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

Social Rating System of the People’s Republic of China in the Cultural Aspect of the State and Society Relations

The article discusses the elements of China’s political culture and their influence on the construction of a social rating system in the PRC and the attitude of the Chinese people towards it.В настоящей статье рассматриваются элементы политической культуры Китая, их влияние на построение системы социального рейтинга в КНР и отношение к ней китайского народа

Explaining Query Answer Completeness and Correctness with Partition Patterns

International audienceInformation incompleteness is a major data quality issue which is amplified by the increasing amount of data collected from unreliable sources. Assessing the completeness of data is crucial for determining the quality of the data itself, but also for verifying the validity of query answers over incomplete data. In this article, we tackle the issue of efficiently describing and inferring knowledge about data completeness w.r.t. to a complete reference data set and study the use of a partition pattern algebra for summarizing the completeness and validity of query answers. We describe an implementation and experiments with a real-world dataset to validate the effectiveness and the efficiency of our approach

Design of ETL Process on Spatio-temporal Data and Study of Quality Control

International audienceIn order to use the space-time data mining technology to conduct operation research in WuLiangSuHai Eutrophication, the water quality sensor parameters of heterogeneous data which reflect the characteristics should set up a spatial data warehouse through ETL process, and water quality sensors for quality control of spatial and temporal data plays a vital role in building an effective analytical environment. The paper designs the ETL process from the data and water quality sensors artificial duty and other heterogeneous data sources spatial data, and proposes data quality control strategy based on the incremental frequency rule engine and the space the inverse distance weighting on the Combination. Experiments show that the incremental frequency rule engine could more effectively find the missing sensor data and abnormal, Space inverse distance weighting method can find the missing data and outliers in the errors within the allowed interpolation processing, ETL procedure is effective and feasible