Exploiting Natural Language Processing for Improving Health Processes

In the medical world, high quality digital registration in an Electronic Patient Dossier (EPD) of symptoms, diagnoses, treatments, test results, images, interpretations, and outcomes becomes commonplace. Together with a shortage of medical professionals, means that they experience pressure at the expense of actual ‘hands on the bed’. On the other hand, EPDs contain a wealth of largely unused, unstructured textual information. Clinicians primarily communicate with each other through letters and reports. Our main question is: Can Natural Language 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.