Centre for Eye Health, The University of New South Wales, Sydney, New South Wales, Australia.
School of Optometry and Vision Science, The University of New South Wales, Sydney, New South Wales, Australia.
Ophthalmic Physiol Opt. 2022 Nov;42(6):1170-1179. doi: 10.1111/opo.13034. Epub 2022 Aug 4.
Artificial intelligence (AI)-based systems have demonstrated great potential in improving the diagnostic accuracy of retinal disease but are yet to achieve widespread acceptance in routine clinical practice. Clinician attitudes are known to influence implementation. Therefore, this study aimed to identify optometrists' attitudes towards the use of AI to assist in diagnosing retinal disease.
A paper-based survey was designed to assess general attitudes towards AI in diagnosing retinal disease and motivators/barriers for future use. Two clinical scenarios for using AI were evaluated: (1) at the point of care to obtain a diagnostic recommendation, versus (2) after the consultation to provide a second opinion. Relationships between participant characteristics and attitudes towards AI were explored. The survey was mailed to 252 randomly selected practising optometrists across Australia, with repeat mail-outs to non-respondents.
The response rate was 53% (133/252). Respondents' mean (SD) age was 42.7 (13.3) years, and 44.4% (59/133) identified as female, whilst 1.5% (2/133) identified as gender diverse. The mean number of years practising in primary eye care was 18.8 (13.2) years with 64.7% (86/133) working in an independently owned practice. On average, responding optometrists reported positive attitudes (mean score 4.0 out of 5, SD 0.8) towards using AI as a tool to aid the diagnosis of retinal disease, and would be more likely to use AI if it is proven to increase patient access to healthcare (mean score 4.4 out of 5, SD 0.6). Furthermore, optometrists expressed a statistically significant preference for using AI after the consultation to provide a second opinion rather than during the consultation, at the point-of-care (+0.12, p = 0.01).
Optometrists have positive attitudes towards the future use of AI as an aid to diagnose retinal disease. Understanding clinician attitudes and preferences for using AI may help maximise its clinical potential and ensure its successful translation into practice.
人工智能（AI）系统在提高视网膜疾病诊断准确性方面显示出巨大潜力，但尚未在常规临床实践中得到广泛接受。临床医生的态度被认为会影响实施。因此，本研究旨在确定验光师对使用 AI 辅助诊断视网膜疾病的态度。
设计了一份纸质调查问卷，以评估对 AI 诊断视网膜疾病的总体态度以及未来使用的动机/障碍。评估了两种使用 AI 的临床情况：（1）在护理点获得诊断建议，与（2）在咨询后提供第二个意见。探讨了参与者特征与对 AI 的态度之间的关系。该调查以邮寄方式发送给澳大利亚随机抽取的 252 名执业验光师，并对未回复者进行了重复邮寄。
回复率为 53%（133/252）。受访者的平均（SD）年龄为 42.7（13.3）岁，44.4%（59/133）为女性，1.5%（2/133）为性别多样化。在初级眼保健中执业的平均年限为 18.8（13.2）年，64.7%（86/133）在独立拥有的诊所工作。平均而言，参与调查的验光师对使用 AI 作为辅助诊断视网膜疾病的工具持积极态度（平均得分为 4.0 分，标准差为 0.8），如果 AI 被证明可以增加患者获得医疗保健的机会，他们更有可能使用 AI（平均得分为 4.4 分，标准差为 0.6）。此外，验光师表示在咨询后使用 AI 提供第二个意见的意愿明显强于在咨询时，即在护理点（+0.12，p=0.01）。
验光师对未来使用 AI 作为辅助诊断视网膜疾病的工具持积极态度。了解临床医生对使用 AI 的态度和偏好可能有助于最大限度地发挥其临床潜力，并确保其成功转化为实践。
