Working towards data-driven epilepsy care: Exploring NHS clinical dashboards presenting patient-generated health data (PGHD) to enhance Dr-patient com

Epilepsy is the most common neurological condition, with a prevalence of 5-10 cases per 1000. It is associated with premature death, risk of injury, reduced quality of Life, and it costs the NHS £1.5 billion p.a.

Epilepsy is challenging to diagnose and treat. Research with clinicians and PWE indicates that the types of PGHD we have been collecting through seizure forecasting technology hold the potential to enhance NHS clinical decision-making. This data could aid diagnosis (e.g. using postictal symptoms to differentiate epileptic seizure and non-epileptic seizure), aid assessment of condition progression (identify deteriorations or improvements in seizures), aid assessment of the impact of treatment plans, and aid the provision of personalised advice on lifestyle factors increasing seizure risk.

However, no research has been carried out to understand how this PGHD should be integrated into NHS workflows to aid clinical decision-making.

The aim of this PhD will be to design, prototype, and usability test a clinical dashboard for presenting PGHD data to clinicians and PWE. The aim is to design a dashboard that can be integrated into clinical workflows, that will aid doctor-patient communication and collaborative care planning, and ultimately will improve clinical outcomes. There is also potential to explore PWE, and clinicians' views on the use of predictive analytics within the clinical dashboard.

This PhD will involve human-computer interaction research. Methods will include co-design, prototyping and NHS-based mixed-methods in-the-wild usability studies.