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Successful Management of IT Projects in Healthcare Institutions after COVID-19: Role of Digital Orientation and Innovation Adaption.

Roxana Elena ȚucmeanuAlin Iulian TucmeanuMădălina-Gabriela IliescuJustyna ŻywiołekZahid Yousaf
Published in: Healthcare (Basel, Switzerland) (2022)
This research aims to examine specific issues that how healthcare institutions successfully manage IT projects after the deadly disease of COVID-19. The world's healthcare institute changed its traditional way of treatment to IT-based equipment after COVID-19. Hence, this study investigated the how digital orientation helps healthcare institutes for successful management of IT. Our study identifies the critical role of digital orientation and innovation adaption in the successful management of IT. The mediating role of innovation adaption in the association between digital orientation and successful management of IT was also investigated. In total, 456 questionnaires were used for the collection of data from eight different healthcare centers. We selected participants through random sampling. Findings on the healthcare institution showed that successful management of IT is predicted through digital orientation. This study's results proved that digital orientation impacts innovation adaption, and similarly, innovation adaption influences the successful management of IT. The outcomes show the mediating role of innovation adaption in the linkage between digital orientation and successful management of IT. Current research contributes to the existing literature through combined impacts of the digital orientation, innovation adaption, and successful management of IT through means of demonstrating how, when, and why digital orientation supports the successful management of IT. Moreover, innovation adaption performs a significant role in the extant digitalize world; thus, we chose innovation adaption as a mediator in this study.
Keyphrases
  • healthcare
  • sars cov
  • coronavirus disease
  • gene expression
  • systematic review
  • type diabetes
  • machine learning
  • mass spectrometry
  • health information
  • hepatitis c virus
  • hiv infected