Refractive laser eye surgery is a specialised field in ophthalmology which aims to correct the refractive disorder of an eye. The most established technique is LASIK, which has shown good results for the treatment of simple myopia. Complex refractive disorders, such as compound myopic astigmatism, have shown less predictable refractive outcomes, and in some cases the severe over- or under-correction can even worsen the preoperative situation and damage the eye. In its first stage, this research aimed to develop a software system able to present and analyse refractive outcomes. Over 2 prototype stages, this research has led to an operational system named IBRA (Internet Based Refractive Analysis), offering web-based data collection and refractive and vector analysis. In a second stage, Nomogram calculation formulas were developed and integrated into IBRA. These formulas were created from linear regression and best-fit analyses of spherical and cylindrical outcome data stored in IBRA. The purpose of the nomogram calculations was to provide surgeons with adjustment factors that could be used to improve the refractive outcome of patients with complex refractive disorders. Two extensive clinical audits and a randomized controlled trial were performed at Moorfields Eye Hospital to evaluate the IBRA nomogram adjustments. This research showed that IBRA was able to achieve a positive health change. In addition, results from the audits and trial contributed to the knowledge of nomogram adjustments and provided a framework in which future investigations on nomogram and treatment modifications could be performed. In addition to the above clinical studies, two evaluations were performed with the use of IBRA and data logging techniques to investigate users‟ behaviour relating to the management of data entry processes and the use of analysis functions. This research revealed the best method for entering refractive data, and was able to identify the most important analysis methods. Finally, the use of IBRA and its user-interface were investigated with a user satisfaction survey. The results from this questionnaire based study showed a high acceptance of the web-based platform of IBRA and indicated points for improvement (Documentation).

Glaucoma is a leading cause of irreversible blindness and visual impairment. In the clinic, glaucomatous damage can be characterized by structural changes in the optic nerve head (ONH) and retinal nerve fibre layer (RNFL) that can be evaluated by various retinal-imaging techniques such as scanning laser polarimetry and optical coherence tomography (OCT). The structural damage can lead to functional damage in the visual field (VF), normally assessed with standard automated perimetry, which assesses the differential light sensitivity in the field of view. The clinical measurements of retinal structure and visual function play an important role in the detection and management of glaucoma, but the data generated is often complex and highly variable, thus making it hard to clinically interpret. The purpose of this thesis was to investigate knowledge mining procedures for extracting clinically useful information from these measurements. Knowledge mining describes iterative divide-and-conquer type analyses of large-scale questions: solutions to individual smaller problems are used to generate better quality knowledge, which in the case of work reported in this thesis can be translated into clinically useful analysis tools. This thesis describes five knowledge mining procedures specifically developed and applied to structural and functional measurements in glaucoma: (1) probabilistic inference to aid image acquisition of OCT images; (2) a robust and efficient segmentation algorithm to extract features of retina tissue layer structures in large-scale 3-dimensional image volumes acquired by OCT; (3) a predictive structure-function relationship model to bridge the retinal structure and visual function measurements in glaucoma; (4) quantification and visualization of structure-function discordance using the model about structure-function relationship; (5) integration of structural and functional measurements to improve the reproducibility of the measurements. In conclusion the knowledge mining approaches improved the acquisition and/or accuracy of the measurements and provide new clinical analysis tools to detect and manage glaucoma.

Chronic Open Angle Glaucoma (COAG) refers to a chronic progressive condition that is characterised by damage to the optic nerve, resulting in peripheral visual loss that can progress to involve the fovea and central vision; subsequently causing blindness. COAG is reported to have a poor level of adherence to treatment due to its asymptomatic nature. In this study, a Glaucoma Expert Patient Programme (GEPP) demonstrated new ways of improving patients' experience and adherence to COAG treatment. The research has employed an Information-Motivation-8ehavioural Skills Model to understand the association between knowledge, motivation and behavioural skills in an attempt to improve adherence amongst recently diagnosed patients. Patient participation was at the heart of every component of the study. In this research, four Expert Patients were trained and supported to deliver an educational programme (termed the GEPP) to 25 recently diagnosed patients with COAG (Intervention Group) and then a comparison was made to 25 participants (Control Group) that were also recently diagnosed with COAG but did not receive the educational programme. Three pre and post educational programme validated questionnaires were used to measure patients' knowledge, satisfaction and adherence at baseline and then discern changes at 1 month and 6 months follow up to the GEPP intervention. Staff (N = 10), Expert Patient (N = 4), Intervention Group (N=10) and Control Group (N=10) semi-structured interviews were also conducted to obtain deeper insight into their experiences of engaging in the programme. Data analysis indicated IMPROVING AWARENESS was the main theme that emerged supported by three subthemes: knowledge, satisfaction and adherence. This research has taken the Patient-Patient relationship to a higher level. It is viewed that the Expert Patients' experience is crucial and valuable to improving the experience, knowledge and adherence of newly diagnosed patients with COAG. The GEPP delineated in this study provided insight regarding individuals' life experiences of living with and managing chronic complex glaucoma. Implications for practice relate to the development of tailored educational programmes. This research contributed new knowledge to improving the adherence practices of glaucoma patients. It also demonstrated the value of Expert Patients' experience and their contribution to assisting newly diagnosed patients in self-managing their COAG.