A Qualitative Exploration of the Adoption of Big Data Analytics Applications in Healthcare: Insights from Saudi Hospitals

Abstract

The emergence of big data analytics (BDA) has introduced innovative solutions to disease prediction and diagnosis, personalised medicine, and hospital management. These advancements have offered opportunities for healthcare organisations to address the sector's pressing demands to reduce cost, improve care quality, and enhance accessibility to healthcare services. The aim of this study is to uncover the factors influencing the adoption of BDA applications in hospitals, promoting a better understanding of BDA adoption within the sector. This research also aims to explore how BDA solutions are being adopted in practice. To address these aims, this investigation followed a qualitative multiple-case study approach. The study investigated five large public hospitals in Saudi Arabia with differing levels of BDA adoption. Data sources included semi-structured interviews, documents, and memos, with interviews serving as the primary research method. A total of 36 interviews were conducted with employees involved in the adoption process. The findings suggest that BDA adoption in hospitals is shaped by a complex interplay of technological, organisational, environmental (TOE), and processual factors. Technological enablers such as data quality, data availability, compatibility, infrastructure, expertise, and trust in BDA applications create a foundation for BDA adoption and their absence results in major barriers. While organisational needs such as healthcare service types, patient volume and internal pressures act as drivers, BDA literacy, business-IT alignment, and decision-making culture are essential enablers for BDA adoption. Similarly, dynamic environments, competition, and changes in medical practices are external drivers for BDA solutions, whereas regulations and vendor support emerged as enablers. The study reveals that a well-defined adoption process and stakeholder consensus facilitate the adoption. Challenges to BDA adoption include resistance to change, vendor lock-in, ethical concerns, and public sector-specific issues such as decision-making dependencies and funding mechanisms. The study also reveals that advanced analytical solutions in hospitals are often adopted as objective-specific projects driven by localised needs and priorities. This sheds light on the role of BDA beneficiaries in the adoption process and the unique challenges to BDA adoption. This study contributes to both theory and practice. Theoretically, it contributes to the information systems (ISs) innovation adoption literature by advancing the understanding of the drivers, enablers, and barriers impacting BDA adoption in hospitals, particularly in public hospitals in Saudi Arabia. In addition to the well-established dimensions of the TOE framework, the study suggests the relevance of a processual dimension in shaping adoption outcomes. This dimension emphasises how aspects of the adoption process itself can influence the adoption. The study also provides insights into how BDA solutions are adopted, further emphasising the importance of understanding the adoption process of emerging technologies in IS adoption research. Practically, the study offers actionable recommendations for hospitals to overcome adoption barriers, improve organisational readiness, and support the effective integration of BDA technologies. It also provides valuable insights for policymakers, IS vendors, and professional bodies by highlighting the need for detailed regulatory frameworks for BDA applications in healthcare, improved vendor practices, and targeted awareness initiatives that promote responsible and ethical BDA adoption in healthcare.