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Cancer Care Ontario’s lung disease pathway initiative: Building resources for lung cancer quality care.

2013· article· en· W2602299717 on OpenAlexaffabout
William K. Evans, Yee Ung, Anna Chyjek, Angelika Gollnow, Carol Sawka

Bibliographic record

VenueJournal of Clinical Oncology · 2013
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsCancer Care OntarioUniversity of TorontoMcMaster University
Fundersnot available
KeywordsMedicineLung cancerAgency (philosophy)Quality managementQuality of life (healthcare)CancerHealth careCare pathwayNursingFamily medicineOncologyOperations managementManagement systemInternal medicinePolitical science

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.955
Threshold uncertainty score0.669

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0050.002
Scholarly communication0.0050.003
Open science0.0030.009
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0540.009

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.

Opus teacher head0.387
GPT teacher head0.630
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2013
Admission routes2
Has abstractyes

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