Ovarian cancer pathway map development as an approach to identifying priority areas for quality improvement in Ontario.
Bibliographic record
Abstract
e18190 Background: Disease Pathway Management (DPM) is the unifying approach to the way in which Cancer Care Ontario (CCO) sets priorities for cancer control, plans cancer services and improves the quality of care in Ontario. In January 2015, DPM began developing an ovarian cancer pathway map (OCPM) to map the patient journey along the ovarian cancer care continuum. Objective: to report on the OCPM development process as a tool to identify key priorities for ovarian cancer management. Methods: DPM convened a multidisciplinary/multi-stakeholder ovarian cancer working group with regional and specialty representation from across Ontario. Over 12 months, 30 individuals participated in an in-person meeting and monthly teleconferences. The OCPM was drafted using guidelines developed by CCO’s Program in Evidence Based Care (PEBC) and considered multiple sources of evidence-based practice from several jurisdictions. Throughout the development process the working group was asked to discuss and reach consensus on key priorities for improving care. Results: Twenty-five priority areas were identified across the continuum in: prevention, diagnosis, treatment, and follow-up. Opportunities were identified for: development/endorsement of evidence-based guidelines, quality improvement, horizon scanning, and an OCPM knowledge translation strategy. Potentially actionable items were aligned with relevant internal and external stakeholders including the PEBC, provincial drug reimbursement programs and other quality improvement teams within CCO. Conclusions: The process of bringing multidisciplinary experts together in order to develop the OCPM successfully identified key priorities across the spectrum of care in Ontario and allowed identification of potential opportunities for quality improvement, development of practice guidelines and new models of care. In turn, the OCPM provides a patient-centred disease focused framework from which stakeholders can approach and evaluate new initiatives in the context of the ovarian cancer care continuum.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.040 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".