Every year, more than 40,000 patients are admitted to the St. Antonius hospital, of which 6,000 patients go home through Care Mediation with home care or to a nursing or care home. At the moment, patients who go to a nursing/care home sometimes spend too long in the hospital because there is no place available yet at a aftercare institution. By indicating the desired capacity in advance at the various aftercare institutions, St. Antonius wants to shorten the unnecessary hospital stay. In this way we try to improve the flow (inflow-flow-outflow) in the hospital.
The candidate is expected to research and develop Process and Data Analytics methods to identify which factors in the process lead to a certain outcome and how early a prediction should be done to provide a certain confidence level and still be useful. He/she develops novel tools & techniques:
- Develop and validate a prediction model that predicts patients remaining length of stay and after-care needs based on the St. Antonius data.
- To identify in which point in time the outcome prediction can have the biggest gain.
- To define a methodology to identify the contributing factors to a certain prediction.
The project is performed within the Process Analytics cluster under the supervision of Dr. Renata Medeiros de Carvalho and Prof.dr. Boudewijn van Dongen. This position is part of a collaboration between the TU/e and the St. Antonius Hospital. The project brings together scientific scholars from Process Analytics (TU/e) and the AI-team from the St. Antonius Hospital which are an essential combination to address the challenges posed.
The Process Analytics research group (https://pa.win.tue.nl/) focusses on the interplay between processes, the data these processes generate, the models that are used to describe them, and the systems that support these processes.
The AI-team (3 FTE) from the St. Antonius Hospital is an innovative team that is part of the Business Intelligence department (35 colleagues). The team has specific knowhow on the development and implementation of data science and artificial intelligence solutions in the hospital.