A54 IMPROVEMENTS OF GLOBAL RATING SCALE (GRS) CANADA SCORES IN SEVEN ENDOSCOPY UNITS IN THE EDMONTON REGION USING AN INTEGRATED QUALITY IMPROVEMENT PROGRAM
Bibliographic record
Abstract
The recently developed GRS-Canada is a validated instrument whose implementation leads to improved quality and patient experience of colonoscopy. The GRS-C has two dimensions dealing with clinical quality and quality of the patient experience. Both have ratings for 6 different categories resulting in a total of 12 dimensions for the “total” GRS-C score. The GRS-C has four grading levels, going from D, the lowest level, to level A, the highest. In order to reach a certain level all questions in each domain need to be answered positively. 18 months ago the GRS was introduced in seven of the eight hospital sites where endoscopy is performed in the Edmonton Zone: University of Alberta Hospital, Royal Alexandra, Grey Nuns, Misericordia, Sturgeon, Leduc and Fort Saskatchewan. The 8th hospital WestView recently also started. The aim is to get all sites up to an A level over the next four years. Here we report on how scores improved as a result of an integrated QA program that was launched. The CAG website created for online submission of the GRS and associated improvement process was used to enter scores. This was done once every year. As can be seen marked improvements were seen in 6 of the 7 hospitals all of whom have been actively working on the project for at least 1 year. In many dimension there was improvement from a D level to a C. One site was unchanged and an eighth site is just starting. Patient surveys have been started which will further help improve scores over time. Important improvements were seen in GRS-Canada scores in Edmonton Zone endoscopy units using an integrated QA program. The program was supported by a project manager. We thank all the Edmonton endoscopy managers for their help with this project. Alberta Health Services funded the project manager
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 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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".