Differences in the management of Crohn’s disease among experts and community providers, based on a national survey of sample case vignettes
Bibliographic record
Abstract
BACKGROUND: When faced with the same set of facts, healthcare providers often make different diagnoses, employ different tests and prescribe disparate therapies. AIM: To perform a national survey to measure process of care and variations in decision-making in Crohn's disease, and the compared results between experts and community providers. METHODS: We constructed a survey with five vignettes to elicit provider beliefs regarding the appropriateness of diagnostic tests and therapies in Crohn's disease. We measured agreement between community gastroenterologists and Crohn's disease experts, and measured variation within each group using the RAND Disagreement Index (DI), which is a validated measure of provider variation. RESULTS: We received 186 responses (42% response rate). Experts and community providers generally agreed on diagnostic testing decisions in Crohn's disease. However, there was a significant disagreement between groups for several decisions (use of 5-aminosalicylate in particular), and there was evidence of 'extreme variation' (defined as DI > 1.0) within groups across a range of decisions. CONCLUSIONS: Although experts and community providers are in general consensus about diagnostic decision-making in Crohn's disease, extreme variation exists both between and within groups for key therapeutic decisions in Crohn's disease. We must understand and decrease this variation prior to future efforts of creating explicit quality indicators in Crohn's disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".