  Big data in healthcare has made a positive difference in advancing analytical
capabilities and lowering the costs of medical care. In addition to providing
analytical capabilities on platforms supporting current and near-future AI with
machine-learning and data-mining algorithms, there is also a need for ethical
considerations mandating new ways to preserve privacy, all of which are
preconditioned by the growing body of regulations and expectations. The purpose
of this study is to improve existing clinical care by implementing a big data
platform for the Czech Republic National Health Service. Based on the achieved
performance and its compliance with mandatory guidelines, the reported big-data
platform was selected as the winning solution from the Czech Republic national
tender (Tender Id. VZ0036628, No. Z2017-035520). The platform, based on
analytical Vertica NoSQL database for massive data processing, complies with
the TPC-H1 for decision support benchmark, the European Union (EU) and the
Czech Republic requirements, well-exceeding defined system performance
thresholds. The reported artefacts and concepts are transferrable to healthcare
systems in other countries and are intended to provide personalised autonomous
assessment from big data in a cost-effective, scalable and high-performance
manner. The implemented platform allows: (1) scalability; (2) further
implementations of newly-developed machine learning algorithms for
classification and predictive analytics; (3) security improvements related to
Electronic Health Records (EHR) by using automated functions for data
encryption and decryption; and (4) the use of big data to allow strategic
planning in healthcare.
