The Impact of Visualization Dashboards on Quality of Care and Clinician Satisfaction: Integrative Literature Review
Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
Notice bibliographique
Résumé
BACKGROUND: Intensive Care Units (ICUs) in the United States admit more than 5.7 million people each year. The ICU level of care helps people with life-threatening illness or injuries and involves close, constant attention by a team of specially-trained health care providers. Delay between condition onset and implementation of necessary interventions can dramatically impact the prognosis of patients with life-threatening diagnoses. Evidence supports a connection between information overload and medical errors. A tool that improves display and retrieval of key clinical information has great potential to benefit patient outcomes. The purpose of this review is to synthesize research on the use of visualization dashboards in health care. OBJECTIVE: The purpose of conducting this literature review is to synthesize previous research on the use of dashboards visualizing electronic health record information for health care providers. A review of the existing literature on this subject can be used to identify gaps in prior research and to inform further research efforts on this topic. Ultimately, this evidence can be used to guide the development, testing, and implementation of a new solution to optimize the visualization of clinical information, reduce clinician cognitive overload, and improve patient outcomes. METHODS: Articles were included if they addressed the development, testing, implementation, or use of a visualization dashboard solution in a health care setting. An initial search was conducted of literature on dashboards only in the intensive care unit setting, but there were not many articles found that met the inclusion criteria. A secondary follow-up search was conducted to broaden the results to any health care setting. The initial and follow-up searches returned a total of 17 articles that were analyzed for this literature review. RESULTS: Visualization dashboard solutions decrease time spent on data gathering, difficulty of data gathering process, cognitive load, time to task completion, errors, and improve situation awareness, compliance with evidence-based safety guidelines, usability, and navigation. CONCLUSIONS: Researchers can build on the findings, strengths, and limitations of the work identified in this literature review to bolster development, testing, and implementation of novel visualization dashboard solutions. Due to the relatively few studies conducted in this area, there is plenty of room for researchers to test their solutions and add significantly to the field of knowledge on this subject.
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.
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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 découle