Mobile Clinical Decision Tools Among Emergency Department Clinicians: Web-Based Survey and Analytic Data for Evaluation of The Ottawa Rules App
Notice bibliographique
Résumé
BACKGROUND: The Canadian CT Head Rule (CCHR), the Canadian Transient Ischemic Attack (TIA) Score, and the Subarachnoid Hemorrhage (SAH) Rule have all previously demonstrated the potential to significantly standardize care and improve the management of patients in emergency departments (EDs). On the basis of user feedback, we believe that the addition of these rules to the Ottawa Rules App has the potential to increase the app's usability and user acceptability. OBJECTIVE: This study aimed to evaluate the perceived usefulness, acceptability, and uptake of the enhanced Ottawa Rules App (which now includes CCHR, TIA, and SAH Rules) among ED clinicians (medical students, residents, nurses, and physicians). METHODS: The enhanced Ottawa Rules App was publicly released for free on iOS and Android operating systems in November 2018. This study was conducted across 2 tertiary EDs in Ottawa, Canada. Posters, direct enrollment, snowball sampling, and emails were used for study recruitment. A 24-question Web-based survey was administered to participants via email, and this was used to determine user acceptability of the app and Technology Readiness Index (TRI) scores. In-app user analytics were collected to track user behavior, such as the number of app sessions, length of app sessions, frequency of rule use, and the date app was first opened. RESULTS: A total of 77 ED clinicians completed the study, including 34 nurses, 12 residents, 14 physicians, and 17 medical students completing ED rotations. The median TRI score for this group was 3.38, indicating a higher than average propensity to embrace and adopt new technologies to accomplish goals in their work or daily lives. The majority of respondents agreed or strongly agreed that the app helped participants accurately carry out the clinical rules (56/77, 73%) and that they would recommend this app to their colleagues (64/77, 83%). Feedback from study participants suggested further expansion of the app-more clinical decision rules (CDRs) and different versions of the app tailored to the clinician role. Analysis and comparison of Google Analytics data and in-app data revealed similar usage behavior among study-enrolled users and all app users globally. CONCLUSIONS: This study provides evidence that using the Ottawa Rules App (version 3.0.2) to improve and guide patient care would be feasible and widely accepted. The ability to verify self-reported user data (via a Web-based survey) against server analytics data is a notable strength of this study. Participants' continued app use and request for the addition of more CDRs warrant the further development of this app and call for additional studies to evaluate its feasibility and usability in different settings as well as assessment of clinical impact.
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 | 0,006 | 0,028 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 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 ».