A Catalyst for Transforming Health Systems and Person-Centred Care: Canadian National Position Statement on Patient-Reported Outcomes
Bibliographic record
Abstract
Background: Patient-reported outcomes (pros) are essential to capture the patient's perspective and to influence care. Although pros and pro measures are known to have many important benefits, they are not consistently being used and there is there no Canadian pros oversight. The Position Statement presented here is the first step toward supporting the implementation of pros in the Canadian health care setting. Methods: The Canadian pros National Steering Committee drafted position statements, which were submitted for stakeholder feedback before, during, and after the first National Canadian Patient Reported Outcomes (canpros) scientific conference, 14-15 November 2019 in Calgary, Alberta. In addition to the stakeholder feedback cycle, a patient advocate group submitted a section to capture the patient voice. Results: The canpros Position Statement is an outcome of the 2019 canpros scientific conference, with an oncology focus. The Position Statement is categorized into 6 sections covering 4 theme areas: Patient and Families, Health Policy, Clinical Implementation, and Research. The patient voice perfectly mirrors the recommendations that the experts reached by consensus and provides an overriding impetus for the use of pros in health care. Conclusions: Although our vision of pros transforming the health care system to be more patient-centred is still aspirational, the Position Statement presented here takes a first step toward providing recommendations in key areas to align Canadian efforts. The Position Statement is directed toward a health policy audience; future iterations will target other audiences, including researchers, clinicians, and patients. Our intent is that future versions will broaden the focus to include chronic diseases beyond cancer.
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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 | 0.264 | 0.301 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.027 | 0.032 |
| Scholarly communication | 0.030 | 0.013 |
| Open science | 0.016 | 0.024 |
| Research integrity | 0.051 | 0.071 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".