Leveraging Big Data Analytics to Improve Quality of Care in Healthcare Organizations: A Configurational Perspective

Abstract

Big data analytics (BDA) is beneficial for organizations, yet implementing BDA to leverage profitability is fundamental challenge confronting practitioners. Although prior research has explored the impact that BDA has on business growth, there is a lack of research that explains the full complexity of BDA implementations. Examination of how and under what conditions BDA achieves organizational performance from a holistic perspective is absent from the existing literature. Extending the theoretical perspective from the traditional views (e.g. resource‐based theory) to configuration theory, the authors have developed a conceptual model of BDA success that aims to investigate how BDA capabilities interact with complementary organizational resources and organizational capabilities in multiple configuration solutions leading to higher quality of care in healthcare organizations. To test this model, the authors use fuzzy‐set qualitative comparative analysis to analyse multi‐source data acquired from a survey and databases maintained by the Centres for Medicare & Medicaid Services. The findings suggest that BDA, when given alone, is not sufficient in achieving the outcome, but is a synergy effect in which BDA capabilities and analytical personnel's skills together with organizational resources and capabilities as supportive role can improve average excess readmission rates and patient satisfaction in healthcare organizations.

Big Data and Performance: What Can Management Research Tell us?

“…(2019) and Wang et al . () attempt to answer the key question as to whether there are additional theoretical perspectives that can be used to better understand the relationship between Big Data and performance. Dubey et al .…”

“…Wang et al . () use the configuration theory to develop a model showing how BDA capabilities interact with organizational resources. They use fuzzyset qualitative comparative analysis to test their hypothesis in the context of Medicare and Medicaid Services.…”

“…Finally, Dubey et al (2019) and Wang et al (2019) attempt to answer the key question as to whether there are additional theoretical perspectives that can be used to better understand the relationship between Big Data and performance. Dubey et al (2019) attempt to integrate three theoretical perspectives, namely institutional theory, the resource-based view and Big Data culture in developing and testing a model examining the influence of Big Data predictive analytics on manufacturing performance.…”

“…Taking an institutional view, the authors further argue that interorganizational pressure is a major influence on firms' BDPA adoption decision, and they also identify Big Data culture as playing a significant moderating role that enhances the effects of tangible resources and human skills on BDPA adoption. Wang et al (2019)…”

The role of big data analytics in enabling green supply chain management: a literature review

“…Big data analytics (BDA) is the use of analytical techniques and the capacity to process large volumes and varieties of data with high velocity to generate insights for decision making (Choi et al 2018;Swaminathan 2018;Wang et al 2019). Recently, practitioners and academics have acknowledged the role of BDA in green supply chain management (GSCM) (Dubey et al 2017;Song et al 2017;Wu et al 2016), which refers to the deployment of comprehensive environmental considerations in supply chain management (Geng et al 2017b, p. 2).…”