Wilderness Paramedic—A Practice Analysis
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».