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The role of big data analytics in improving the quality of healthcare services in the Italian context: The mediating role of risk management

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  • Basile, L.J.
  • Carbonara, N.
  • Panniello, U.
  • Pellegrino, R.

Abstract

Digital transformation is revolutionizing many industries and increasingly more organizations are adopting digital technologies in their processes. The adoption and integration of digital technologies are boosting the production of data that can be collected, analyzed, and exploited for decision-making through big data analytics. Data can play a significant role in healthcare since it is a complex system where every decision is affected by risk and uncertainty. This study investigates how big data analytics (BDA) enables the use of risk management (RM) practices, resulting in improving the quality of healthcare services (QoHS). It also analyses the indirect effect of BDA on the QoHS through the use of RM practices. To this aim, 204 responses from Italian healthcare professionals were collected and investigated via the lens of Organizational Information Processing Theory using PLS-SEM methodology. The results revealed that BDA contributed positively and significantly to the use of RM practices, while only the use of risk identification and monitoring practices impact healthcare service quality significantly and mediate the relationship between BDA and QoHS. The results provide managerial insights about the use of data to support the decision-making process in healthcare showing that decision-makers should focus their effort on integrating data-driven tools and capabilities with RM practices to reduce the uncertainty surrounding this environment and ensure a higher quality of healthcare services.

Suggested Citation

  • Basile, L.J. & Carbonara, N. & Panniello, U. & Pellegrino, R., 2024. "The role of big data analytics in improving the quality of healthcare services in the Italian context: The mediating role of risk management," Technovation, Elsevier, vol. 133(C).
    • Handle: RePEc:eee:techno:v:133:y:2024:i:c:s0166497224000609
    DOI: 10.1016/j.technovation.2024.103010
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