Big Data and Patient Safety

Abstract

The advent of big data promises to revolutionize healthcare and lead to improved and streamlined healthcare processes and improved outcomes. Driving the move to big data in healthcare is the concomitant deployment of health information technologies worldwide. These systems have been shown to improve safety of healthcare by providing automated advice and alerts and by allowing for integration of a wide array of patient and health data held in databases (Shortliffe and Cimino in Biomedical informatics. Springer, New York, 2006 [1]). However, as in other domains where technology has advanced, the potential for inadvertent error to arise as a result of technology use has also increased (Kushniruk et al. in International journal of medical informatics 74(7–8):519–526, 2005 [5]). In order to ensure the quality and safety of healthcare, databases are being developed globally to allow for reporting of a new type of error, known as technology-induced error (Palojoki et al. in Health informatics journal 23(2): 134–145, 2017 [3]; Kushniruk et al. in International journal of medical informatics 74(7–8):519–526, 2005 [5]). Current approaches to collecting and analyzing this type of error are discussed, including the development of national databases of usability and safety information. In addition to this, the potential for automated analysis and detection of error contained in big data are also explored in the context of patient safety and quality of healthcare data.