Development and usability testing of a multifaceted intervention to reduce low-value injury care
Notice bibliographique
Résumé
BACKGROUND: Multifaceted interventions that address barriers and facilitators have been shown to be most effective for increasing the adoption of high-value care, but there is a knowledge gap on this type of intervention for the de-implementation of low-value care. Trauma is a high-risk setting for low-value care, such as unnecessary diagnostic imaging and the use of specialized resources. The aim of our study was to develop and assess the usability of a multifaceted intervention to reduce low-value injury care. METHODS: We used the Consolidated Framework for Implementation Research and the Expert Recommendations for Implementing Change tool as theoretical foundations to identify barriers and facilitators, and strategies for the reduction of low-value practices. We designed an initial prototype of the intervention using the items of the Template for Intervention Description and Replication. The prototype's usability was iteratively tested through four focus groups and four think-aloud sessions with trauma decision-makers (n = 18) from seven Level I to Level III trauma centers. We conducted an inductive analysis of the audio-recorded sessions to identify usability issues and other barriers and facilitators to refine the intervention. RESULTS: We identified barriers and facilitators related to individual characteristics, including knowledge and beliefs about low-value practices and the de-implementation process, such as the complexity of changing practices and difficulty accessing performance feedback. Accordingly, the following intervention strategies were selected: involving governing structures and leaders, distributing audit & feedback reports on performance, and providing educational materials, de-implementation support tools and educational/facilitation visits. A total of 61 issues were identified during the usability testing, of which eight were critical, 33 were moderately important, and 18 were minor. These issues led to numerous improvements, including the addition of information on the drivers and benefits of reducing low-value practices, changes in the definition of these practices, the addition of proposed strategies to facilitate de-implementation, and the tailoring of educational/facilitation visits. CONCLUSIONS: We designed and refined a multifaceted intervention to reduce low-value injury care using a process that increases the likelihood of its acceptability and sustainability. The next step will be to evaluate the effectiveness of implementing this intervention using a pragmatic cluster randomized controlled trial. TRIAL REGISTRATION: This protocol has been registered on ClinicalTrials.gov (February 24th 2023, #NCT05744154, https://clinicaltrials.gov/ct2/show/NCT05744154 ).
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 | 0,023 | 0,043 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,002 | 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 ».