Deriving National Continued Competency Priorities for Emergency Medical Services Clinicians
Bibliographic record
Abstract
OBJECTIVE: Continued competency is poorly defined in emergency medical services (EMS), with no established method for verifying continued competency at a national level. The objective of this project was to refine understanding of continued competency for EMS clinicians in the U.S. and establish priorities for developing competency assessments. METHODS: A panel of EMS managers, educators, medical directors, and experts in competency assessment, simulation, and certification used a modified Delphi technique to address two questions: "What is the content for continued competency in EMS that should be assessed or verified?" (content) and "How should continued competency of EMS clinicians be demonstrated?" (process). The Delphi process was conducted through electronic conferencing and survey software over a 6-month period. In round one, panelists responded to open-ended prompts and their contributions were analyzed and categorized into themes by independent reviewers. In round two, the panel rated theme importance using five-point Likert-type scales. In round three, the panel ranked their top 10 themes, and in round four, the panel selected the most important themes for each of the two questions through consensus-building discussions. Descriptive statistics and thematic analyses were performed with Excel and STATA 16. RESULTS: Fourteen invited experts participated in all Delphi activities. The panel contributed 70 content and 35 process items from the original prompts. Following thematic analysis, these contributions were reduced to 21 and 14 unique themes, respectively. The final top five prioritized themes for content important for continued competency included (1) airway, respiration, and ventilation, (2) patient assessment, (3) pharmacology, (4) pediatrics, and (5) management of time critical disease progressions. The final top five prioritized themes for the processes for continued competency assessment included (1) assessments of evidence-based practice, (2) performance-based assessments, (3) combined knowledge and skill assessments, (4) performance improvement over time, and (5) frequent, short knowledge assessments. CONCLUSION: This modified Delphi process identified priorities for content and assessment, laying the groundwork for EMS continued competency at a national level. These findings can be leveraged by national task forces to develop transparent and consistent guidelines for systems that verify continued competency related to certification, licensure, and local credentialing.
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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 | 0.041 | 0.068 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".