Cancer Care Ontario’s lung disease pathway initiative: Building resources for lung cancer quality care.
Bibliographic record
Abstract
e17531 Background: Cancer Care Ontario (CCO) is the provincial agency mandated to improve the quality of cancer care in Ontario. CCO has driven quality improvement (QI) on a programmatic basis but in 2008, introduced Disease Pathway Management (DPM) as an additional QI approach. The lung cancer (LC DPM) began in 2009 as a two-year, phased initiative. Methods: The LC DPM team, consisting of clinicians, patients and system stakeholders, was organized into five groups and focused on aspects of the patient journey from diagnosis to end-of-life care, guided by draft pathway maps of the ideal state. 17 improvement concepts were identified of which 8 were selected for detailed development at a provincial consensus conference and validated as LC DPM’s Priorities for Action. 14 regional road shows presented region-specific performance and quality data to practitioners involved in LC patient care to promote ideas for improvement. Funding was provided to support both provincial and regional initiatives that addressed identified gaps. Results: Key outputs of the LC DPM initiative were: establishment of lung diagnostic assessment programs in 14 regions; completion of diagnostic and treatment pathways for NSCLC and SCLC which were grounded in evidence; 10 improvement projects on various stages of the cancer continuum; and 6 one-year Dyspnea Management Pilot Projects. For the dyspnea projects, each funded centre used different approaches and evaluated impacts on patient symptom burden, measured by Edmonton Symptom Assessment System (ESAS), patient satisfaction and quality of life. The learnings from each project have been summarized and will be shared with all regional cancer programs to facilitate knowledge transfer. Tools to support the patient experience include a LC Patient Pathway Map (PPM) and a document, Understanding Lung Cancer. The physician and patient pathways and related materials are available on CCO's website at https://www.cancercare.on.ca Conclusions: LC DPM has proven an effective strategy to accomplish system changes across a large geography that impact the quality of LC care, processes and patient experience. Indicator development and performance management will be used to sustain the gains achieved.
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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 | 0.012 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.054 | 0.009 |
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".