Examining the role of the physician as a source of variation: Are physician‐related variations necessarily unwarranted?
Bibliographic record
Abstract
RATIONALE, AIMS, AND OBJECTIVES: The physician is often implicated as an important cause of observed variations in health care service use. However, it is not clear if physician-related variation is problematic for patient care. This paper illustrates that observed physician-related variation is not necessarily unwarranted. METHODS: This is a narrative review. RESULTS: Many studies have attributed observed variations to the physician, but little attention is given towards discriminating between those variations that exist for good reasons and those that are unwarranted. Two arguments can be made for why physician-related variation is unwarranted. The first posits that physician-related factors should not play a role in management of care decisions because such decisions should be driven by science (which is imagined to be definitive). The second considers the possibility of supplier-induced demand as a factor driving observed variations. We show that neither argument is sufficient to rule out that physician-related variations may be warranted. Furthermore, the claim that such variations are necessarily problematic for patients has yet to be substantiated empirically. CONCLUSIONS: It is not enough to simply show that physician-related variation can exist-one must also show where it is unwarranted and what is the magnitude of unwarranted variations. Failure to show this can have significant implications on how we interpret and respond to observed variations. Improved measurement of the sources of variation, especially with respect to patient preferences and context, may help us start to disentangle physician-related variation that is desirable from that which is unwarranted.
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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 | 0.111 | 0.359 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".