The Effect of Patient Feedback on Physiciansʼ Consultation Skills: A Systematic Review
Bibliographic record
Abstract
PURPOSE: The effect of patient feedback interventions as a method of improving physicians' consultation (i.e., communication, interpersonal) skills is equivocal; research is scarce, and methods and rigor vary. The authors conducted this systematic review to analyze the educational effect of feedback from real patients on physicians' consultation skills at the four Kirkpatrick levels. METHOD: The authors searched five databases (PubMed, EMBASE, Cochrane, PsycInfo, ERIC; April 2010). They included empirical studies of all designs (randomized controlled, quasi-experimental, cross-sectional, and qualitative) if the studies concerned physicians in general health care who received formal feedback regarding their consultation skills from real patients. The authors have briefly described aspects of the included studies, analyzed their quality, and examined their results by Kirkpatrick educational effect level. RESULTS: The authors identified 15 studies (10 studies in primary care; 5 in other specialties) in which physicians received feedback in various ways (e.g., aggregated patient reports or educator-mediated coaching sessions), conducted in the United States, the Netherlands, the United Kingdom, Australia, and Canada. All studies that assessed level 1 (valuation), level 2 (learning), and level 3 (intended behavior) demonstrated positive results; however, only four of the seven studies that assessed level 4 (change in actual performance or results) found a beneficial effect. CONCLUSIONS: Some evidence for the effectiveness of using feedback from real patients to improve knowledge and behavior exists; however, before implementing patient feedback into training programs, educators and policy makers should realize that the evidence for effecting actual improvement in physicians' consulting skills is rather limited.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".