Data-driven technologies for global healthcare practices and COVID-19: opportunities and challenges

Nnamdi Ogbuke, Yahaya Y. Yusuf, Angappa Gunasekaran, Nora Colton, Dharma Kovvuri

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


This paper discusses the applications of data-driven technologies in managing healthcare data services and information systems, as well as how they stimulate innovations to bring major improvements in the industry. The study explores the novel applications of digital technologies such as Big Data, AI, 3D Printing, and Blockchain and the most challenging parts of data security, privacy, and interoperability in healthcare organisations. Whilst the number of articles on this subject have been steadily increasing owing to the sweeping health crisis of COVID-19 Pandemic, there is absence of systematic literature review that comprehensively explored the existing and potential applications of these digital data-driven innovations in response to the pandemic, and in handling healthcare data services. The review outlined six principal facets namely: hospitals practices, clinical services, patients’ home, nursing homes, rural areas, and anywhere, which provided the useful insights and the journey involved in the emergence of data-driven technologies for healthcare Practices. These facets are built across the multiple levels and unique conceptual standpoints indicated by 10 sub-themes. These themes were generated based on 77 articles (2010–2022) drawn from 40 leading Journals. Overall, there is a considerable consensus across current literature that digital data-driven technologies extend far beyond mitigating the significant impacts of coronavirus on healthcare industry. They have the potential to support and provide more responsive digital solutions to the data management crises that industry has been characterised, such as high demands of rising aging populations with chronic diseases, child mortality and potential impacts of pandemics.

Original languageEnglish (US)
JournalAnnals of Operations Research
StateAccepted/In press - 2023

All Science Journal Classification (ASJC) codes

  • Decision Sciences(all)
  • Management Science and Operations Research

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