Proceedings of the 2nd Implementation Science Health Conference Australia: Sydney, NSW, Australia, 23-24 March 2023
Bibliographic record
Abstract
<br/>Background: Despite the known benefits of routinely collecting Patient Reported Outcomes (PROs) in cancer care clinical services, implementation of such programs have been uncoordinated and inconsistent in Australia. In Canada, PRO collections have been routine practice for over 10 years and thus learnings from these mature programs may provide useful insights for Australian practice. This study aimed to examine influencing factors that contribute to the sustainability of a mature program of routinely collected PROs in cancer care clinical services.<br/>Methods: Key stakeholders in PRO collection programs across the 14 cancer centres in the province of Ontario, Canada were invited to participate in a qualitative interview. Using an implementation science-based approach through process mapping and qualitative interviews, factors influencing sustainability were explored. The interview guide was designed using the domains of the Program Sustainability Assessment Tool. Influencing barriers and enablers were identified across recommendations for sustainability through thematic analysis using framework methodology.<br/>Results: Twenty-four key stakeholders participated in interviews. Example roles of participants ranged from PRO project coordinators, nurse- and clinician- leads for implementation of PRO programs across provincial cancer centres, academic researchers involved in pilot testing and program design, and PRO policy coordinators from peak body governmental organisations. Thematic analysis of recommendations to implement and sustain PRO collection programs identified four major themes with recommendations within each; planning for success, acute necessities, ironing out issues, long-term essentials. Key recommendations included provision of a PRO implementation coordinator, selection of action-based outcome and process measures, and reiteration and feedback.<br/>Conclusions: This study provides recommendations and insights from a mature PRO collection program. These insights, along with patient perspectives, should be considered in Australian efforts to implement similar PRO collection programs within cancer care clinical services. <br/>
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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 | 0.020 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.016 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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; both teacher heads agree on what is shown here.
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".