Exploiting Natural Language Processing for Improving Health Processes
Maurice van Keulen, Jeroen Geerdink, Gerard C.M. Linssen, Riemer H. J. A. Slart, Onno Vijlbrief · University of Twente Research Information · 2017
In the medical world, high quality digital registration in an Electronic Patient Dossier (EPD) of symptoms, diagnoses, treatments, test results, images, inter- pretations, and outcomes becomes commonplace. Together with a shortage of medical professionals, means that they experience pressure at the expense of ac- tual ‘hands on the bed’. On the other hand, EPDs contain a wealth of largely un- used, unstructured textual information. Clinicians primarily communicate with each other through letters and reports. Our main question is: Can Natural Lan- guage Processing (NLP) exploit this wealth? By extracting structured data and using it as features for machine learning, a wide variety of process improvements become possible. Furthermore, it may contribute to the desire of government and health stakeholders to simplify registration and relieve pressure. This paper sketches a few prominent process improvements that we plan to research.