P.068 Quality improvement in Infantile Spasms through standardization: a tertiary-care centre retrospective chart review implementation study
Bibliographic record
Abstract
Background: Infantile Spasms (IS) is a rare epilepsy syndrome with characteristic features, and a strong consensus regarding treatment strategies. Clinical care pathways provide standardized and evidence-based patient care, support care quality and improve patient outcomes. Standardized electronic notes may support data collection and quality. After the concurrent implementation of an IS pathway and standardized electronic note at the Alberta Children’s Hospital in 2015, improvements in patient outcomes and quality of care were anticipated. Methods: A single-centre, retrospective chart review of patients diagnosed with Infantile spasms in Alberta, Canada from 2011-2019 was completed. Patient characteristics and outcomes were analyzed by pre-pathway and post-pathway implementation status. Results: Rates of 3-month spasm remission, and of remission without relapse did not significantly differ between pre- and post-pathway cohorts. Rates of 2-week spasm remission were not obtainable from a significant proportion of pre-pathway patient records when compared to the post-pathway group, indicating patient record quality improved following the electronic note implementation. A significant proportion of patients received Prednisolone as their first treatment for IS post-pathway implementation compared to pre-pathway (p<0.001). Conclusions: A single-centre experience with concurrent implementation of an IS pathway and standardized electronic note demonstrated no significant changes in patient outcomes. Potential improvements for patient care are identified.
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| 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".