Physician perspectives on Choosing Wisely Canada as an approach to reduce unnecessary medical care: a qualitative study
Bibliographic record
Abstract
BACKGROUND: Reducing monies spent on unnecessary medical care is one possible target to improve value in healthcare systems. Regional variation in the provision of medical care suggests physician behaviour and patient demands influence the provision of unnecessary medical care. Recently, Choosing Wisely campaigns began using 'top 5 do-not-do' lists to target unnecessary medical care by encouraging greater physician and patient dialogue at the point of care. The present study aims to examine the rationale for Choosing Wisely Canada's (CWC) design and to analyse physician perceptions regarding the features of CWC aimed to reduce unnecessary medical care. METHODS: The study involved semi-structured interviews with 19 key informant physicians with CWC experience and the application of procedures of grounded theory to analyse interview transcripts and develop explanations addressing the objectives. RESULTS: Participants reported that the CWC was the medical community's response to three pressures, namely (1) demand for unnecessary medical care from patients during the clinical encounter; (2) public perception that physicians do not always prioritise patients' needs; and (3) 'blunt' government tools aimed to reduce costs rather than improving patient care. Respondents stated that involving the patient in decision-making would help alleviate these pressures by promoting the clinical encounter as the paramount decision-point in achieving necessary care. However, CWC does not address several of the key reasons, from a physician perspective, for providing unnecessary medical care, including time pressures in the clinical encounter, uncertainty about the optimal care pathway and fear of litigation. CONCLUSION: This study contributes to our understanding of the perceptions of physicians regarding the CWC campaign. Specifically, physicians believe that CWC does little to address the clinical reasons for unnecessary medical care. Ultimately, because CWC has limited impact on physician behaviour or patient expectations, it is unlikely to have a major influence on unnecessary medical care.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: yes · About a Canadian topic: yes | Qualitative | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Qualitative | high |
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 | 0.038 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".