The impact of big data utilisation on Malaysian government Hospital performance

The Malaysian healthcare systems face incredible challenges as technology is being used more and more widely and citizens' expectations are increasing just as rapidly. Meeting costs and
improving health outcomes would also serve as obstacles. In this context, Big Data can help providers achieve these objectives in an unparalleled manner. The Healthcare industry is adopting big data in daily operations to ensure excellent performance. However, the Malaysian government hospitals remain unable to implement Big data. Besides, previous studies relating to use of big data among Malaysian government hospitals and its implication to hospital performance is
inadequate. Hence, this study examines the mediating role of use of Big data (UBD) on the relationship between hospitals performance (HP), Data quality (DQ), data integration (DI) and data governance (DG). Study framework is established from theories namely Resource Based View (RBV), extending the DeLone and Mclean IS Success Model (D&M ISSM). Data was collected from Malaysian government hospitals. Total questionnaires of 560 were distributed and 212 were responded. The convenience sampling technique was used. Hypotheses tests were performed via Smart PLS 3.9. Results show DQ and DI have significant direct relationships with the UBD. However, DG is not significant with UBD. Findings on use of big data as a mediating
variable reveal DQ and DI have significant direct relationship with UBD except DG. Findings provide important insights to Government, policy-makers and researchers to further understand the use of big data to enhance hospitals performance in Malaysia. Organisations are struggling to fulfill all their expected big data related analysis skills in the workplace. Failure to interpret the produced reports in this respect may lead to serious misjudgements and doubtful decisions. This study focused solely on the performance of Government hospitals in Malaysia. There is a need to investigate the performance of other types of hospitals and clinics (Clinicals and Specialist centers), such as private hospitals, clinics and specialist hospitals. As a result, the analysis is constrained by the fact that hospitals or treatment center characteristics vary depending on the form of facility and funding in the healthcare sector. Future research could look into hospital performance and big data technologies in other parts of the world, as well as other sector activities, which could provide more in-depth information. Besides, Future research can also explore how and why big data capacity contributes towards improvement of some IT-enabled transformation activities by means of thorough single or multiple case studies. This is especially true of the most frequent value chain, which leads to profitability from analytical capacity from concrete evidence medicine and IT infrastructure advantages.