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

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

Cache Performance Optimizations for Parallel Lattice Boltzmann Codes

When designing and implementing highly ecient scienti c applications for parallel computers such as clusters of workstations, it is inevitable to consider and to optimize the single{CPU performance of the codes. For this purpose, it is particularly important that the codes respect the hierarchical memory designs that computer architects employ in order to hide the eects of the growing gap between CPU performance and main memory speed. In this paper, we present techniques to enhance the single{CPU eciency of lattice Boltzmann methods which are commonly used in computational uid dynamics. We show various performance results to emphasize the eectiveness of our optimization techniques