That could include the proportion of assessments containing narrative text, the frequency of coaching language or the specificity of recommendations. Such individualized development is practical in principle, although leaders still face familiar barriers involving faculty time, participation and the scale of implementation.

The same EPA records that describe residents could also reveal how faculty teach. Because evaluators generate portfolios of comments over time, institutions could analyze patterns across individuals, divisions or departments. These profiles might help identify educators who need assistance and provide leaders with evidence about engagement in assessment. Artificial intelligence and large language models could make this review more manageable by synthesizing hundreds of comments into longitudinal summaries. For a resident, such a summary might reveal repeated strengths in tissue handling alongside recurring suggestions to improve operative anticipation or case progression. For a program director, it could highlight performance trends earlier and support a more individualized learning plan. The proposed use is analytical and supportive: technology would organize information that is difficult for humans to review at scale, rather than replace clinical judgment.

AI could also intervene closer to the moment when feedback is written. A language model might flag a comment that lacks a specific observation or prompt an educator to add an actionable coaching recommendation while preserving the original intent. Related work has explored whether AI can help faculty convert fixed-mindset wording into growth-mindset language, and emerging research is examining whether naturally occurring intraoperative teaching conversations can be analyzed and summarized. Such tools could capture educational guidance that currently disappears after an operation, when both teacher and learner are working under intense cognitive demands. But the potential benefits come with substantial limits. Algorithms can reproduce bias, generate inaccurate or fabricated interpretations and create an appearance of objectivity that their human-designed rules do not warrant. Any system would need oversight, privacy protections and careful validation against expert judgment.

The central test for EPAs is therefore not how many assessments a program collects, but whether the resulting feedback helps residents become better surgeons. More observations can provide a stronger foundation for detecting patterns, but quantity without specificity may simply increase documentation burden for educators and review burden for trainees. Surgical education leaders will need to pair structured assessments with clear expectations for narrative quality, targeted faculty development and systems that make useful feedback easier to produce and interpret. AI may eventually reduce some of the administrative work, but it cannot substitute for meaningful observation or the relationship between a resident and an educator. The promise of EPAs will be realized only when the growing volume of assessment data is matched by comments that are timely, equitable, technically grounded and actionable in the operating room.

One implication of this discussion is that feedback quality should be treated as a property of the assessment system, not merely as an individual writing skill. An EPA can record a supervision decision and still provide little explanation of the behaviors that led to it. Conversely, a brief comment may be educationally valuable if it identifies a precise observation and connects it to a feasible next action. This distinction is important for program review because completion rates and entrustment ratings describe whether documentation occurred, whereas narrative analysis asks whether the documentation can support learning.

Classification frameworks offer a way to make that second question more visible. By distinguishing evaluative language from coaching, and general statements from specific comments, educators can examine patterns that would otherwise remain hidden in a large assessment database. Such categories should not be mistaken for a complete measure of educational value: a comment’s usefulness also depends on clinical context, timing, the learner’s prior experience and whether the suggested action is realistic. Still, a shared vocabulary can help faculty discuss feedback more consistently and make development goals more concrete.

The reported differences by case complexity and practice readiness also suggest that feedback systems should not assume that the most advanced or challenging encounters automatically generate the richest coaching. Faculty may interpret a near-independent resident’s performance as requiring less explanation, even when complex cases contain important opportunities to discuss judgment, anticipation and prioritization. Similarly, an assessment indicating readiness for practice does not eliminate the need for developmental guidance. Ongoing coaching can clarify how a resident should extend performance, manage variation and prepare for responsibilities that exceed the specific encounter being evaluated.

Attention to evaluator and trainee characteristics adds an equity dimension to EPA design. If narrative specificity or evaluative language varies across groups, the resulting record may provide some residents with clearer developmental information than others. The source evidence identifies differences but does not establish their causes, so corrective efforts should avoid assuming that bias is the only explanation. Programs could instead use patterns as prompts for review, examine assessment contexts and ensure that faculty receive guidance on observing and documenting performance in behavior-based terms. Monitoring should support improvement rather than turn isolated comments into judgments about individual educators.

For artificial intelligence to assist responsibly, its role would need to be defined around transparency and human review. A system might identify that a comment contains praise without an observable behavior or a recommendation without a clear next step, but that signal would be a prompt for the faculty member, not a final rating. Any generated summary should remain traceable to the underlying comments so residents and program directors can check whether recurring themes are genuine. The caution is especially important when language models analyze intraoperative conversations, where context, speakers and intended meaning may be difficult to determine.

Evaluation of an AI-supported feedback process should therefore include more than efficiency. Educational leaders would need to ask whether comments become more specific and actionable, whether faculty preserve clinical nuance, and whether summaries accurately represent the record across different learners and evaluators. The source commentary frames these tools as augmentation because observation, judgment and the educator–learner relationship remain central. A successful implementation would reduce avoidable documentation and synthesis work while preserving accountability for the feedback that ultimately informs resident development and decisions about entrustment.

Subject of Research: Quality of narrative feedback in surgical education

Article Title: EPAs gave us feedback quantity, but what about quality?

Article References: Jou, K., & Holmstrom, A. L. (2026). EPAs gave us feedback quantity, but what about quality?. Global Surgical Education – Journal of the Association for Surgical Education, 5(1), Article 172. https://doi.org/10.1007/s44186-026-00576-6

Image Credits: AI Generated

DOI: 10.1007/s44186-026-00576-6

Keywords: surgical education, feedback, Entrustable Professional Activities, workplace assessment, resident training, faculty development, competency-based education, artificial intelligence, EPAs, gave, quantity, quality