Hospitals needs to make efficient use of beds and healthcare professionals in order to provide optimal care for patients while using the available budget efficiently. Therefore, hospitals aim to hospitalize patients if necessary and discharge patients when possible, i.e. patients requiring care should receive this at the appropriate level and those patients no longer in need of hospital care should be discharged. However, triaging patients and discharge management is not straightforward and wrong decisions may lead to suboptimal care. As a PhD, you will focus on aiding these decisions by using a large amount of digital information obtained from medical records, (wearable) sensors and from patients themselves.

In this role, you have the opportunity to develop new Artificial Intelligence (AI) based models to predict which patients can be discharged without compromising the patient’s safety. You will develop AI models to predict 1) patient deterioration, and 2) hospital discharge. The effects of these predictions on e.g. length of hospital stay, quality of care, rehospitalisation rate, and on healthcare professionals and patient satisfaction will be measured. Furthermore, the impact on logistical and financial outcomes will be assessed. You will use and extend your knowledge of machine learning and signal processing for physiological monitoring.

You are responsible for:

• designing study protocols, collecting data, and study logistics in a multidisciplinary team,
• understanding the clinical workflow, care paths of patients,
• developing new models to predict patient deterioration and hospital discharge,
• analyzing data obtained from different sources,
• writing scientific articles for peer reviewed international journals and reports for colleagues and management,
• presenting results for an (inter-)national audience at conferences,
• being the cornerstone in the collaboration between Rijnstate hospital, Philips and the University of Twente concerning prediction models.

You will be part of a collaboration between Rijnstate hospital Arnhem, University of Twente Enschede and Philips Research Eindhoven, combining the clinical, academic and industrial view. You will work together closely with a more clinically oriented PhD student. You will get a contract at Rijnstate hospital, and will be stationed primarily in Arnhem and Eindhoven.

We are looking for a highly motivated, enthusiastic and curiosity-drive researcher with:

• A Master's degree in Data Science, Computing Science or Mathematics, or related disciplines with excellent grades or are about to get such a degree.
• Excellent knowledge of artificial intelligence and machine learning, preferably in the analysis of time series.
• Knowledge of, or affinity with, patient monitoring and clinical practice.
• Solid programming skills (e.g., in R, Python, Matlab or C++).
• Good communication and organization skills, who enjoys working in multidisciplinary teams.
• An excellent command of the Dutch Language (vital to perform research in the Dutch care settings) and of the English language (writing and presenting).
• and who is flexible in travelling between Arnhem, Eindhoven and Enschede.

Fixed-term contract: 4 years.

We offer an appointment as PhD candidate (1,0 FTE) for 4 years. Starting salary in FWG 50, 2526,- euro, in accordance to the CAO Ziekenhuizen, analog with the UMC-CAO scale 10A. In addition, Rijnstate Hospital offers additional attractive employment conditions.

• Holiday and end-of-year bonus 8.33%.
• Flexeuro arrangement. This allows you, among other things, to use part of your salary, year-end bonus and / or holiday pay in a tax-attractive way for a higher travel allowance or, for example, financing study costs.
• Excellent pension arrangement at Pensioenfonds Zorg & Welzijn (PFZW), of which Rijnstate pays half of the remittance.

Rijnstate

Rijnstate is one of the major top clinical hospitals in the Netherlands with a leading ambition in science and innovation. By conducting scientific research in order to achieve better diagnostic and treatment methods and continuously innovating care, Rijnstate takes patient care to a higher level. Every year approximately 200 scientific studies and innovation projects start in Rijnstate.  

Health Technology and Services Research, University of Twente
At Health Technology and Services Research (HTSR, https://www.utwente.nl/en/bms/htsr/), expertise in clinical epidemiology, health technology assessment, behavioral research and data science is combined to support decisions on process and innovation development, evaluation and implementation, based on (clinical) effectiveness. HTSR research aims to evaluate the impact of new health technologies to optimise healthcare: the effects of innovations (including innovative technology and processes) on clinical and health outcomes, quality and safety of healthcare, delivery of health services and associated healthcare. HTSR is located in the Technical Medical Centre (TechMed centre), a leading Innovation Hub equipped with state-of-the-art infrastructure, ranging from research labs, preclinical testbeds and simulated hospital environments, aiming to improving healthcare by personalized technology (https://www.utwente.nl/en/techmed/).

Philips
Philips Research is the source of many advanced developments in Healthcare, Lifestyle and Technology. Building on 100 years of experience in industrial research and our world-leading patent position, we are dedicated to bringing meaningful innovations that improve people's lives. We provide technology options for innovations in the area of health and well-being, targeted at both developed and emerging markets. Positioned at the front-end of the innovation process, we work on everything from spotting trends and ideation to proof of concept and first-of-a-kind product development. For more insights you can visit: www.research.philips.com.
The Patient Care & Monitoring department (High Tech Campus in Eindhoven, the Netherlands) comprises 40 highly skilled professionals. The focus of the group is to provide clinically relevant and business-compatible solutions for high- and low-acuity care settings, comprising vital signs monitoring, data-driven connected systems, all the way up to enabling services. At the heart of our capabilities lies an interdisciplinary mix of human physiology, electronic/systems design, IT architecture and clinical workflow, which are being leveraged to develop integrated propositions from idea to concept and up to transfer in one of our business units. We work, already at a very early stage, with our key businesses and leverage our strong academic and clinical network. The department is involved in early technology scouting up to first-of-a-kind product development for acute and transitional care settings. For a significant part of the time, the successful candidate will execute his/her work at the department, where he/she is co-supervised and integrated in a team focusing on remote patient monitoring.