Developing an Interprofessional Care Plan for an Older Adult Woman With Breast Cancer: From Multiple Voices to a Shared Vision
Bibliographic record
Abstract
Interprofessional collaboration is central to quality patient care; however, little is known about developing interprofessional care plans, particularly in oncology. This article describes the development of an interprofessional care plan for an older adult woman with breast cancer. Two collaborative expert workshops were used; 15 clinical experts reviewed an online patient case and were asked to prepare a uniprofessional care plan. In workshop 1, participants worked from a draft interprofessional care plan, synthesized from the uniprofessional care plans by research associates, to arrive at consensus on an ideal interprofessional care plan. Using qualitative inductive content analysis of workshop transcripts, specific changes and overall key principles were identified and used to revise the draft plan. Based on these findings, a generalized interprofessional care plan/oncology model was developed. Revisions and proposed model were validated through consensus by participants during workshop 2. Participants highlighted the iterative, cyclical, and multilayered nature of patient care experiences; the importance of central patient profiles, which are contributed to and validated by all healthcare professionals; and the importance of assessing patient understanding. Participation of a patient representative provided an invaluable contribution. The process and model provide a unique framework for interprofessional care plan development in other settings and patient populations.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".