Analysis of the Status of Research Outputs in the Field of Knowledge Management in the Health and Healthcare Field
Notice bibliographique
Résumé
Background and Aim: The expansion of information technology has led to the production of increasing knowledge, which may be a part of this knowledge that is hidden, so the role of knowledge management is very important to reveal knowledge. On the other hand, in health research, which is basically based on the needs of patients, their caregivers, and specialists, knowledge management is of great importance for the quality of their services. The aim of the current research is to analyze the status of research outputs in the field of knowledge management in the health sector. Materials and Methods: Based on its nature, the present study is descriptive, quantitative, and applied, and was conducted using a lexical co-occurrence scientometric technique. The research community includes 2487 sources, which are the results of all research outputs in the field of knowledge management in the health sector, which are indexed in the Web of Science database. The analysis of the research questions was done through Excel, BibExcel, and VOSviewer software. Results: According to research findings, the continents of Europe, Asia, and North America, respectively, have had the highest contributions to research output in the field of knowledge management in the health and healthcare sector. Among individual countries, the United States, the United Kingdom, and Canada demonstrated the most significant activity in this area, while Iran ranked 17th. Among the United Nations Sustainable Development Goals (SDGs), the goals of Good Health and Well-being, Industry, Innovation and Infrastructure, and Quality Education have received the most attention in knowledge management research related to health and healthcare. The keyword co-occurrence map highlights the prominence of terms such as “knowledge management,” “healthcare,” and “electronic health records.” The identified thematic clusters also underscore the significance of three key domains: organizational performance, information management, and health information systems. Conclusion: In developed countries and the first level of the world, attention to knowledge management in the field of health and health is more prominent. Also, in order to achieve a high level in the field of health and health as an important and effective criterion in most development sectors, it is necessary to address other sustainable development goals, especially by establishing systems Knowledge management in the field of health helped to achieve important goals such as eradicating poverty and hunger and reducing inequalities.
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 | 0,014 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,011 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,005 | 0,002 |
| 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 ».