Cancer Partnerships Hub (CPH) Model: Implementing an Organizational Innovation to Enhance Engagement of Patient-Partner in Cancer Care Services
Bibliographic record
Abstract
Patient partnership is rapidly becoming a cornerstone of effective care, with healthcare professionals recognizing the immense value of collaboration. This case study delves into the innovative Cancer Partnership Hub (CPH) model implemented at the Integrated University Health and Social Services Center of East Montreal Island (CIUSSS-EMTL) in Quebec, Canada. The CPH model exemplifies the integration of patients as active agents within the cancer program. The CPH Model is designed to offer comprehensive support and information services, providing a diverse array of resources crafted ``by and for'' people living with and beyond cancer (PLC). Rooted in the project's motto ``Engage. Share. Progress'', the CPH unites a community of PLC, patient-partners, collaborators, and committed healthcare professionals, all working together to enhance care and services within the cancer program of the CIUSSS-EMTL. Expanding upon existing models of patient and public engagement, the CPH has introduced significant innovations in its design and structure. This article aims to present the CPH model as a case study, offering insights into its innovative organizational structure. It delves into the development and implementation process, including the establishment of leadership, empowerment of patient partners, amplification of patient voices, creation of a welcoming environment, and ongoing monitoring and adaptation of services. Moreover, it explores the key principles and objectives of the CPH, emphasizing its role in supporting people living with cancer, enhancing the cancer program, fostering collaborations, and empowering patient partners, providing a valuable insight for healthcare organizations seeking to prioritize patient partnership and deliver patient-centered care effectively in oncology settings.
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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 | 0.013 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".