Introduction
Cataract is defined as the degradation of the optical quality of the crystalline lens that affects vision and is the current leading cause of blindness worldwide.1 Age is a major factor in the development of cataracts, which can affect one or both eyes.2 According to the 2009 Cost of Vision Loss Report, cataracts were one of the top causes of blindness in Canada, affecting almost 3.5 million individuals.3 However, since 2006, the number of surgeries performed yearly has declined, and wait times have soared in Ontario, Canada.4 5 The reason for this declining trend after 2006 is likely multifactorial, including increasing cataract prevalence, restricted operational resources and a 5.9% decline in the number of cataract surgeons per 100 000 total population.5 There is a pressing need for strategies to support the workforce crisis in delivering high-volume, low complexity pathways such as cataract surgery.
The development of artificial intelligence (AI) has led to improvements in many areas of medicine.6 In ophthalmology, AI has shown promising results in the detection and screening of retinopathy of prematurity, age-related macular degeneration, glaucoma and diabetic retinopathy.7–11 Similar to most surgeries, cataract surgery involves postoperative monitoring for complications and to evaluate success. This visit has traditionally been carried out as an in-person visit. AI is set to revolutionise post-cataract surgery management by enhancing automation, increasing effectiveness and decreasing burdens placed on patients and the healthcare system.7 Ultimately, using AI-enabled automation could enhance patient management during and post-cataract surgery.
Dora is a regulated autonomous, voice-based, natural-language clinical assistant designed in the UK. It can have a consultation with patients over the telephone in a similar way to a human clinician by incorporating speech transcription, natural language understanding and a machine learning conversation model to allow contextual dialogues, speech production and natural conversation.12 The technology does not require the installation of an application, the provision of a device, or any training. This is relevant since elderly people and people from low-income families are more likely to be digitally excluded.12
Dora is used in the cataract pathway in the UK, and in a recent study, Khavandi et al found that the majority of patients regarded the AI-telephone follow-up after cataract surgery as very simple, easy to use and they appreciated the convenience.13 The patients also noted that an automated telephone follow-up might greatly lower the number of clinical appointments required to provide postoperative care because it would be less time-consuming than a clinician and would also free up clinicians’ time for other clinical tasks.12
This study is designed to further evaluate the impact of automating cataract follow-up using Dora, in a different Canadian healthcare setting. Technical readiness level of five meaning that technological components are currently being integrated for testing in relevant environments.12 14 The Developmental and Exploratory Clinical Investigations of DEcision support systems driven by Artificial Intelligence reporting guideline was followed in creation of this protocol.15
The objectives of this study are to describe:
Clinical safety of using Dora in the cataract pathway using Kappa statistic of the interobserver decision reliability and retrospective review of clinical notes to establish whether the patient attended the clinic with further concerns after their Dora call.
Patient acceptability of Dora using Net Promoter Score (NPS) to determine on a scale of 1–10 the likelihood of them recommending Dora to a friend or colleague.
Usability and accessibility of the technology for patients using the scores from the System Usability Questionnaire (SUS).
Cost-effectiveness of using Dora compared with standard practice by comparing the cost of the Dora system to the clinic specific costs.
Impact on sustainability through use of the automated telephone follow-up by calculating travel distance and mode of transportation for each patient.