Doctor of Philosophy
Despite the surge of big data analytics (BDA) deployments in healthcare, many organizations still struggle to successfully realize value from their investments. This has resulted in the phenomenon of BDA deployment gap, where relative to the interest and investments in BDA initiatives by the organizations, actual value generated from successful migrations of BDA models from data labs to in-practice environment deployments at the initiative level have been scarce. To leverage the growing repository of big data, organizations are required to develop the ability to collect, store, process, and analyze big data (BD); this process is referred to as big data analytics capability (BDAC) in the literature. However, the underlying assumption that organizations with BDAC will always be able to orchestrate the necessary resources and capabilities to use the information from analytics to generate value largely ignores the operational mechanisms involved in how the information is leveraged. This thesis seeks to address this gap in the literature by investigating how organizations find ways to operationally leverage BDAC to generate value in the context of healthcare and generating a better understanding of the knowledge management practices involved in transforming the information from analytics into BDA-enabled capabilities that can lead to improved operational and clinical outcomes.
This thesis includes three components. First, the constructs involved in the value generation process from BDAC in the general context are identified: BDA resources, BDAC, and value. Second, a systematic literature review (SLR) is conducted to develop the conceptual framework in the healthcare context and identify the possible constituents of the mediating ‘black box’, which serve as the operational mechanisms in the leveraging process of BDAC in generating value. Finally, a multiple case study is presented to empirically validate the presence and explicate the workings of the ‘black box’ presented in the indirect value generation pathway framework via BDA-enabled functioning capability (BDA-eFC), a dual-purpose capability. The study further supplements the BDAC literature by offering a nuanced understanding of the underlying mechanisms of how organizations implement BDA in the healthcare delivery process at a functional level to generate value, and address the BDA deployment gap in the healthcare context.
Summary for Lay Audience
With the digitization of healthcare, various healthcare organizations have been investing in ways to use the large volumes of data generated (e.g., electronic health records) to improve the quality of care, patient experience, and overall cost of care. The large volumes of data, often referred to as big data (BD), have been predicted to deliver on the promise of immense benefits for healthcare organizations through the use big data analytics (BDA), which can provide unprecedented ways to gain insights for decision-making that were not possible by the traditional methods in healthcare. In the pursuit of these promises, healthcare organizations invest considerable resources towards developing BDA capability (BDAC) and deploy various BDA initiatives; however, many organizations fail to successfully realize the intended value from the deployments. Often, the healthcare organizations are left with plenty of information that can be used; however, the information needs to be further leveraged to actually inform decisions and actions. The existing research in the context of healthcare offers limited understanding on the leveraging mechanisms involved in transforming the information from BDA into insights and knowledge that enables improved work efforts in the care delivery process, which ultimately leads to value.
This thesis seeks to address this gap through an examination of healthcare organizations that have deployed various BDA applications and possess BDAC to better understand how these organizations leverage the information generated from BDA to inform their decisions and actions to change care practices and improve healthcare delivery services. As a result, this research finds consistent patterns of BDA-enabled routines and practices that help facilitate the effective leveraging of information outputs from BDA in the value generation process in healthcare. It also highlights the importance of these leveraging mechanisms in linking the healthcare organizations’ BDAC with ways to improve or innovate the operational processes involved in the delivery of care.
Shin, Hyunmin (Dan), "Understanding the Big Data Analytics Deployment Gap: Operationally Leveraging Big Data Analytics Capability for Value Generation in Healthcare" (2023). Electronic Thesis and Dissertation Repository. 9466.