Substance Use and the Paramedic Role
Bibliographic record
Abstract
The crisis state of toxic drug-related morbidity and mortality is well documented on a global scale. Countries that are being hit the hardest such as the United States, are producing a mounting body of literature focused on the extremely high incidence of overdose-related deaths secondary to the increasingly toxic supply of drugs. In the United States, 136 people die every day of opioid-related drug overdoses. In British Columbia, Canada illicit drug toxicity is responsible for more deaths than suicides, homicides, motor vehicle incidents, drownings, and fire-related deaths combined. Although commonly referred to as the “opioid crisis” or “opioid epidemic,” this review will use “overdose epidemic” due to the abundant prevalence of the illicit toxic drug supply, and drugs contaminated with non-opioid substances. Because paramedics are on the front lines of the overdose epidemic, data is often mined from paramedical organizations via retrospective and prospective analysis to better understand the inner workings of the paramedic interface with PWUD. Of particular interest is how this paramedic interaction impacts a patients transition through the health care system and what, if any, effects this has on their morbidity or mortality at large. Anecdotally, the most researched areas include evaluation of naloxone access and utilization in the prehospital setting, safety of discharge on scene following a toxic drug event as well as mortality rates following an out of hospital overdose, the empathy, and attitudes of paramedics towards their care of substance users, and the expanding contexts and opportunities of paramedic-led harm reduction. What is less pronounced in the existing literature is of the paramedic's greater purpose during these interactions, and how the shifting of paramedic practice into a more holistic entity may impact a substance user’s journey not only through the health care system, but through their relationship with substance use, and recovery. What is further highlighted in the literature is that current means of overdose response are not working. The sharp increase in drug overdose-related deaths warrants an innovative approach, one that is proactive, preventative, and holistic. Paramedics on the frontlines are uniquely positioned to reduce drug-related harm, and thus their role must be fully understood. This scoping review aimed to answer the following research questions: 1. What is known about paramedics and their role with those experiencing drug-related substance use? 2. What current opportunities and gaps exist in the literature regarding the primary research question? 3. How do the implications of this research inform contemporary and future paramedic 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".