Partnering with patients and caregivers to improve systemic treatment regimen information.
Bibliographic record
Abstract
185 Background: Cancer Care Ontario’s Drug Formulary is a web-based drug information resource. Patient information is currently provided as single-drug information sheets, with a limited number of multi-drug regimen information sheets (RIS) for breast and lung cancer treatments. Patients identified a need to create additional, high-quality, “user-friendly” RIS. Objectives of this project were to 1) engage patients and caregivers in RIS redesign; 2) evaluate the original vs a redesigned model RIS; and 3) use the model RIS template to create additional RIS across disease sites. Methods: The project team included a patient and family advisor (PFA) and clinical and research experts. This was a qualitative study between August 2017 to May 2019. A focus group (FG) was conducted with 5 PFAs to identify and prioritize drug information needs. A model RIS was designed, incorporating FG input and health literacy best practices. RIS were evaluated through blinded comparative cognitive interviews with 13 PFAs, to assess RIS for usability, understandability and content relevance. Evaluation informed iterative revisions. RIS were also evaluated by clinical and education experts using the Patient Education Materials Assessment Tool (PEMAT). An RIS style guide was developed to inform the creation of future RIS. Ethics approval was obtained from the University of Toronto. Results: The FG prioritized information on regimen details, Dos and Don’ts while on treatment, drug interactions, side effects and contact information. Guidance was provided on simplifying language, highlighting important information and aesthetics. Cognitive interviews consistently reported preference for model RIS over original RIS in most domains. PEMAT scores for original versus model RIS were 64% and 94% respectively (for understandability) and 60% and 82% respectively (for actionability). To date, the style guide has informed the creation of RIS for 10 high-use regimens. Conclusions: PFA and clinician co-design along with health literacy best practices informed measurable improvements in RIS. The style guide will enable the future creation and ongoing evaluation of high-quality RIS to enhance the cancer treatment experience for patients and caregivers.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".