Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence
1.3 PHYSICAL SCIENCES
Refractive error is a significant cause of vision impairment both through the limited access to correction in some areas and the associated ocular diseases for which refractive errors are risk factors. Having timely, regular access to population level estimates of refractive error and vision impairment is necessary to adequately plan public health resources and resource appropriate interventions. A lack of access to current and regularly updated refractive error and vision impairment prevalence data has been identified as a significant limitation in predicting future population trends with many countries lacking any prevalence data or available data being outdated. This project addresses this gap by utilising the untapped potential of Big Data in the form of spectacle lens sales data and optometric electronic medical record data and assesses the potential of these data sources as a public health tool. Chapter 5 contains a review of the application of Big Data and Artificial Intelligence to the field of eyecare and describes the revolutionary potential these new technologies may hold. Chapter 6 describes the data used in this project and the steps taken to acquire and clean the data. Chapter 7 and 8 compare the prevalence of refractive error found using spectacle lens sales data and optometric electronic medical record data to a large population survey of refractive error and demonstrate that with careful analysis an accurate estimation of population distribution of refractive error can be obtained from both types of data. Chapter 8 also estimates the likely level of vision impairment by age 75 given the distribution of myopia in the spectacle lens sales data. Chapter 9 analyses visual acuity data within the optometric electronic medical records which allowed the optimum recall interval and visual acuity threshold for driving licence renewal to be determined. Chapter 10 provides a summary and conclusion on the work, and contains recommendations for future research.
Moore, M. (2021). Big Data: Potential as an Ocular Epidemiology and Public Health Tool. Technological University Dublin. DOI: 10.21427/26WX-FB96
Thesis submitted for the award of PhD, Technological University Dublin, 2021.