Population-Based Home Care Services in Breast Cancer: Utilization and Costs
Bibliographic record
Abstract
OBJECTIVE: To determine utilization and costs of home care services (hcs) for individuals with a diagnosis of breast cancer (bc). METHODS: Incident cases of invasive bc in women were extracted from the Ontario Cancer Registry (2005-2009) and linked with other Ontario health care administrative databases. Control patients were selected from the population of women never diagnosed with any type of cancer. The types and proportions of hcs used were determined and stratified by disease stage. Attributable home care utilization and costs for bc patients were determined. Factors associated with hcs costs were assessed using regression analysis. RESULTS: Among the 39,656 bc and 198,280 control patients identified (median age: 61.6 years for both), 75.4% of bc patients used hcs (62.1% stage i; 85.7% stage ii; 94.6% stage iii; 79.1% stage iv) compared with 14.6% of control patients. The number of hcs used per patient-year were significantly higher for the bc patients than for the control patients (14.97 vs. 6.13, p < 0.01), resulting in higher costs per patient-year ($1,210 vs. $325; $885 attributable cost to bc, p < 0.01). The number of hcs utilized and the associated costs increased as the bc stage increased. In contrast, hcs costs decreased as income increased and as previous health care exposure decreased. INTERPRETATION: Patients with bc used twice as many hcs, resulting in costs that were almost 4 times those observed in a matched control group. Less than an additional $1000 per bc patient per year were spent on hcs utilization in the study population.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".