Retrospective Analysis of Adult Patients Presenting to the Acute Care Setting Requesting Prescriptions
Bibliographic record
Abstract
INTRODUCTION: Patient visits to the emergency department (ED) or urgent care centre (UCC) for the sole purpose of requesting prescriptions are challenging for the patient, the physician, and the department. The primary objective of this study was to determine the characteristics of these patients, the nature of their requests, and the response to these requests. Our secondary objective was to determine the proportion of these medication requests that had street value. METHODS: This was a retrospective, electronic chart review of all adult patients requesting a prescription from a two-site ED and/or an UCC in a medium-sized Canadian city between April 1, 2014-June 30, 2017. Recorded outcomes included patient demographic data and access to a family doctor, medication requested, whether or not a prescription was given, and ED length of stay. Medication street value was determined using a local police service listing. RESULTS: A total of 2,265 prescriptions were requested by 1,495 patients. The patient median [interquartile range] age was 43 [32-54] years. A family doctor was documented by 55.4% (939/1,694) of patients. The two most commonly requested categories of medications were opioid analgesics 21.2% (481/2,265) and benzodiazepine anxiolytics 11.7% (266/2,265). Of patients requesting medication, 50.5% (755/1,495) requested medications without street value including some with potential to cause serious adverse health effects if discontinued. The requested prescription was received by 19.9% (298/1,495) of patients; 15.3% (173/1,134) returned for further prescription requests. The 90th percentile length of stay was 3.2 and 5.6 hours at the UCC and ED, respectively. CONCLUSION: Patients who presented to the ED or UCC sought medications with and without street value in almost equal measure. A more robust understanding of these patients and their requests illustrates why a 'one-size-fits-all' response to these requests is inappropriate and signals some fault lines within our local healthcare system.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".