Communication Errors in Dispatch of Air Medical Transport
Notice bibliographique
Résumé
BACKGROUND: Communication errors are a source of preventable medical errors. In high-risk health care settings, identifying the source and addressing root causes can reduce error and improve patient safety. While air medical transport is a high-risk setting, its sources and rates of error have been investigated only within the last several years. OBJECTIVES: This investigation examined the rate and types of communication errors during call booking of interfacility air medical transports. The primary objective was to determine the incidence and type of errors when the initial requests for transfer took place between the sending facility and transport medicine communication center. The secondary objective was to identify potential underlying causes of these errors. METHODS: Requests for urgent and emergent interfacility air medical transfers were examined prospectively during a consecutive two-week period. As the first step in call booking, sending facility staff speak directly to communication center staff and are asked for administrative, demographic, and medical details to determine patient acuity and call priority. After this information was captured, investigators contacted the sending facility to verify the information and identify any communication errors. Errors were classified as major (potentially impacting care) or minor (unlikely to impact care) and as errors of omission or commission. Common error types were presented to a management focus group to identify potential contributing causes for these errors. RESULTS: One hundred twelve calls were randomly selected during the study period, with 98 meeting study criteria. Of those, 41 (42%) calls contained a total of 65 errors. Eleven were classified as major, including five errors of omission and six errors of commission. The most common major errors were recording "no drug allergies" when a drug allergy was present (n = 4), incorrect diagnosis (n = 2), and failure to record that patients were intubated or required mechanical ventilation (n = 2 each). There were 54 minor errors, including 41 omission errors and 13 commission errors. Nearly half the errors were attributed to procedures and software. No identified error resulted in patient harm or an adverse outcome. CONCLUSIONS: Communication-based errors are common in the initial phases of call booking in air medical transport. Human and process-driven errors contribute equally to these errors.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,054 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
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 source (Gemma direct ou Codex distillé), 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 ».