A multi-perspective approach to developing the Saudi Health Informatics Competency Framework
Notice bibliographique
Résumé
BACKGROUND: Determining the key sets of competencies necessary for a Health Informatics (HI) professional to practice effectively either solo or as a member of a multidisciplinary team has been challenging for the regulator and registration body responsible for the healthcare workforce in Saudi Arabia, which is the Saudi Commission for Health Specialties (SCFHS). OBJECTIVE: The aim of this study was to develop a HI competency framework to guide SCFHS to introduce a HI certification program that meets local healthcare needs and is aligned with the national digital health transformation strategy. METHODOLOGY: A two-phase mixed methods approach was used in this study. For phase 1, a scoping review was conducted to identify HI competencies that have been published in the relevant literature. Out of a total 116 articles found relevant, 20 were included for further analysis. For phase 2, Saudi HI stakeholders (N = 24) that included HI professionals, administrators, academics, and healthcare professionals were identified and participated in an online survey, and asked to rank the importance of HI competencies distinguished in phase 1. To further validate and contextualize the competency framework, multiple focus groups and expert panel meetings were undertaken with the key stakeholders. RESULTS: For phase 1, about 1315 competencies were initially extracted from the included studies. After iterative reviews and refinements of codes and themes, 6 preliminary domains, 23 sub-domains and 152 competencies were identified. In phase 2, a total of 24 experts participated in the online surveys and ranked 58 out of 152 competencies as 'very important/required', each received 75 % or more of votes. The remaining competencies (N = 94) were included in a list for a further discussion in the focus groups. A Total of fourteen HI experts accepted and joined in the focus groups. The multiphase approach resulted in a competency framework that included 92 competencies, that were grouped into 6 domains and 22 subdomains. The six key domains are: Core Principles; Information and Communication Technology (ICT); Health Sciences; Health Data Analytics; Education and Research; Leadership and Management. CONCLUSION: The study developed the Saudi Health Informatics Competency Framework (SHICF) that is based on an iterative, evidence-based approach, with validation from key stakeholders. Future work should continue the validation, review, and development of the framework with continued collaboration from relevant stakeholders representing both the healthcare and educational communities. We anticipate that this work will be expanded and adopted by relative professional and scientific bodies in the Gulf Cooperation Council (GCC) region.
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 | 0,037 | 0,019 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,011 | 0,006 |
| Études des sciences et des technologies | 0,005 | 0,008 |
| Communication savante | 0,009 | 0,007 |
| Science ouverte | 0,002 | 0,008 |
| Intégrité de la recherche | 0,002 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
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 ».