Semi-automated screening reveals patients with glaucoma-induced blindness missing out on social support: a cross-sectional study of certificate of visual impairment allocation

Background/aims Many countries provide social support to patients with severe sight impairment (blindness). In the UK, these benefits require a certificate of visual impairment (CVI) which requires referral by a consultant ophthalmologist. Many eligible patients do not receive a CVI due to personal choice or lack of consideration or communication by their doctor. This study investigated the frequency and reasons for missed certification in glaucoma. Methods A retrospective cross-sectional survey was undertaken of all patients with glaucoma attending a tertiary referral clinic over a 12-month period. Semi-automated screening using objective visual acuity and perimetry parameters was facilitated by a web application, GFDC (Glaucoma Field Defect Classifier). CVI-eligible patients’ records were analysed to determine the reasons for missed registration, including incorrect screening classification. Results Of 5620 individual patients consulted, 919 were classified as sight impaired, and 64 were classified as severely sight impaired (blind). Of the patients classified as blind, 7 (11%) were misclassified, and 36 (56%) were on the CVI register already. 21 of 57 eligible patients with glaucoma-induced blindness (37%) were unregistered. Reasons for missed registration included administrative failure (23.8%), lack of consent (9.5%), reversible visual impairment (19.0%), frailty and comorbidity (71.4%), and mental health diagnoses (38.1%). Conclusion A semi-automated algorithm can be used to screen large numbers of patients for CVI eligibility due to blindness. Many eligible patients are not registered, with risk factors including frailty, comorbidity and reversible causes of visual impairment. This algorithm could be used to prompt ophthalmologists to consider registration or used as an alternative referral mechanism. Screening for CVI-eligible patients with an objective algorithm may ameliorate the inequity associated with subjective and variable decision-making. Data are available upon reasonable request. Available upon request to the corresponding author.