Utilization and costs of home care for patients with colorectal cancer: a population-based study
Bibliographic record
Abstract
BACKGROUND: The utilization and costs of home care services provided for people with colorectal cancer is not well-known. We conducted an analysis to determine the utilization and costs of such services associated with each stage of colorectal cancer among patients in the province of Ontario. METHODS: We included cases of colorectal cancer diagnosed in Ontario between Jan. 1, 2005, and Dec. 31, 2009. Data were extracted from the Ontario Cancer Registry and linked to data from a home care administrative database. The types of services used were stratified by stage of disease and by phase of care (initial phase = 180 d after diagnosis, terminal phase = 180 d before death, continuing phase = interval between initial and terminal phases). Overall utilization rates and costs were determined, and regression analysis was used to examine associated factors. RESULTS: A total of 36 195 patients had colorectal cancer diagnosed during the study period; the median age was 71 (interquartile range 61-79) years. Home care services were provided to 24 641 patients (68.1%). The number of services per patient-year was 27.5, at a cost of $2180 per patient-year. The number of services provided per patient-year increased with increasing disease severity at diagnosis (15.5 at stage I, 25.5 at stage II, 32.5 at stage III and 62.5 at stage IV; 22.6 for unstaged disease). The cost of services per patient-year also increased with disease severity at diagnosis ($1170 at stage I, $1995 at stage II, $2727 at stage III and $5541 at stage IV). Publicly funded home care services and associated costs decreased with increasing income group, but they increased among patients who had a history of high health resource utilization. The mean 30-day cost of home care services decreased from the initial phase of care ($323) to the continuing phase ($160) but increased during the terminal phase ($616). INTERPRETATION: More than two-thirds of the patients with colorectal cancer in this study used home care services. Those who received home care services used about 2 services per month in a one-year period, at a cost of about $2000 per year. This information can aid policy-makers in future decisions regarding resource allocations.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".