Advancing Learning Health Systems: A Preliminary Model of Learning at a Large Canadian Hospital
Bibliographic record
Abstract
The ability to learn is central to innovation and performance across industries. While learning drivers are well-articulated (experimentation, risk-taking, decision-making, dialogue, and interaction), they receive little attention in healthcare research. This case study explored the nature of learning within Trillium Health Partners (THP), the largest hospital system in Canada by patient volume. Formal leaders at THP completed the Organizational Learning Capability Survey. A latent profile analysis (LPA) identified the number and nature of distinct learning profiles. Semi-structured interviews were conducted to systematically explore the factors enabling or stifling organizational learning. N=231 leaders completed the survey. LPA identified two distinct learning profiles: one with high perceived learning capability and another with moderate capability. Interviews with leaders (n=12) from both groups described the factors that influence organizational learning (or a lack thereof). This systematic understanding of how learning occurs—or fails to occur—in healthcare organizations will support the development of evidence-based processes and programs that foster the learning necessary to develop innovative delivery models at scale.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".