A165 ASSESSING ATTENDANCE OF SUBSTANCE USER ENDOSCOPIES (A.S.U.R.E)
Bibliographic record
Abstract
Abstract Background In Canada, British Columbia (BC) is the leading province in opioid deaths with 30.6 per 100,000 population. Since substance users are stigmatized in health care, patient care requires specific, individualized management strategies, which often creates a gap between the patient and health care service. Diagnostic studies remain a challenge due to lack of funding and the unique requirements necessary to treat this patient population efficiently. Thus, new methods of prevention must be cultivated to ensure ideal patient care. Aims To investigate the proportion of patients on restricted narcotics that failed to attend scheduled gastroenterology and hepatology appointments at our center. Methods A retrospective chart review from 01/05 – 07/19 and data analysis of patients (≥ 19 yrs.) referred to a Downtown Gastroenterology office was performed. Data was collected from an electronic medical record system and filtered through a keyword search for ‘Methadone’, ‘Suboxone’, ‘Dilaudid’, and ‘Morphine’ to create a sample size of patients with recent/ongoing use of narcotic agents. Patients with chronic pain, or terminal illness prescribed these drugs were not included. Demographic information, type of appointment scheduled and failure to attend were recorded. Results Acquired data yielded 2630 patients of which 350 patient were included. Mean age was 47 years (61% male). 35% of the patients were current narcotics users, the rest being previous users of these agents. Scheduled appointments and non-attendance are shown in Tables 2 and 3. Most patients (70%) were referred for various general GI complaints with HCV accounting for 23% of the consults. Despite the use of confirmation lines, 20% of HCV referred patients and 29% of non-HCV referred patients did not attend their first appointment. Conclusions Current and prior narcotic users failed to attend more than one quarter of scheduled gastroenterology/hepatology appointments. Ideal management of care for GI disease can’t be obtained without contact with those that provide the service. Creative, innovative management strategies are required to ensure ideal care for this unique group of patients. Funding Agencies 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 | 0.003 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".