Improving the Transition From Oncology to Primary Care Teams: A Case for Shared Leadership
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article discusses the case of a 47-year-old woman who underwent primary therapy with curative intent for breast cancer. The case illustrates a number of failure events in transferring information and responsibility from oncology to primary care teams. The article emphasizes the importance of shared leadership, as multiple team members, dispersed in time and space, pursue their own objectives while achieving the common goal of coordinating care for survivors of cancer transitioning across settings. Shared leadership is defined as a team property comprising shared responsibility and mutual influence between the patient and the patient's family, primary care providers, and oncology teams, whereby they lead each other toward quality and safety of care. Teams, including the patient-family, should achieve leadership when their contribution is relevant in managing task interdependence during transition. Shared leadership fosters coordinated actions to enable functioning as an integrated team-of-teams. This article illustrates how shared leadership can make a difference to coordinate interfaces and pathways, from therapy with curative intent to the follow-up and management of survivors of breast cancer. The detailed case is elaborated as a clinical vignette. It can be used by care providers and researchers to consider the need for new models of care for survivors of cancer by addressing the following questions. Who accepts shared leadership, how, with whom, and under what conditions? What is the evidence that supports the answers to these questions? The detailed case is also valuable for medical and allied health professional education.
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.
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 | 0.001 | 0.005 |
| 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 it