A look at the thoracic surgery workforce in Canada: how demographics and scope of practice may impact future workforce needs
Bibliographic record
Abstract
BACKGROUND: The purpose of this study is to describe the demographics, training and practice characteristics of physicians performing thoracic surgery across Canada to better assess workforce needs. METHODS: We developed a questionnaire using a modified Delphi process to generate questionnaire items. The questionnaire was administered to all Canadian thoracic surgeons via email (n = 102) or mail (n = 35). RESULTS: In all, 97 surgeons completed the survey (71% response rate). The mean age of respondents was 47.7 (standard deviation 9.1) years; 10.3% were older than 60. Ninety respondents (88.7%) were men, 95 (81.1%) practised in English and 93 (76%) were born in Canada. Most (90.4%) had a medical school affiliation, with an equal proportion practising in community or university teaching hospitals. Only 18% of respondents reported working fewer than 60 hours per week, and 34% were on call more than 1 in 3. Three-quarters of work hours were devoted to clinical care, with the remaining time split among research, administration and teaching. Malignant lung disease accounted for 61.2% of practice time, with the remaining time equally split between benign and malignant thoracic diseases. Preoperative testing (49.4%) and insufficient operating time (49.5%) were the most common factors delaying delivery of care. More than 80% of respondents reported being satisfied with their careers, with 62.1% planning on retiring after age 60. CONCLUSION: This survey characterizes Canadian thoracic surgeons by providing specific demographic, satisfaction and scope of practice information. Despite challenges in obtaining adequate resources for providing timely care, job satisfaction remains high, with a balanced workforce supply and demand anticipated for the foreseeable future.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".