BREAST CANCER: BETTER CARE FOR LESS COST
Bibliographic record
Abstract
OBJECTIVES: To estimate the potential for cost reduction in the acute care setting and the required investment in the home care setting of implementing an outpatient/early discharge strategy for operable (stages I and II) breast cancer in Canada. METHODS: Data from a community hospital were augmented by expert knowledge and incorporated into the breast cancer submodel of Statistics Canada's Population Health Model. For the estimated 90% of patients for whom this approach was assumed to be appropriate, the resource utilization for outpatient breast-conserving surgery and 2 days of hospitalization for those women undergoing mastectomy was quantified and costed, as were the appropriate home care services. A 5% readmission rate for complications was assumed. Cost per case, total cost burden, investment in home care, savings in acute care, and net savings were calculated. Sensitivity analyses were performed around readmission rates and home care/surgical follow-up costs. All costs were determined in 1995 Canadian dollars. RESULTS: The cost of initial treatment for the 15,399 women diagnosed with stages I and II breast cancer in 1995 in Canada was estimated to be $127.6 million. Hospitalization made up 53% of these costs. Under the outpatient/early discharge strategy, the acute care cost of initial breast cancer management could be reduced by $47.2 million, with an investment in home care of $14.5 million ($453 per patient), resulting in an overall net saving of $33 million. Under this strategy, hospitalization would contribute only 21% to the total care cost. CONCLUSIONS: If Canadian surgeons and healthcare administrators were to work together to put in place processes to support ambulatory breast cancer surgery and if resources were redirected to the provision of home-based post-operative care, there would be potential for a large net healthcare saving and preservation of high-quality patient care.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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 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".