Factors impacting the adoption of big data in healthcare: A systematic literature review

Abeer Saleh Al Teneiji; Taghreed Yahia Abu Salim; Zainab Riaz

doi:10.1016/j.ijmedinf.2024.105460

Factors impacting the adoption of big data in healthcare: A systematic literature review

Int J Med Inform. 2024 Apr 20:187:105460. doi: 10.1016/j.ijmedinf.2024.105460. Online ahead of print.

Authors

Abeer Saleh Al Teneiji¹, Taghreed Yahia Abu Salim², Zainab Riaz³

Affiliations

¹ College of Business Administration, Abu Dhabi University, United Arab Emirates. Electronic address: Dr.alteneiji@hotmail.com.
² College of Business Administration, Abu Dhabi University, United Arab Emirates. Electronic address: taghrid65@yahoo.com.
³ College of Business Administration, Abu Dhabi University, United Arab Emirates. Electronic address: zainab.riaz@adu.ac.ae.

PMID: 38653062
DOI: 10.1016/j.ijmedinf.2024.105460

Abstract

Background: The term "big data" refers to the vast volume, variety, and velocity of data generated from various sources-e.g., sensors, social media, and online platforms. Big data adoption within healthcare poses an intriguing possibility for improving patients' health, increasing operational efficiency, and enabling data-driven decision-making. Despite considerable interest in the adoption of big data in healthcare, empirical research assessing the factors impacting the adoption process is lacking. Therefore, this review aimed to investigate the literature using a systematic approach to explore the factors that affect big data adoption in healthcare.

Methods: A systematic literature review was conducted. The methodical and thorough process of discovering, assessing, and synthesizing relevant studies provided a full review of the available data. Several databases were used for the information search. Most of the articles retrieved from the search came from popular medical research databases, such as Scopus, Taylor & Francis, ScienceDirect, Emerald Insights, PubMed, Springer, IEEE, MDPI, Google Scholar, ProQuest Central, ProQuest Public Health Database, and MEDLINE.

Results and conclusion: The results of the systematic literature review indicated that several theoretical frameworks (including the technology acceptance model; the technology, organization, and environment framework; the interactive communication technology adoption model; diffusion of innovation theory; dynamic capabilities theory; and the absorptive capability framework) can be used to analyze and understand technology acceptance in healthcare. It is vital to consider the safety of electronic health records during the use of big data. Furthermore, several elements were found to determine technological acceptance, including environmental, technological, organizational, political, and regulatory factors.

Keywords: Adoption; Big data; Data science; Electronic health records; Healthcare; Systematic literature review.

Publication types

Review