Lean Transformation of the Eye Clinic at The Hospital for Sick Children: Challenging an Implicit Mental Model and Lessons Learned
Bibliographic record
Abstract
Long patient dwell time (i.e., the time between patients arriving and leaving the clinic) has been a long-standing issue in the eye clinic at The Hospital for Sick Children. By applying the Lean principles of eliminating waste and enhancing flow, we achieved a 26% reduction in the mean patient dwell time over an eight-month period. Importantly, the average time a patient spent with healthcare providers (value-added time) increased from 21% to 31%. In this paper, we summarized our experience by illustrating how an implicit mental model (conscious or unconscious conceptual framework from which we understand the world) pervades in the healthcare system based on deeply held but unexamined assumptions that arise from heuristics (general rules of thumb) and biases; how these assumptions can be tested by objective data; and how we can build a new mental model based on objective findings to improve the healthcare system.
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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 | 0.035 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.017 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".