Achieving Person-centered Care: The Need for Multiple Strategies
Bibliographic record
Abstract
Background: Evidence from patient satisfaction surveys, needs assessments, and stakeholder forums provide a clear picture that cancer patients are not receiving the full range of supportive care services that could be of benefit to them. The cancer system needs to undergo a shift toward person-centered care. Such a cultural shift requires concerted effort and multiple strategies to be successful.Objective: The purpose of the Cancer Journey Action Group of the Canadian Partnership Against Cancer is to provide leadership to achieve person-centered care in the Canadian cancer care system.Methods: The Cancer Journey Action Group has developed and implemented several initiatives to demonstrate how person-centered care can be achieved. The initiatives include programs in screening for distress (6th vital sign), patient navigation, on-line support groups, survivorship care plans projects, cancer transition education, and palliative care/end-of-life education. Tools to support this work have been designed including evidence-based practice guidelines, algorithms, and on-line education modules. Evaluation has focused on program uptake, educational effectiveness, inter-professional teamwork and patient satisfaction.Results: All initiatives have been evaluated by patients/survivors as helpful. Issues of importance to patients/survivors are the focus of conversations with, and assessments by, health care professionals. Critical success factors across the respective programs for achieving person-centered care include clarity of a shared vision, leadership, persistent and concerted effort, and consistent messaging in communications.Conclusions: Demonstration projects undertaken for each topic area have provided an excellent opportunity to learn about best practices to implement the respective approaches. Guiding principles for implementation and relevant tools/resources have been developed as a result. Although progress toward person-centered care is evident, intentional and concerted efforts are necessary to sustain momentum of these efforts in routine clinical practice.
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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 | 0.127 | 0.084 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.016 | 0.025 |
| Scholarly communication | 0.025 | 0.033 |
| Open science | 0.009 | 0.046 |
| Research integrity | 0.013 | 0.033 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".