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.
|Title of host publication||Proceedings of the 7th International Symposium on Data-Driven Process Discovery and Analysis (SIMPDA 2017)|
|Editors||Paolo Ceravolo, Maurice van Keulen, Kilian Stoffel|
|Publication status||Published - Dec 2017|
|Event||7th IFIP WG 2.6 International Symposium on Data-Driven Process Discovery and Analysis, SIMPDA 2017 - Neuchatel, Switzerland|
Duration: 6 Dec 2017 → 8 Dec 2017
Conference number: 7
|Name||CEUR Workshop Proceedings|
|Conference||7th IFIP WG 2.6 International Symposium on Data-Driven Process Discovery and Analysis, SIMPDA 2017|
|Period||6/12/17 → 8/12/17|
- Natural language processing
- Electronic patient record
- Machine learning
- Care processes
Van Keulen, M., Geerdink, J., Linssen, G. C. M., Slart, R. H. J. A., & Vijlbrief, O. (2017). Exploiting Natural Language Processing for Improving Health Processes. In P. Ceravolo, M. van Keulen, & K. Stoffel (Eds.), Proceedings of the 7th International Symposium on Data-Driven Process Discovery and Analysis (SIMPDA 2017) (pp. 145-146). (CEUR Workshop Proceedings; Vol. 2016). CEUR.