Is There a Consensus when Physicians Evaluate the Relevance of Retrieved Systematic Reviews?
Bibliographic record
Abstract
BACKGROUND: A significant challenge associated with practicing evidence-based medicine is to provide physicians with relevant clinical information when it is needed. At the same time it appears that the notion of relevance is subjective and its perception is affected by a number of contextual factors. OBJECTIVES: To assess to what extent physicians agree on the relevance of evidence in the form of systematic reviews for a common set of patient cases, and to identify possible contextual factors that influence their perception of relevance. METHODS: A web-based survey was used where pediatric emergency physicians from multiple academic centers across Canada were asked to evaluate the relevance of systematic reviews retrieved automatically for 14 written case vignettes (paper patients). The vignettes were derived from prospective data describing pediatric patients with asthma exacerbations presenting at the emergency department. To limit the cognitive burden on respondents, the number of reviews associated with each vignette was limited to three. RESULTS: Twenty-two academic emergency physicians with varying years of clinical practice completed the survey. There was no consensus in their evaluation of relevance of the retrieved reviews and physicians' assessments ranged from very relevant to irrelevant evidence, with the majority of evaluations being somewhere in the middle. This indicates that the study participants did not share a notion of relevance uniformly. Further analysis of commentaries provided by the physicians allowed identifying three possible contextual factors: expected specificity of evidence (acute vs chronic condition), the terminology used in the systematic reviews, and the micro environment of clinical setting. CONCLUSIONS: There is no consensus among physicians with regards to what constitutes relevant clinical evidence for a given patient case. Subsequently, this finding suggests that evidence retrieval systems should allow for deep customization with regards to physician's preferences and contextual factors, including differences in the micro environment of each clinical setting.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.033 | 0.048 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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; both teacher heads agree on what is shown here.
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".