Data Use Application 008
Lead applicant organisation name
Name of the legal entity that signs the contract to access the data.
University of Birmingham (UoB). Applicant: Simon Baldwin, Research student PhD
Project title
The title of the project/research study request that the applicant is investigating through the use of health data.
Components of Variability in Retinal Nerve Fibre Layer Thickness Measures from Ophthalmic Image Segmentation of Optical Coherence Tomography Scans on the Optic Nerve Head: A Retrospective Longitudinal Study on Repeated Measures Data Collected as Part of Routine Care on People with Ocular Hypertension Receiving Monitoring over Time at an NHS England Trust.
Lay summary
A concise and clear description of the project. This should outline the problem, objective and the expected outcomes in language that is understandable to the general public.
Glaucoma, a leading cause of blindness, damages the optic nerve without warning. Early ocular hypertension diagnosis (OH), a glaucoma precursor, is essential to reduce risk of sight-loss.
Ophthalmic examinations are an important part of early stage OH diagnosis, but the reliability of eye tests may impact disease identification and monitoring, potentially leading to treatment and intervention delays, and accelerated vision loss.
Retinal nerve fibre layer thickness measures (RNFL) form part of the examination process. RNFL measures are calculated from optical coherence tomography (OCT) scans on the optic nerve head (ONH), by an automated process trained to calculate the retinal thickness from scans in a way that is similar to an eye-care practitioner – this process is called image segmentation.
However, the reliability of image segmentation can sometimes be called into question; as such, RNFL measures may be subject to variability. The key component of variability to quantifying reliability issues in tests is the measurement error.
The measurement error represents the variability observed between multiple measurements on the same patient taken at almost the same time using the same test. For a ‘perfect test’, the measurement error would be equal to zero; however, in practice nearly all test measurements taken in duplicate are unequal.
Prospective studies to evaluate test reliability are not always feasible and are mostly practical over shorter periods under controlled study conditions. Our study uses real-world clinical data from INSIGHT of OH patients monitored in routine clinical care, to determine the measurement variability in RNFL measures and the contributing factors to error variation and reliability issues in OCT image segmentation.
Project aims:
● Evaluate the reliability of image segmentations by estimating measurement error in ONH RNFL thickness measures, from repeated measurements taken on adults with OH having ophthalmic images monitored over time
● Consider the results of the study in relation to existing ophthalmic examination strategies at tertiary care ophthalmology clinics. This has the capacity for public health impact by providing evidence on image segmentation reliability, which may inform subsequent decisions about further investigations, treatments, and interventions
Project duration: 18 months
Public benefit statement
A description in plain English of the anticipated outcomes, or impact of project on the general public.
Test reliability on patients receiving disease monitoring impacts clinicians’ ability to resolve uncertainties about health status and reduces ambiguity in clinical decision making, leading to prompt and appropriate treatments or interventions, and ultimately improving health outcomes.
This research will inform existing ophthalmic examination strategies at ophthalmology clinics, by providing evidence on the reliability of RNFL measures and OCT imaging. Since disease monitoring is often expensive, our study also seeks to benefit the ‘public purse’ by providing evidence to inform the development and ongoing appraisal of cost-effective OH monitoring strategies.
Latest approval date
The last date the data access request for this project was approved by a data custodian.
26 June 2023
Dataset(s) name
The name of the dataset(s) being accessed.
Bespoke, University Hospitals Birmingham, ocular hypertension dataset
Access type
Determines whether the data will be accessed with an Trusted Research Environment (TRE) or via data release.
Data Licence Agreement. Data accessed within UHB Trust on premises digital enviornment
Data sensitivity level
The level of identifiability of the data being accessed, as defined by Understanding Patient Data.
Anonymised