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Digital transformation in healthcare: Assessing the role of digital technologies for managerial support processes.

Authors :
Mauro, Marianna
Noto, Guido
Prenestini, Anna
Sarto, Fabrizia
Source :
Technological Forecasting & Social Change; Dec2024, Vol. 209, pN.PAG-N.PAG, 1p
Publication Year :
2024

Abstract

This study used Porter's value chain model within healthcare organizations and the technology–organization–environment framework to explore the impact of digital technologies on managerial and administrative support processes and identify the determinants of their adoption. We used the Delphi methodology to examine six categories of digital technologies (Internet of Things, artificial intelligence & machine learning, big data & business analytics, cloud storage & computing, social media, and blockchain). The study used an inductive qualitative approach involving 11 experts to gather opinions on the most impactful digital technologies and the factors that hinder or limit digital transformation. We found that the Internet of Things and artificial intelligence & machine learning have the most significant impact on administrative support processes in healthcare organizations. Blockchain was least relevant. The experts identified the skills and competencies of employees as the most crucial determinants for ensuring successful digital transformation. These results contribute to the literature on digital transformation in healthcare, which has previously mainly focused on the impact of technologies on clinical processes. The findings may also be useful to both policymakers and practitioners in determining priorities for investment in digital technologies and delivering successful implementation. • Technologies deeply impact on Porter's value chain managerial processes in healthcare. • Internet of Things and Artificial Intelligence have the most significant impact. • Blockchain is found to be less relevant in healthcare. • Employees' skills and competencies are crucial determinants for digital transformation. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00401625
Volume :
209
Database :
Supplemental Index
Journal :
Technological Forecasting & Social Change
Publication Type :
Academic Journal
Accession number :
180929969
Full Text :
https://doi.org/10.1016/j.techfore.2024.123781