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Analysing Patterns in Electronic Optometry Referrals: Feasibility and Methodology
Abdullah F Alotaibi1, Matthew Jinkinson2, Ketan R Parmar3
1Division of Pharmacy and Optometry, The University of Manchester, Manchester, UK. Abdullah.Alotaibi@postgrad.manchester.ac.uk.
Purpose:
There may be considerable untapped potential in using large-scale electronic primary care optometry referral data to understand referral patterns. This study aims to evaluate the feasibility of using different analytical methods for this type of dataset.
Methods:
A total of 12,339 electronic referrals made by primary care optometrists in November 2023 were examined. The dataset contained 36 demographic and clinical variables. Preprocessing involved categorising and normalising referral conditions and merging similar attributes to enhance consistency. The feasibility of descriptive evaluations of referral conditions to both ophthalmology in secondary care and within primary care was explored, and a regression analysis was conducted to investigate potential associations between patient sex and referral patterns. A spatial analysis was also conducted to map the geographic distribution of referrals and their association with social deprivation.
Results:
Of all referrals, 77.3% were directed to ophthalmology in secondary care, 14.1% within primary eyecare optometry and non-optometric services, with the remaining 8.5% being unspecified. Cataracts (17.2%), glaucoma (13.5%) and YAG laser capsulotomy (12.1%) emerged as the most frequent referral reasons. Regression analysis identified significant sex differences, where referral proportions for female patients were higher than males for conditions such as glaucoma and neuro-ophthalmology (p = 0.001). Spatial analysis revealed no significant difference between the referral ratio and the deprivation level.
Conclusions:
This study demonstrated viability for evaluating electronic optometry referrals. Despite data limitations, these findings indicate that data quality and scope can support established analytical methods. Moreover, the scale of data variables suggests expanding sample sizes and extending time windows could reveal clinically informative patterns in referrals. Future investigations may further validate findings, helping to understand local, regional or national referral patterns within optometry and potentially address inequalities in eyecare.
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