Evaluation of a system-level organizational approach to person-centered care education and implementation toolkit.
Bibliographic record
Abstract
67 Background: Cancer Care Ontario (CCO) is an Ontario government agency which drives quality and improvement in the delivery of care and the patient experience for the Ontario cancer system. Person-Centred Care (PCC) has been identified as a goal from the recent Institute of Medicine (IOM) report and as a corporate strategic priority at CCO. As an initial step in a province-wide PCC strategy, CCO is developing and internally disseminating a patient engagement toolkit and eLearning module with expansion to regional cancer programs. Methods: The PCC eLearning module defines the care approach and explains the corporate goals and objectives of practicing PCC at CCO. Pre- and post-evaluation metrics are embedded to measure module impact on a rating scale with respect to: (1) understanding of PCC; (2) willingness to include the patient voice in CCO work; and (3) understanding of the role of patients who serve as advisors at CCO. The Patient Engagement Toolkit was developed as a step-by-step guide on why and how to engage Patients and Family Advisors (PFAs) in different organizational contexts. To test effectiveness and impact, we piloted the toolkit in 6 interactive sessions across 7 departments with 184 CCO employees over 2 months (Clinical Program and Quality Initiatives, Regional Program, Communication, Finance/Procurement/Facilities, HR, Business Analyst/Project Management Office). We are taking a comprehensive mixed methods evaluation approach with online surveys and key informant interviews to identify uptake and barriers. Results: Preliminary findings suggest considerable increase in the understanding of PCC and the role of PFAs at CCO, with 138 current instances of patient engagement in 1 quarter. After an introduction to the toolkit, many employees (86.7%) understood the value of engaging PFAs and most (63.7%) felt willing to start. Conclusions: Initial program evaluation demonstrates an increase in the understanding and implementation of direct (e.g., joining committees/working groups) and indirect PFA engagement (e.g., speaking at events/in focus groups) across CCO departments. Further evaluation of the toolkit at a provincial level is needed.
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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 | 0.054 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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; 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".