Lean transformation framework for treatment-oriented outpatient departments
Bibliographic record
Abstract
Long wait times and low resource utilisation are the most critical issues in treatment-oriented outpatient departments. While Lean has been utilised to resolve similar issues in healthcare, the literature provides no structured means of implementing Lean in outpatient departments. This study establishes a Lean transformation framework to identify a balanced patient demand by determining proper patient compositions, to schedule non-specialists to increase resource utilisation, and to level patient schedule throughout the day to reduce wait times. This framework includes a series of activities and Lean tools that are specifically adapted for use in outpatient departments. A case study is presented to illustrate the implementation of the proposed framework and its possible impacts, using data from a community hospital oncology department in Montreal, Canada. Results suggests that this framework reduces patient visit time by 36% and increases daily treatments by 39% and utilisation of chemotherapy chairs by 22%, with a possibility to implement a one-day treatment regime. The proposed framework can assist treatment-oriented outpatient departments to overcome their operational challenges and to serve as an effective guideline in their Lean transformation.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".