Wilderness Paramedic—A Practice Analysis
Bibliographic record
Abstract
Emergency medical services (EMS) has existed in its modern form for over 50 years. EMS has become a critical public safety net and access point to the larger health care system. Mature EMS systems are in place in most urban areas. However, EMS systems are not as developed in wilderness areas. A barrier to further development of these systems is the lack of an agreed-upon standard of minimum competence and validation of specialized practice. A practice analysis was completed to create such standards. The practice analysis was completed using a multi-step process. A group of subject matter experts constructed a survey of tasks and knowledge needed for wilderness EMS (WEMS) specialty practice. The tasks and knowledge were validated through an industry survey. A total of 947 surveys were submitted for analysis. Of these, 196 were at least 55% complete and used for analysis. North America was heavily represented as a primary practice location with 177 (90.3%) responses out of the 196 total. Of these 177 responses, 164 (92.7%) were from the United States and 12 (6.8%) were from Canada. One hundred seven of the 116 tasks identified by the subject matter expert group were passed by the survey group, and 164 of the 175 knowledge statements were passed by the survey group. An index of agreement (IOA) was calculated and found to be greater than 0.9 for each task and knowledge statement across all subgroups. A content coverage rating was also calculated and the results indicate survey participants felt the content was "adequate" to "well" covered. The survey results were used to construct a pilot examination. Beta testing of the pilot examination was performed. The beta test results were analyzed and a cut score was determined using the Angoff method with a Beuk compromise. The final product of this process is a defensible exam that will certify candidates' cognitive knowledge of the specialty of WEMS. Completion of this practice analysis solidifies WEMS as distinct subspecialty of out-of-hospital medicine. Additionally, it establishes a consensus definition of wilderness paramedicine and standards that may be used by WEMS systems and regulatory entities.
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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 | 0.015 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".