Primary Care Paramedic–administered Ketamine in British Columbia, Canada: A Patient Safety–focused Observational Study
Bibliographic record
Abstract
OBJECTIVES: In Western Canada, British Columbia Emergency Health Services (BCEHS) aimed to enhance prehospital pain management by authorizing Primary Care Paramedics (PCP) to administer intranasal (IN) ketamine. The objective of this study is to describe patient safety implications of expanding PCP scope to include IN ketamine. METHODS: This retrospective, observational study reviewed patient care records of the first 100 consecutive patient encounters where PCPs administered IN ketamine for pain between December 2020 and September 2021. Data analysis used the Canadian Quality and Patient Safety Institute and Rights of Medication Administration frameworks. RESULTS: Of the 100 patients, 74% met the analgesia clinical practice guideline (CPG) criteria: adult, trauma, and moderate to severe pain. Most injuries (31%) involved extremities or hips/pelvis (18%). With 6 cases missing data, an 11.2% dosage error rate (>5 mg deviation) was identified. In 14 cases, PCPs did not contact mandatory clinical support and administered ketamine outside of the CPG. Documentation errors occurred in 25% of patient encounters, particularly with pain scores (20), patient weight (15), and vital signs (8), possibly indicating incomplete patient assessments. No instances of adverse patient outcomes resulting from dosing errors or missed consultations were observed throughout the study. CONCLUSIONS: This study highlights the safety implications of PCP-administered ketamine, including concerns about weight-based dosing, CPG compliance, and documentation standards. The key competencies of the Canadian Patient Safety Institute framework offer a foundation for addressing these safety concerns before expanding ketamine administration for broader PCP practice.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".