Data Analytics in Healthcare Informatics

Abstract

In recent years, the introduction of data analytics to large amounts of healthcare data collected on daily basis opened numerous new opportunities and challenges in the field of medical informatics. By definition, healthcare informatics refers to the process of leveraging information technologies to improve the quality of healthcare. Many researchers are focusing on basic and translational research to achieve this goal by proposing novel or applying and adapting the state-of-the-art data analytics techniques to vast amounts of recently collected data. Recent adoption of Electronic Health Records (EHR) opens additional opportunities for data analytics, as we are able to access structured and unstructured data that is systematically collected for each event in the healthcare system or even contributed by the patients themselves. This tutorial covers different data analytics techniques and their translational value in improving the quality of healthcare. In the introductory part of the tutorial, we will outline the basics of data analytics in healthcare and continue with description of data representation that is specific to this field. The second part of the tutorial will present concrete state-of-the-art approaches that can be applied in healthcare informatics. Participants will gain a better understanding of risk estimation and stratification, patient similarity, privacy-preserving predictive modelling and patient-based classification. All methods presented in the tutorial have great translational value and can be implemented as a stand-alone solution or a part of health information systems. The intended audience of this tutorial are healthcare professionals and researchers from all fields of healthcare informatics. No specific knowledge will be required since the tutorial is self-contained and most fundamental concepts will be introduced during the presentation.