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Completed RESEARCH GRANT UKRI Gateway to Research

Leveraging digital phenotyping to monitor and support patients with vision loss beyond the clinic

£494.8K GBP

Funder Industrial Strategy Challenge Fund
Recipient Organization University College London
Country United Kingdom
Start Date Aug 31, 2021
End Date Oct 31, 2022
Duration 426 days
Number of Grantees 1
Roles Principal Investigator
Data Source UKRI Gateway to Research
Grant ID ES/W006510/1
Grant Description

Glaucoma is a chronic progressive ophthalmic disease causing non-recoverable loss of vision. Age is a major risk factor, affecting ~3.3% of those over the age of 70 in the UK. The number of people diagnosed with glaucoma is projected to rise dramatically over the next decade.

For example, by 2035 there will be 8.9 million people aged over 75 in the UK, an increase of 80% compared to 2010. Epidemiological modelling predicts the number of people with glaucoma in the UK will grow by 44% by 2035. The rising glaucoma caseload creates a landscape filled with complex challenges for the hospital eye service.

The problem is illustrated by national statistics that consistently identify ophthalmology as the busiest outpatient service in the NHS, with over 7.9 million hospital attendances in England in 2019-2020.

Preserving visual function in people with glaucoma requires a targeted approach, enabled by digital innovation. Technological advances now allow some populations to be monitored remotely using home-based or wearable equipment. Home monitoring is an attractive prospect for a number of reasons, particularly if clinically useful data can be captured to allow earlier detection of disease progression.

The general focus of research in this area has been directed at creating home-based versions of tests that would usually take place in clinic, such as laptop-based visual field testing. Evidence surrounding glaucoma home monitoring is promising, however this strategy does little to reflect the 'real-world' impact of glaucoma, and the clinical practicality of this approach remains to be seen.

An alternative strategy for offsetting the glaucoma burden is to monitor patterns in patients' day-to-day activities using routinely gathered patient-generated data. For example, smartphone devices and wearables exert a transformative power by creating opportunity for collection of valuable health information, enabling informed clinical decision-making and better patient outcomes.

Digital phenotyping is an emerging concept in the digital health sphere. It is defined as the moment-by-moment quantification of the individual-level human phenotype, using personal digital devices. In this approach, patients download and launch a smartphone application that collects both active data (e.g. surveys) and passive data (e.g. global positioning system [GPS] data).

Care providers can track changes in parameters for monitoring purposes, moving beyond predominantly curative responsibilities and engaging in proactive, predictive and preventive action. To date, digital phenotyping has primarily been applied within the psychiatry sector to monitor depressive symptoms. Yet, digital phenotyping could be a source of significant clinical utility for monitoring people with vision impairment.

Digital phenotyping offers a route to innovation by leveraging technology to measure and monitor the real-world impact of glaucoma. In order to stimulate this change in how patient outcomes are reviewed, there is a need to generate evidence to determine the viability of this approach. The proposed project will be a feasibility and acceptability study investigating the potential for using digital phenotyping in glaucoma care.

A mixed methods approach will be used to help clarify what parameters will be useful to measure (e.g. mobility) and how well digital phenotyping is received by the target population. Research questions will be surrounding aspects such as willingness of participants to engage with digital phenotyping, adherence/compliance, availability and usefulness of the data, and qualitative feedback on user experience.

All Grantees

University College London

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