One cannot go anywhere these days and not hear about data analytics and big data. These concepts are becoming increasingly relevant in health care. We see applications in banking (electronic banking) and the use of customer data for a variety of purposes. In addition, the travel industry (consumer websites that will find your hotel or airline reservation and Uber), consumer products (Amazon), and Sports all use data analytics in some way. Health care has been one of the industries that has been slow to adapt information technology and data analytics.
Wearable health information technology is now ubiquitous, whether it is in the form of electronic fitness trackers, smart phone and/or watches, and other wearable devices. These devices generate data, much of which might be able to be used by providers and patients in the care of the latter, particularly in the context of the transition from fee-for-service medicine to payment for quality and cost-effectiveness. It is not only the privacy and security of these devices and their information which might keep General Counsel up at night, but also how the data is being transmitted. How are healthcare professionals using this data in the context of overall patient care?
Increasingly, healthcare systems have employed electronic health records (EHRs). These EHRs facilitate the collection of data. When coupled with clinical decision support systems (CDSS), computerized physician order entry (CPOE), and e-prescribing, considerably more patient data can be collected and used in the management of patient care. Add telemedicine, mHealth, and social media to the care delivery processes and the stage is set for the better management of care toward greater quality in a cost-effective manner. However, to accomplish these objectives, it is necessary to develop benchmarks and/or metrics from which to manage care. Doing so involves analyzing a considerable amount of data or data analytics.