Adherence to quality breast cancer survivorship care in four Canadian provinces: a CanIMPACT retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: In order to maximize later health, there are established components and guidelines for quality follow-up care of breast cancer survivors. However, adherence to quality follow-up in Canada may not be optimal, and may vary by province. We determined and compared the proportion of patients in each province who received adherent and non-adherent surveillance for recurrence, new cancers and late effects, recommended preventive care, and recommended physician visits for comorbidities. METHODS: Cohorts consisted of all adult women diagnosed with incident invasive breast cancer between 2007 and 2010/2012 in four Canadian provinces (British Columbia (BC) N = 9338; Manitoba N = 2688; Ontario N = 23,700; Nova Scotia (NS) N = 2735), identified from provincial cancer registries, alive and cancer-free at 30 months post-diagnosis. Their healthcare utilization was determined from one to 5 years post-treatment, using linked administrative databases. Adherence, underuse, and overuse of recommended services were evaluated yearly and compared using descriptive statistics. RESULTS: In all provinces and follow-up years, the majority of survivors had more than the recommended number of visits to either an oncologist or primary care physician (range 53.8% NS Year 3; 85.8% Ontario Year 4). The proportion of patients with the guideline-recommended number of oncologist visits varied by province (range 29.8% BC Year 5; 74.8% Ontario Year 5), and the proportion of patients with less than the recommended number of specified breast cancer-related visits with either an oncologist or primary care physician ranged from 32.6% (Ontario Year 2) to 84.4% (NS Year 3). Underuse of surveillance breast imaging was identified in NS and BC. The proportion of patients receiving imaging for metastatic disease (not recommended in the guidelines) in BC, Manitoba, and Ontario (not reported in NS) ranged from 20.3% (BC Year 5) to 53.3% (Ontario Year 2). Compliance with recommended physician visits for patients with several chronic conditions was high in Ontario and NS. Preventive care was less than optimal in all provinces with available data. CONCLUSIONS: Quality of breast cancer survivor follow-up care varies among provinces. Results point to exploration of factors affecting differences, province-specific opportunities for care improvement, and the value of administrative datasets for health system assessment.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".