Research line: Learning and Innovation in Resilient Systems
Phd research
Start 2022

Contact: prof. dr. Remko Helms

There is a wealth of attention for information technology (IT) adoption and IT-enabled transformation in healthcare research. However, there is still a limited understanding of big data’s role and its associated predictive models as a crucial enabler of the hospital’s 'ability to adequately 'sense' and 'respond' to patient needs and wishes. We refer to this ability as 'patient agility'.

Predictive analytics

Predictive analytics refers to the skills, practices, applications, and techniques to analyze current and historical information to predict future or even unknown events. Predictive analytics is relevant for hospitals from:

• a medical point of view:
  predictive analytics can be used to identify defects in care and risk factors for patient safety issues, occurrence patterns, and statistical testing of intervention strategies, evidence-based medicine / comparative effectiveness, and analyses to measure the impact of using clinically substitutable supply items on patient outcomes.
• a managerial point of view:
  predictive analytics can be used to determine the time required to perform key patient care activities (e.g., passing medication) and to coordinate (and exchange) capacity within and between hospitals (or with other care providers, e.g., general practitioners).

Framework and case studies

The project will develop a conceptual framework for predictive analytics to foster a hospital’s patient agility. The framework will be applied at various hospitals. Data will be collected through surveys and case studies. The case studies are focused on:

• predicting patient flow at the emergency department and the impact on the triage of patients
• discharging patients that recover from illness to home from the intensive care unit
• monitoring patients at home and applying predictive analytcs in for example signaling possible complications.

Team

Faculty of Sciences: prof. dr. ir. Remko Helms (promotor), dr. Rogier van de Wetering (copromotor)
Faculty of Management: prof. dr. Nadine Roijakkers (promotor), dr. Ward Ooms (copromotor), prof. dr. ir. Daan Dohmen, prof. dr. Cornelis Boersma.

Read more

Damien S.E. Broekharst, Rogier van de Wetering, Ward Ooms, Remko W. Helms, Nadine Roijakkers, Deploying predictive analytics to enhance patient agility and patient value in hospitals: A position paper and research proposal