Digital Health
Welcome to our Digital Health Research Programme, where we are dedicated to transforming and democratising healthcare through a more holistic and comprehensive approach to individual health and wellbeing. Our goal is to lead the way in developing personalised, accessible, proactive, and preventive healthcare solutions, enabled by digital technologies, and specifically tailored for those impacted by neurological and neuropsychiatric diseases. Leveraging our diverse data-driven environment, we aim to rapidly translate scientific insights into practical applications, advancing healthcare, streamlining clinical decisions, and ultimately improving patient outcomes. Additionally, we foster collaboration to innovate and co-create digital solutions that empower self-care and enhance the patient-clinician relationship.
Our Grand Challenges are
- Expanding the co-creation of electronic health records and patient registries based on best-in-class data governance practices.
- Advancing a learning health system that integrates clinical practice and scientific knowledge to enable a continuous cycle of data-driven improvement in healthcare.
- Forging sustainable and ethical pathways for linking electronic health records, patient portals, patient registries, and connected health devices.
- Building trust and transparency around the use of health data and digital technologies.
- Harnessing the potential of big data and artificial intelligence (AI) to yield new knowledge from health data and improve patient outcomes.
- Pioneering digital therapeutic interventions in the area of mental health to refine risk identification and guide the delivery of future care with greater precision.
Overview of the Digital Health Research Programme
View Transcript
ShowOur research program lays the groundwork for a learning health system that actively involves healthcare professionals, individuals living with neurological and neuropsychiatric diseases, and their families. Through four research themes, we aim to uncover new insights from data collected during clinical encounters as well as person-generated data obtained through connected devices in home environments. These insights will be translated into actionable practices to promote proactive and personalised healthcare.
Specifically, we will establish ethical pathways toward the linkage of different types of data, address socio-technical considerations in a data-driven environment, develop responsible AI solutions to support clinical-decision making and create a digital therapeutic for early intervention in mental health.
Collaborating with our industry partners, we will investigate attitudes and trust surrounding the use of AI solutions in addition to identifying novel digital biomarkers for predicting or monitoring disease progression. We will scale our patient registries and incorporate patient-reported outcome measures to enhance our understanding and management of neurological and neuropsychiatric conditions.
Our Digital Health research is distinguished by
- An epilepsy Electronic Patient Record (EPR) supporting a National Network of Care, managing over 10,000 longitudinal records.
- The world’s longest-running ALS register containing patient and care-giver data, with growing registries in MS, adult & paediatric epilepsy.
- Mobile technology, via the Neureka app (>12k users), facilitating citizen science to create a clearer picture of what keeps the brain healthy.
- Interdisciplinary collaborations drawing on diverse perspectives and expertise including patients, care partners, patient organisations, health care professionals, software engineers, data scientists and ethicists.
- Expertise in human-centred design, business analysis and implementation science.
- Growing emphasis on digital therapeutics and the role of AI/ML and robust data analytics to enhance the patient journey.
- An applied ethics approach integrated into the co-design of digital health technologies, ensuring responsible use and societal benefit.
Seamless data linkage and integration
Here, we aim to harmonise and link siloed data sources, empowering clinicians and researchers to discover new insights and tailor clinical-decisions and disease management.
A learning health system 2.0
Here, we lay down the foundations for a learning health system (LHS) whereby data-driven knowledge is embedded into clinical practice, fostering cycles of continuous learning and enhanced patient outcomes.
Seamless data linkage and integration
Here, we aim to harmonise and link siloed data sources, empowering clinicians and researchers to discover new insights and tailor clinical-decisions and disease management. Starting with epilepsy, we will take a use-case approach and integrate different data points and sources based on clinician and patient needs. We will design and build an infrastructure that will allow exchange of information. From this, we will develop a standards-based interoperability roadmap that will benefit other neurological and neuropsychiatric diseases.
Research Leads
A learning health system 2.0
Here, we lay down the foundations for a learning health system (LHS) whereby data-driven knowledge is embedded into clinical practice, fostering cycles of continuous learning and enhanced patient outcomes. Through a multi-stakeholder approach, we will address ethical considerations and sociotechnical factors that influence the adoption of a LHS model in health research. Employing a collective intelligence approach, we will examine areas such as consent, privacy and secondary use of health data. Finally, we will initiate quality improvement methodology to evaluate the practical application of a LHS model.
Research Leads
Robust AI/ML applications
We will apply ethical and quality-orientated ML/AI on FutureNeuro datasets to investigate the potential for improving diagnosis, therapeutics and self-management strategies for patients. We will also explore the application of Natural Language Processing (NLP) on electronic datasets to extract crucial information, gain new clinical insights, and boost clinical efficiency.
Research Leads
Innovative digital therapeutics
We are creating a smartphone app powered by AI to intervene early in youth psychotic episodes. Adopting a user-centred-design approach, we will capture value propositions and user requirements from a variety of stakeholders. We will assess the feasibility and efficacy of this intervention. Additionally, we'll identify new digital biomarkers to pinpoint individuals at highest risk.
Research Leads
Collaborative Industry Projects
We partner with industry to leverage data and digital health to improve the diagnosis, treatment and care pathways of people living with neurological disease. Examples of recent collaborations include:
Novartis Irl
We are working together to study the interrogation of data at scale to inform improvements in individualised patient care in the clinical setting.
IQVIA
We are working together to deepen our understanding of how to build public trust and confidence in the secondary use of health data for healthcare improvement and research.
Therapeutics
Welcome to our Therapeutics research programme where our objective is to produce a new generation of disease-modifying treatments for brain diseases.
Diagnostics
The objective of the diagnostics programme is to create a stratified, research-engaged patient population to enable faster diagnosis, precision medicine and clinical trials. Our research focuses on how changes in our genes can cause, or contribute to the development of neurological disease.