Assignment: Forecasting & Social Change
Capability profile of big data analytics in healthcare
Overall, the five generic categories of big data analytics capabilities we identified from 136 statements in our review of the cases are analyt- ical capability for patterns of care (coded as part of 43 statements), un- structured data analytical capability (32), decision support capability (23), predictive capability (21), and traceability (17). These are de- scribed in turn below.
4.1.1. Analytical capability for patterns of care Analytical capability refers to the analytical techniques typically
used in a big data analytics system to process datawith an immense vol- ume (from terabytes to exabytes), variety (from text to graph) and ve- locity (from batch to streaming) via unique data storage, management, analysis, and visualization technologies (Chen et al., 2012; Simon, 2013). Analytical capabilities in healthcare can be used to identify pat- terns of care and discover associations frommassive healthcare records, thus providing a broader view for evidence-based clinical practice. Healthcare analytical systems provide solutions that fill a growing need and allow healthcare organizations to parallel process large data volumes, manipulate real-time, or near real time data, and capture all patients’ visual data or medical records. In doing so, this analysis can identify previously unnoticed patterns in patients related to hospital readmissions and support a better balance between capacity and cost.
8 Y. Wang et al. / Technological Forecasting & Social Change 126 (2018) 3–13
Interestingly, analyzing patient preference patterns also helps hospitals to recognize the utility of participating in future clinical trials and iden- tify new potential markets.
4.1.2. Unstructured data analytical capability An analytical process in a big data analytics system starts by acquir-
ing data fromboth inside andoutside the healthcare sectors, storing it in distributed database systems, filtering it according to specific discovery criteria, and then analyzing it to integrate meaningful outcomes for the data warehouse, as shown in Fig. 2. After unstructured data has been gathered across multiple healthcare units, it is stored in a Hadoop dis- tributed file system andNoSQL database thatmaintain it until it is called up in response to users’ requests.
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