Qualitative study of cardiologists’ perceptions of factors influencing clinical practice decisions
Bibliographic record
Abstract
BACKGROUND: Healthcare costs are increasing in the USA and Canada and a substantial portion of health spending is devoted to services that do not improve health outcomes. Efforts to reduce waste by adopting evidence-based clinical practice guideline recommendations have had limited success. We sought insight into improving health system efficiency through understanding cardiologists' perceptions of factors that influence clinical decision-making. METHODS: In this descriptive qualitative study, we conducted in-depth interviews with 18 American and 3 Canadian cardiologists. We used conventional content analysis including inductive and deductive approaches for data analysis and mapped findings to the ecological systems framework. RESULTS: Physicians reported that major determinants of practice included interpersonal interactions with peers, patients and administrators; financial incentives and system factors. Patients' insurance status represented an important consideration for some cardiologists. Other major influences included time constraints, fear of litigation (less prominent in Canada), a sense that their obligation was never to miss any underlying pathology, and patient demands. The need to bring income into their health system influenced American cardiologists' practice; personal income implications influenced Canadian cardiologists' practice. Cardiologists reported that knowledge limitations and logistical challenges limit their ability to assist patients with cost considerations. All these considerations were more influential than guidelines; some cardiologists expressed a high level of scepticism regarding guidelines. CONCLUSIONS: Clinical decision-making by cardiologists is shaped by individual, interpersonal, organisational, environmental, financial and sociopolitical influences and only to a limited extent by guideline recommendations. Successful strategies to achieve efficient, evidence-based care will require addressing socioecological influences on decision-making.
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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 | 0.015 | 0.042 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".