Assessment of Radiology Physicians by a Regulatory Authority
Bibliographic record
Abstract
PURPOSE: To determine whether it is possible to develop a feasible, valid, and reliable multisource feedback program for radiologists. MATERIALS AND METHODS: Surveys with 38, 29, and 20 items were developed to assess individual radiologists by eight radiologic colleagues (peers), eight referring physicians, and eight co-workers (eg, technicians), respectively, by using five-point scales along with an "unable to assess" category. Radiologists completed a self-assessment on the basis of the peer questionnaire. Items addressed key competencies related to clinical competence, collegiality, professionalism, workplace behavior, and self-management. The study was approved by the University of Calgary Conjoint Health Ethics Research Board. RESULTS: Data from 190 radiologists were available. The mean numbers of respondents per physician were 7.5 of eight (1259 of 1520, 83%), 7.15 of eight (1337 of 1520, 88%), and 7.5 of eight (1420 of 1520, 93%) for peers, referring physicians, and co-workers, respectively. The internal consistency reliability indicated all instruments had a Cronbach alpha of more than 0.95. The generalizability coefficient analysis indicated that the peer, referring physicians, and co-worker instruments achieved a generalizability coefficient of 0.88, 0.79, and 0.87, respectively. The factor analysis indicated that four factors on the colleague questionnaire accounted for 70% of the total variance: clinical competence, collegiality, professional development, and workplace behavior. For the referring physician survey, three factors accounted for 64.1% of the variance: professional development, professional consultation, and professional responsibility. Two factors on the co-worker questionnaire accounted for 63.2% of the total variance: professional responsibility and patient interaction. CONCLUSION: The psychometric examination of the data suggests that the instruments developed to assess radiologists are a feasible way to assess radiology practice and provide evidence for validity and reliability.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".