Use of patient-reported outcomes in regional cancer centres over time: a retrospective study
Bibliographic record
Abstract
BACKGROUND: Since 2007, Cancer Care Ontario has been collecting data using the Edmonton Symptom Assessment System as a patient-reported outcome measure for use in routine care. The purpose of this project was to evaluate the factors associated with Edmonton Symptom Assessment System uptake among cancer patients seen at regional cancer centres and to examine if these associations have changed over time. METHODS: This was a retrospective cohort study among cancer patients eligible to complete Edmonton Symptom Assessment System assessments who were seen at regional cancer centres in Ontario between 2007 and 2015. We used linked administrative sources of health care data. Our primary outcome for each patient was defined as the rate of ESAS assessments, which was analyzed overall and on an annual basis. RESULTS: We identified 525 409 unique patients with at least 1 visit to a cancer centre during the study period. The percentage of patients with at least 1 Edmonton Symptom Assessment System assessment increased from 5% in 2007 to 67% in 2015. Analysis demonstrated that variation by region and by cancer type decreased over time: relative rates for region ranged from 0.31 to 13.3 in 2007 whereas they ranged from 0.7 to 1.56 in 2015, and relative rates for cancer type ranged from 0.03 to 1.0 in 2007 whereas they ranged from 0.55 to 1.0 in 2015. In 2015 women and people living in poorer neighbourhoods had a lower Edmonton Symptom Assessment System uptake (relative rate 0.93 and 0.91, respectively). INTERPRETATION: Ontario has implemented a patient-reported outcome program across the province; over time, uptake has improved and variation by cancer type and region has decreased. Variation persists for other patient characteristics, which suggests that there are opportunities to improve equity in the program.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".