Negotiating for Change. The Healthcare Manager as Catalyst for Evidence-Based Practice: Changing the Healthcare Environment and Sharing Experience
Notice bibliographique
Résumé
This paper addresses the problem of the implementation of both clinical and managerial evidence-based decision-making in healthcare. The lack of implementation of research findings in clinical and management practice has been identified as a key failure in healthcare. Many await the development of better methods of research transfer led by academics and clinicians. Research transfer has become one of the highest priority are as for health services research. In this paper, the authors propose that the healthcare manager is well positioned to advance the research transfer process within the individual healthcare environment through two main mechanisms. First, healthcare managers can align decision-making structures within their own environment to facilitate evidence-based practice. This can occur by managers demonstrating a commitment to processes for the measurement and management of knowledge (identifying knowledge stewards) to the same extent that they demonstrate commitment to the measurement and management of finances. Within such a framework, the healthcare manager can build an environment in which there is an explicit "negotiation" between "knowledge stewards" (usually clinicians) and "financial stewards" (usually administrators) to achieve a common goal. The negotiation is an explicit, documented process that addresses the trade-offs that are made to avoid both financial and quality deficits in the organization (the quality deficit is defined as the gap between knowledge and practice). The second way in which healthcare managers can act as catalysts for promoting evidence-based practice is through cataloguing and reporting, using documented stories, the unique barriers to evidence-based approaches that are peculiar to their specific healthcare environments. It is hypothesized that local contextual circumstances, which can be expressed only through stories, are the most powerful barriers to research transfer within specific organizations. This has implications for what we count as useful knowledge as we try to better understand how rigorous research on the one hand and research and stories on the other contribute to strategies for research transfer at the organizational level.
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 | 0,006 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,009 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 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 ».