EyeWorld India September 2020 Issue

22 EWAP SEPTEMBER 2020 SECONDARY FEATURE Table 1. Operational models for digital health applications in ophthalmology and beyond. * Consultation alludes to provision of medical advice and/or clinical care (e.g. diagnosis, prescription of medications, recommended surgical management). ** Tele-support alludes to the provision of medical information not amounting to clinical care (e.g. illness coping support, generic information about drug interactions, tackling misinformation) # Operational impact is presented as it relates to the need to re-orient in-person clinical services to cater to the new digital service. Digital Operational models Description of model and clinical context. Clinical applications Health system impact Operational impact # Descriptions of illustrative examples and existing research reports Triage/ Risk stratify Consultation* Telesupport**  Availability of clinical expertise  Access to care  Capacity of care & efficiency Low Middle High Out of Hospital (“Pre-Hospital”) Sorting conveyor Optimise patient flow to minimise unnecessary physical touchpoints. + + + + + + + + + – AI-based eye screening (eg IDx-DR 17 , SELENA 17,31 ) – AI-based chatbots (eg ZOC digital hospital 32 ) Hub-and-Spoke Project expertise across geographies including provider- provider support + + + + + + + + + + + + – Telehealth outreach Services (eg TECS 10 , ETHAN 34 ) – Online health community (OHC eg WebMD 35 , AskDr 36 ) Front-line settings (Outpatient clinics/ Emergency departments) Stream fishing In-person providers with spare capacity help cross-cover digital care. + + + + + + + – Single patient channel (eg ER) – Support from providers on an adhoc basis 2 (e.g. Surgeons with cancelled electives) Inflow funnel Digital care provider augmenting in-person care for overflow patients. + + + + + + + –Multiple patient channels (eg multiple primary care clinics) – Support from dedicated digital provider (eg telehealth) 37 Pyramid Single service with stacked technology such as hybrid telehealth (Synchronous- Asynchronous). + + + + + + + + + + + – “Digital first” service before in-person care (eg SAVED 41 ) – AI chat bot with referrals 40 to online/offline clinic (eg Babylon) Shuffling cards Mixed service with digital appointment- based care overlaid with on-demand. + + + + + + + + + + + + + – “Digital only” healthcare services with scheduled chronic cases & adhoc acute cases (eg SNEC VidCON 41 ) Monitoring solutions (In-/Outpatient) Catchment net Passive monitoring that is ambient or patient-led. + + + + + + + –Wearables (eg ViSi Mobile) 2 –Mobile/IoT applications (eg Alleye 43 ) Lighthouse Active monitoring that is provider- supported and/or state-led + + + + + + + + – Chronic disease apps with provider support (eg Diabeo 47 ) – State-led contact tracing 49 and Surveillance (eg travel/ exposure) healthcare services. Therefore, it is beneficial for clinicians, administrators and researchers to evaluate operational considerations including stakeholders, workflow, resources, and contextual factors for any intended innovation. This would help identify potential unanticipated barriers in different settings, providing opportunities to address them before attempting adoption at scale. Conclusions Digital ophthalmology models will increasingly play a key role in the management of eye patients. COVID-19 has sharpened the need for quicker and broader adoption of different digital solutions. There is need for the ophthalmology community to specifically address the pain points and potential barriers to adoption and design clear strategies to deploy digital services. It is important to emphasize