A236 UTILIZATION OF AN URGENT GASTROENTEROLOGY CLINIC FOR PATIENTS SEEN IN THE EMERGENCY ROOM OR URGENT CARE CENTRE
Bibliographic record
Abstract
The Canadian Association of Gastroenterology reports that wait times to see a gastroenterologist are too long, even for urgent problems. To improve timely access for patients, a dedicated urgent GI clinic started at St Joseph’s Healthcare Hamilton in March 2014. The clinic accepted referrals from the emergency room (ER) and urgent care clinic with a capacity of 6 patients per week booked within 3 weeks of referral. Suggested referral criteria included a) subacute GI bleeding b) progressive dysphagia c) suspected diagnosis of IBD based on imaging/results and other reasons including liver diseases. To review the utility of the clinic, appropriateness of referrals, and utilization of endoscopy resources to guide any necessary changes to the clinic. Retrospective review of all cases that were seen in the urgent GI clinic to identify demographic factors, reasons for referrals, duration of symptoms, whether they had previously seen a gastroenterologist, utilization of endoscopy resources and requirement for ongoing follow up. Between March and October 2014, 119 patients were seen in the urgent GI clinic and 118 were reviewed. An average of 4.5 patients was seen per clinic out of 6 allocated spots giving a missed appointment rate of 25%. The average age of the patient was 52.9 years, and 57% were females. The mean duration of symptoms was 23.4 weeks, but 59% of patients had more acute symptoms for 1 week or less when presenting to ER or urgent care. The most common reasons for referrals included lower GI bleeding (31%), abdominal pain (25%), upper GI bleeding (13%), anemia (5%), and dysphagia (3%). Of the 119 patients, 42% had previously seen a gastroenterologist, and 46% had recently visited the ER or urgent care. A high proportion (71%) was booked for endoscopic tests after the consultation, and 52% were booked for a follow-up appointment. The urgent clinic provides a useful mechanism to see subacute GI illnesses in a timely fashion. However, further optimization is needed to reduce incidence of missed appointments, seeing patients already under care of a gastroenterologist, and referrals for chronic GI illness. There are challenges in high endoscopy utilization and clinic follow-up associated with this strategy. Longer studies may help illustrate further benefits of healthcare utilization by examining reduction in recurrent visits to ER or urgent care. None
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".