Awareness and attitudes of elderly Southeast Asian adults towards telehealth during the COVID-19 pandemic: a qualitative study.

Introduction: We aimed to understand the awareness and attitudes of elderly Southeast Asians towards telehealth services during the coronavirus disease 2019 (COVID-19) pandemic in this study. Methods: In this qualitative study, 78 individuals from Singapore (51.3% female, mean age 73.0 ± 7.6 years) were interviewed via telephone between 13 May 2020 and 9 June 2020 during Singapore's first COVID-19 'circuit breaker'. Participants were asked to describe their understanding of telehealth, their experience of and willingness to utilise these services, and the barriers and facilitators underlying their decision. Transcripts were analysed using thematic analysis, guided by the United Theory of Acceptance Use of Technology framework. Results: Of the 78 participants, 24 (30.8%) were able to describe the range of telehealth services available and 15 (19.2%) had previously utilised these services. Conversely, 14 (17.9%) participants thought that telehealth comprised solely home medication delivery and 50 (51.3%) participants did not know about telehealth. Despite the advantages offered by telehealth services, participants preferred in-person consultations due to a perceived lack of human interaction and accuracy of diagnoses, poor digital literacy and a lack of access to telehealth-capable devices. Conclusion: Our results showed poor overall awareness of the range of telehealth services available among elderly Asian individuals, with many harbouring erroneous views regarding their use. These data suggest that public health education campaigns are needed to improve awareness of and correct negative perceptions towards telehealth services in elderly Asians.

DeepDRiD: Diabetic Retinopathy-Grading and Image Quality Estimation Challenge.

We described a challenge named "Diabetic Retinopathy (DR)-Grading and Image Quality Estimation Challenge" in conjunction with ISBI 2020 to hold three sub-challenges and develop deep learning models for DR image assessment and grading. The scientific community responded positively to the challenge, with 34 submissions from 574 registrations. In the challenge, we provided the DeepDRiD dataset containing 2,000 regular DR images (500 patients) and 256 ultra-widefield images (128 patients), both having DR quality and grading annotations. We discussed details of the top 3 algorithms in each sub-challenges. The weighted kappa for DR grading ranged from 0.93 to 0.82, and the accuracy for image quality evaluation ranged from 0.70 to 0.65. The results showed that image quality assessment can be used as a further target for exploration. We also have released the DeepDRiD dataset on GitHub to help develop automatic systems and improve human judgment in DR screening and diagnosis.

Patterns and Characteristics of a Clinical Implementation of a Self-Monitoring Program for Retina Diseases during the COVID-19 Pandemic.

PURPOSE: We describe the large-scale self-initiated recruitment of patients to a self-monitoring initiative for macular pathologic features during the coronavirus disease 2019 (COVID-19) pandemic. DESIGN: Observational study with retrospective analysis. PARTICIPANTS: A total of 2272 patients from the Singapore National Eye Centre (SNEC) whose visits were rescheduled over lockdown (April 13-June 1, 2020) were offered participation in a self-monitoring initiative administered by SNEC with the Alleye application (Switzerland) as the testing instrument. METHODS: This was an observational study with retrospective analysis. Demographics and characteristics were compared between those who signed up and those who did not. Similar comparisons were made between patients who complied with the initiative versus those who did not. Outcomes were tracked for 6 months starting from the commencement of lockdown. MAIN OUTCOME MEASURES: Participation and compliance rates and characteristics of patients who were more likely to participate and comply with the initiative. RESULTS: Seven hundred thirty-two patients (32%) participated in this self-monitoring initiative. Those who participated were younger (62 years of age vs. 68 years of age; P < 0.001), men, and living with family. Patients not receiving treatment and those with poorer vision in the worse-seeing eye were more likely to participate. When grouped according to diagnosis, the proportion who participated was highest for diabetic macular edema (52%), nonneovascular age-related macular degeneration (AMD; 42%), diabetic retinopathy (35%), retinal vein occlusions (18%), and neovascular AMD (15%; P < 0.001). Testing compliance rate was 43% (315/732). Patients who complied with the initiative were older, were receiving treatment, and had poorer vision in the worse-seeing eye. Trigger events occurred in 33 patients, with 5 patients having clinically verified disease progression (1.6%). CONCLUSIONS: We provide clinical data on characteristics of patients with stable retinal diseases who were offered, participated in, and complied with a self-monitoring program. The lower participation rate compared with standardized clinical studies reflects the difficulties in implementation for such initiatives in clinical settings. Despite this, self-monitoring continues to show promise in relieving clinic resources, suggesting the feasibility of scaling such programs beyond the COVID-19 pandemic.