Physician perspectives on delays in cancer diagnosis in Alberta: a qualitative study
Bibliographic record
Abstract
BACKGROUND: Delays in cancer diagnosis have been associated with reduced survival, decreased quality of life after treatment, and suboptimal patient experience. The objective of the study was to explore the perspectives of a group of family physicians and other specialists regarding potentially avoidable delays in diagnosing cancer, and approaches that may help expedite the process. METHODS: We conducted a qualitative study using interviews with physicians practising in primary and outpatient care settings in Alberta between July and September 2019. We recruited family physicians and specialists who were in a position to discuss delays in cancer diagnosis by email via the Cancer Strategic Clinical Network and the Alberta Medical Association. We conducted semistructured interviews over the phone, and analyzed data using thematic analysis. RESULTS: Eleven family physicians and 22 other specialists (including 7 surgeons or surgical oncologists, 3 pathologists, 3 radiologists, 2 emergency physicians and 2 hematologists) participated in interviews; 22 were male (66.7%). We identified 4 main themes describing 9 factors contributing to potentially avoidable delays in diagnosis, namely the nature of primary care, initial presentation, investigation, and specialist advice and referral. We also identified 1 theme describing 3 suggestions for improvement, including system integration, standardized care pathways and a centralized advice, triage and referral support service for family physicians. INTERPRETATION: These findings suggest the need for enhanced support for family physicians, and better integration of primary and specialty care before cancer diagnosis. A multifaceted and coordinated approach to streamlining cancer diagnosis is required, with the goals of enhancing patient outcomes, reducing physician frustration and optimizing efficiency.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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; 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".