Author: Mallika Prem Senthil
Prem Senthil, Mallika, 2018 Development and validation of technologically advanced patient-reported outcome measures for retinal diseases, Flinders University, College of Nursing and Health Sciences
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Background: Patient-reported outcome (PRO) instruments are increasingly being considered as an essential outcome measure in clinical practice, research, audits, and trials involving patients. The existing PRO instruments are static (paper-and-pencil based), limited in their item-content, not comprehensive enough to measure quality of life (QoL), outdated and poorly targeted to the study population. Therefore, a project (The Eye-tem Bank) is designed to develop and validate technologically advanced PRO instruments which can precisely measure comprehensive ophthalmic QoL. The Eye-tem Bank project aims to create measures of QoL for all eye diseases. Recognising that different diseases require different questions; the ideal situation is to have disease-specific item banks for all diseases. However, this is not practical. So, the major diseases have individual item banks, then less common diseases need to be split or “grouped” together. But to be valid, these groups must be of diseases with similar QoL impacts. In terms of retinal diseases item banks have been developed for age related macular degeneration, diabetic retinopathy, and retinal detachment. However, it is unclear whether the remaining retinal diseases (other vitreoretinal diseases) can be “grouped” together, or whether they need to be split into multiple separate item banks. The remaining retinal diseases include hereditary degenerations, vascular occlusions and other rare vascular diseases and vitreoretinopathies. Theoretically there would be a need to separate these further. The aim of this thesis is to create item banking for other VR diseases and determine how many item banks the remaining diseases will be split into. This will be done by looking at qualitative data on items and analyses of proposed item banks.
Methods: The other vitreoretinal diseases were grouped into hereditary retinal diseases and acquired retinal diseases. A mixed method design was used. Qualitative methods were used to explore the impact of retinal diseases on the QoL of 79 people. A systematic multi-stage process of item extraction and item revision was used to develop separate item banks for hereditary retinal diseases and acquired retinal diseases . However, only the hereditary retinal diseases item banks were pilot tested on 233 participants. Rasch analysis was used to assess the psychometric properties of the hereditary retinal diseases item banks.
Results: People with hereditary retinal diseases and acquired retinal diseases had different QoL issues. A total of 1,217 items were extracted from 17 PRO instruments, 4 qualitative studies and 79 interviews. After 3 sessions of binning and winnowing, items were reduced to a minimally representative set (n = 411) across nine QoL domains namely; activity limitation, emotional, social, mobility, convenience, symptoms, health concerns, economic and coping. The hereditary retinal diseases and the acquired retinal diseases items banks had 345 and 254 items respectively. Psychometric assessment of the hereditary retinal diseases item banks demonstrated that five domains (mobility, economic, social, convenience and visual symptoms) required minor modifications and three domains (activity limitation, health concerns, and emotional) demonstrated multidimensionality requiring substantial modifications that resulted in the development of 5 new domains.
Conclusion: This research project resulted in the development of comprehensive and psychometrically valid items banks for hereditary retinal diseases that will enable clinicians and researchers to explore the impact of hereditary retinal diseases on QoL.
Keywords: Retinal diseases, quality of life, qualitative interviews, patient-reported outcome instruments, item bank, computerised adaptive testing, Rasch analysis
Subject: Health Sciences thesis
Thesis type: Doctor of Philosophy
Completed: 2018
School: College of Nursing and Health Sciences
Supervisor: Prof Konrad Pesudovs