Scholarlink

Purpose <p>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.</p> Methods <p>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.</p> Results <p>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 (<i>p</i> = 0.001). Spatial analysis revealed no significant difference between the referral ratio and the deprivation level.</p> Conclusions <p>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.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Analysing Patterns in Electronic Optometry Referrals: Feasibility and Methodology

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月6日

查看全文
  • Abdullah F. Alotaibi,
  • Matthew Jinkinson,
  • Ketan R. Parmar,
  • Glen P. Martin,
  • Philip B. Morgan,
  • Robert A. Harper

摘要

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.