Alberta Health Services Emergency Strategic Clinical Network Quality Improvement and Innovation forum 2021
Notice bibliographique
Résumé
The Alberta Health Services Emergency Strategic Clinical Network Quality Improvement and Innovation forum 2021. Patrick McLane and Eddy Lang on behalf of the Emergency Strategic Clinical Network Evidence-based research and quality improvement work are pivotal to health systems meeting their goals. Translating findings and disseminating innovative practices to new settings occurs in part through knowledge translation events, such as conferences and workshops. The Emergency Strategic Clinical NetworkTM (ESCN) Quality Improvement and Innovation forum fills a gap between local and national events. It is devoted to sharing methods and results of emergency department projects in Alberta among those working in emergency care. 2021 was the third consecutive year the ESCN has held this event. The event provides an opportunity for those working on quality improvement in emergency medicine to network with one another, share innovative projects, share know how and translate promising works to new settings. In addition, the event provides an opportunity to identify projects for potential development through local, provincial, or national funding opportunities. In light of the ongoing pandemic, this year’s forum was held virtually with the support of the University of Calgary Continuing Medical Education group. Funding was kindly provided by the College of Physicians and Surgeons of Alberta. Nineteen teams presented their projects orally. Invited nurse and clinician scientists ranked all submissions to the forum, and the top ranked submissions were recognized in the following categories:Submissions by ESCN staff and the event sponsor were not eligible for recognition. A new feature this year was a presentation by ESCN patient advisors on their perspectives on quality improvement, which was well received by all. Strong attendance shows the value practitioners see in the forum. In 2021, the forum was attended by approximately 140 educators, managers, nurses, physicians and researchers from across Alberta. This is a marked increase over previous years. Post-event evaluation survey feedback suggests that the online format was greatly appreciated and made the event more accessible. Requests for more rural oriented content in event feedback may also indicate that the event drew more rural attendees this year. We are pleased to partner with the Canadian Journal of Emergency Nursing to make abstracts from the event widely available. Individual presenters have had the option of submitting their abstracts for publication in CJEN. In some instances, abstracts have already been published through other conferences and so could not be submitted to CJEN. The findings presented in the abstracts are solely the work of the submitting authors. The ESCN does not guarantee the accuracy of any reported information. The views expressed in the abstracts are solely the views of the authors and do not represent the ESCN or Alberta Health Services. Correspondence to: emergencyscn@ahs.ca
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 | 0,027 | 0,026 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,002 |
| Communication savante | 0,009 | 0,002 |
| Science ouverte | 0,003 | 0,005 |
| Intégrité de la recherche | 0,008 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,105 | 0,025 |
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 ».