Evaluation of the Effectiveness of Ophthalmology Emergency Clinic Intake Forms
Bibliographic record
Abstract
Objective: To evaluate the effectiveness of a novel patient intake form in an emergency ophthalmology clinic at a Canadian academic center. Despite the popularity of intake forms, they have not been previously reported in the literature in an emergency ophthalmology clinic setting. Methods: All new patients at the University of Ottawa emergency ophthalmology clinic were provided with a patient intake form to complete while waiting to be seen. Ophthalmology residents and nurses at the University of Ottawa completed an effectiveness survey evaluating the benefits of these forms after 24 months of use. Emergency ophthalmology clinics at other Canadian academic institutions were questioned regarding their use of patient intake forms. Results: Nine residents and two nurses completed the effectiveness survey. The mean (SD) score assessing the use of the form (1=never, 5=every patient encounter) was 3.90 (1.20). The greatest perceived benefit involved improved clinic efficiency (91%). All (100%) of responses indicated that the form should continue to be used in practice. Of the other 14 ophthalmology residency programs in Canada, nine currently do not use an intake form, two have forms completed by nurses and three utilize a form but are dissatisfied with their results. Conclusions: Our results suggest that there are benefits with respect to clinic efficiency, accuracy of medical information, collaboration between healthcare professionals, and patient satisfaction when utilizing patient intake forms in an emergency ophthalmology setting. The use of similar forms may provide an opportunity to improve clinical practice at other academic institutions within Canada.
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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 | 0.018 | 0.077 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".