Patient Engagement in the Implementation of Electronic Patient-Reported Outcome Tools: The Experience of Two Early-Adopter Institutions in the Pan-Canadian Radiotherapy Patient-Reported Outcome Initiative
Bibliographic record
Abstract
AIMS: To share the patient and community engagement experience of two Canadian early adopter sites that implemented electronic patient-reported outcomes collection in radiotherapy practice. MATERIALS AND METHODS: In the first institution, the McGill University Health Centre, a socio-technical stakeholder co-design approach was used to develop a patient portal application (Opal) with built-in ePRO collection capability. Patient and family members were engaged through patient co-leadership, focus groups, semi-structured interviews, a persistent feedback form in the resultant application, and user satisfaction surveys. In the second institution, the Nova Scotia Health (NSH) centres of Dalhousie University's Department of Radiation Oncology, an industry-provided patient engagement tool was deployed. Patient and community engagement in the deployment effort was purposive to promote digital inclusion and diverse representation. Engagement was operationalized via a community feedback session and involvement of patient representatives in oversight committees. RESULTS: The McGill experience highlighted 3 particular points of concern for patients when collecting ePROs: (1) Data flow should be two-way such that patients have access to their data from the hospital (lab results, clinical notes) as well as providing their data to the hospital (ePROs); (2) If ePROs are collected, they should be used actively by clinicians or the incentive for patients to continue reporting will be diminished; (3) The inherent rigour of electronic data collection may risk frustrating patients due to the inability to skip questions or spoil responses. The Dalhousie/NSH experience demonstrated the value and importance of including a diverse set of community representatives in building an ePRO program so that it can proactively account for real-world complexities and the challenge of simultaneously addressing the needs of diverse communities. CONCLUSION: Two early-adopter Canadian cancer care programs reported on their experience and lessons learned with patient and community engagement in the rollout of their ePRO collection initiatives.
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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 | 0.010 | 0.002 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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".