Staging the development and implementation of a Coordinated Cancer Care Model using risk-based survivorship care: A deliberative discussion among multiple stakeholders.
Bibliographic record
Abstract
e18027 Background: Risk-based survivorship care has become one of the best practices care recommended by the Institute of Medicine. It involves coordinated follow-up services based on the risk of long-term and late effects, cancer recurrence and an individualised care plan. Risk-based care requires specific knowledge about cancer histology, treatments, and potential consequences of cancer and its treatment to guide surveillance, screening and counseling. Diagnostic and treatment details and their associated health risks may not be known by survivors or their multiple care providers. Implementing risk-based survivorship care is often challenging for providers. This presentation report on a deliberative workshop on the development and planning of a risk-based survivorship care model. Methods: The deliberative workshop is part of a larger study in two regional cancer networks in Quebec, selected for there differences (geographic location, population size, academic mandate). A total of 25 key informants (researchers, managers, family physicians, oncologists, cancer survivors, nurses, social workers) participated into the workshop on October 2nd, 2018. Deliberative discussion between local stakeholders followed by videoconference, getting together stakeholders from both networks was drawn from Gupta et al 3 steps: 1) identify the problem; 2) develop the innovation; 3) design the pilot test. Results: Although the context of the network was different, main issues were similar: 1) there is no common understanding of the concept “risk-based survivorship care”, either for survivors, primary care providers and cancer specialist; 2) “silo functioning” within and between teams is a main barriers to ensure care coordination based on risk assessment; 3) organizational assets should be formalized to insure safe coordination of survivorship care based on cancer risk assessment. Conclusions: Given the recognized importance of risk-based survivorship care and implementation challenges, deliberative discussions may provide a useful lens to inform translation of this model into real practices and guide empirical studies.
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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 | 0.094 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.009 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.005 | 0.017 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".