A Journey to Patient-Centered Care in Ontario, Canada
Bibliographic record
Abstract
PURPOSE: This article describes the process undertaken to implement the Best-Practice Guideline on Client (patient)-centered care. Curriculum development, the application of theoretical frameworks, and the use of a variety of models for care and learning are described. Clinical nurse specialists demonstrated successful curriculum development, facilitation, and research uptake by participants. BACKGROUND: As a Canadian teaching hospital, we are committed to promoting a variety of evidence-based practice guidelines that are systematically developed and framed around a core set of values consistent with our ethical frameworks and based on current research and theories. Many guidelines are prescriptive; however, this particular guideline posed challenges because of its conceptual and philosophical nature. DESCRIPTION: Challenges of curriculum development were resolved using the "know-do-be" framework and "proximity" as the element of the caring component of patient-centered care. Elements of narrative theory and inclusion of nursing and other experiential learning models were utilized. Competing corporate initiatives that linked with client-centered care were included. OUTCOMES: The process resulted in the development of a 12-week course entitled "The Telling Stories of our Practice-Client-Centered Care." Evidence of sustainability and spread of this best-practice guideline to other corporate initiatives through research, patient safety workshops, nursing staff orientation, and other educational activities focusing on professionalism, quality of work life, and falls prevention is described. CONCLUSIONS: Clinical nurses specialists and other advanced practice nurses demonstrated clinical competencies in initiating changes that resulted in increased use of evidence-based practice.
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.
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 | 0.005 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".