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Enregistrement W4308799508 · doi:10.1016/j.ijmedinf.2022.104914

Unlocking the eHealth professionals’ career pathways: A case of Gulf Cooperation Council countries

2022· article· en· W4308799508 sur OpenAlexaboutno aff
Nasriah Zakaria, Norhayati Zakaria, Omar Alnobani, Manal Almalki, Osama El-Hassan, Mohammed Alhefzi, Mowafa Househ, Amr Jamal

Notice bibliographique

RevueInternational Journal of Medical Informatics · 2022
Typearticle
Langueen
DomaineHealth Professions
ThématiqueMobile Health and mHealth Applications
Établissements canadiensnon disponible
Organismes subventionnairesDeanship of Scientific Research, King Saud UniversityKing Saud University
Mots-cléseHealthCareer PathwaysHealth professionalsPublic relationsMedical educationMedicineBusinessKnowledge managementPolitical scienceHealth careComputer science

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: During the past two decades, various sectors and industries have undergone digital transformation. Healthcare is poised to make a full transformation in the near future. Although steps have been taken toward creating an infrastructure for digital health in the Middle East, as it stands, digital health is still an emerging field here. The current global health care crisis has underscoredthe need for digitization of the healthcare sector to provide high-value, high-quality care and knowledge generation. With the advent of digital transformation in countries around the globe, there is a rising demand for investment and innovation in health information technology. With the demand for health informatics (HI) graduates in different disciplines (e.g., healthcare professions, information technology, etc.), there is an urgent need to determine and regulate clear career pathways and the core competencies necessary for digital health professional to practice effectively and to allow technology to add value to the healthcare systems. Given the changing landscape of the profession, the Kingdom of Saudi Arabia (KSA) and the Gulf Cooperation Council (GCC) countries are experiencing a rising demand to produce digital health professionals who can meet the needs of all the stakeholders involved, including patients, healthcare professionals, managers, and policymakers. However, despite the number of region-wide initiatives in the form of training programs, there remains a knowledge-practice gap and unclear job roles within the HI community. In recent years, regional digital health workforce initiatives have been put forward, such as the GCC Taskforce on Workforce Development in Digital Healthcare. The taskforce initiated a survey and several workshops to identify and classify HI disciplines according to the needs of the job market and through comparisons with similar efforts developed across the globe, such as the TIGER project and the EU*US eHealth Work project. Digital health implementation has been flourishing in the Middle East for the past 15 years. During this period, while digital health professions have been thriving in the industry to deliver tools and technologies, academic institutions have offered some amount of training and education in digital health; however, the career pathway for digital health professionals is not clear due to mismatch about the qualifications, skills, competencies and experience needed by the healthcare industry. OBJECTIVES: Due to this discrepancy between the academic curriculum and the skills needed in the healthcare industry, the objectives of this study are to define the career pathway for eHealth professions and identify the challenges experienced by academic institutions and the industry in describing digital health professionals. METHODS: We elicited qualitative data by conducting six focus groups with individuals from different professional backgrounds, including healthcare workers, information managers, computer sciences professionals, and workers in the revenue cycle who participated in a workshop on November 2-3, 2019, in Dubai. All focus group sessions were audio-recorded and transcribed, and participants were de-identified before analysis. An exploratory method was used to identify themes and subthemes. Saturation was reached when similar responses were found during the analysis. In this study, we found that respondents clearly defined eHealth career pathways based on criteria that included qualifications, experience, job scope, and competency. We also explored the challenges that the respondents encountered, including differences in the required skill sets and training and the need to standardize the academic curriculum across the GCC region, to recognize the various career pathways, and to develop local training programs. Additionally, country-specific projects have been initiated, such as the competency-based Digital Health framework, which was developed by the Saudi Commission of Healthcare Specialties (SCFHS) in 2018. Competency-based digital health frameworks generally include relevant job definitions, roles, and recommended competencies. Both the GCC taskforce and the Saudi studies capitalized on previous efforts by professional organizations, including Canada's Digital Health formerly known as (COACH), the U.S. Office of the National Coordinator for Health Information Technology (ONC), the American Medical Informatics Association (AMIA), and the Health Information and Management Systems Society (HIMSS). RESULTS: In this study, we found that respondents defined eHealth career pathways based on different criteria such as: qualifications; various background of health and IT in the HI field; work experiences; job scope and competency. We also further explore the challenges that the respondents encountered which delineates four key aspects such as need of hybrid skills to manage the digital transformation, need of standardization of academic curriculum across GCC, recognition of the career pathways by the industry in order to open up career opportunity and career advancement, and availability of local training programs for up-skilling the current health workforce. CONCLUSION: We believe that successful health digital transformation is not limited to technology advancement but requires an adaptive change in: the related competency-based frameworks, the organisation of work and career paths for eHealth professionals, and the development of educational programmes and joint degrees to equip clinicians with understanding of technology, and informaticians with understanding of healthcare. We anticipate that this work will be expanded and adopted by relevant professional and scientific bodies in the 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 distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,010
score de la tête « metaresearch » (Gemma)0,002
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,401
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0100,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,002
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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.

Tête enseignante Opus0,113
Tête enseignante GPT0,432
Écart entre enseignants0,319 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations16
Publié2022
Routes d'admission1
Résumé présentoui

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