Background: Ophthalmic clinicians report low confidence in telemedicine-based eye care delivery, but it may have changed given its rapid expansion during the coronavirus 2019 (COVID-19) pandemic. Introduction: The purpose of this study was to determine clinician confidence in telemedicine-based eye care services during COVID-19. Materials and Methods: An electronic survey was sent to clinicians at University of Michigan Kellogg Eye Center (April 17, 2020-May 6, 2020) when nonemergent in-person visits and procedures were restricted. The primary outcome was clinician confidence in using telemedicine-based eye care during COVID-19. Secondary outcomes included telemedicine utilization and its association with clinician confidence using Fisher's exact test. Results: Of the 88 respondents (90.7% response rate; n = 97 total), 83.0% (n = 73) were ophthalmologists and 17.0% (n = 15) were optometrists. Telemedicine utilization increased from 30.7% (n = 27) before the pandemic to 86.2% (n = 75) after the pandemic. Clinicians' confidence in their ability to use telemedicine varied with 28.6% (24/84) feeling confident/extremely confident, 38.1% (32/84) somewhat confident, and 33.3% (28/84) notat-all confident. Most felt that telemedicine was underutilized (62.1%; 54/87) and planned continued use over the next year (59.8%; 52/87). Confident respondents were more likely to have performed three or more telemedicine visits (p = 0.003), to believe telemedicine was underutilized (p < 0.001), and to anticipate continued use of telemedicine (p = 0.009). Discussion: The majority of clinicians were at least somewhat confident about using telemedicine during the pandemic.Clinician confidence was associated with telemedicine visit volume and intention to continue using telemedicine. Conclusions: Policies that foster clinician confidence will be important to sustain telemedicine-based eye care delivery.

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Purpose: To investigate the burden of procedures, visits, and procedure costs in the management of microbial keratitis (MK). Methods: Medical records of patients from an academic hospital outpatient facility between December 2013 and May 2018 were retrospectively reviewed. Patients were included if they were older than the age of 18 years, recruited for study of likely MK, and not concurrently undergoing treatment for other acute eye conditions. For procedural costs, Medicare data for billing were obtained using the Center for Medicare and Medicaid Services Physician Fee Lookup tool. Results: A total of 68 patients were included for analysis. Patients were on average 51.3 years (SD = 19.5), 55.9% women (n = 38), and 89.7% White (n = 61). Per person, the average number of procedures was 2.9 (SD = 4.2). The average number of visits was 13.9 (SD = 9.2) over an average of 26.9 weeks (SD = 24.3). Age (P < 0.0001), positive Gram stain (P = 0.03), and mixed Gram stain (P = 0.002) were positively associated with the number of procedures. Age (P = 0.0003), fungal keratitis (P = 0.02), and mixed Gram stain (P = 0.01) were positively associated with the number of visits. Race was inversely associated with the number of procedures (P = 0.045) and visits (0.03). Patients with bacterial keratitis were more likely to have amniotic membrane grafts (P = 0.01) and tarsorrhaphies (P = 0.03) than fungal patients. Across all procedures performed for the management of MK, the mean cost per patient was $1788.7 (SD = $3324.62). Conclusions: Patients incur many procedural costs and attend many visits during the management of MK. These findings emphasize the importance of patient–provider communication for frequent follow-up care and the potential need to perform procedures for disease management.

Purpose: To understand medication use and patient burden for treatment of bacterial keratitis (BK). Methods: A retrospective study was conducted examining medical records of adult patients with BK in an academic cornea practice. Data collected included medications used in the treatment of BK, dosing of medications, and the number and total duration of clinical encounters. Costs of medications were estimated using the average wholesale pharmacy price. Linear regression analysis was used to investigate associations of medication use with patient demographics and corneal culture results and reported with beta estimates (β) and 95% confidence intervals (95% CIs). Results: Forty-eight patients with BK (56% female) were studied. Patients were treated for a median of 54 days with 10 visits, 5 unique medications, 587 drops, and 7 prescriptions. The estimated median medication cost was $933 (interquartile range: $457–$1422) US dollars. Positive bacterial growth was significantly associated with more visits (β: 6.16, 95% CI: 1.75–10.6, P = 0.007), more days of treatment (β: 86.8, 95% CI: 10.8–163, P = 0.026), more prescribed medications (β: 2.86, 95% CI: 1.04–4.67, P = 0.003), and more doses of medications (β: 796, 95% CI: 818–1412, P = 0.012) compared with patients who did not undergo corneal scraping. Patients were prescribed 132 more drops of medication for every 10 years of older age (β: 132, 95% CI: 18.2–246, P = 0.024). Sex and income were not associated with medication burden or treatment length. Conclusions: Older patients and those with positive cultures incur the most medication burden in treatment of BK. Providers should be aware of medication usage and cost burden as it may affect compliance with treatment.

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Purpose of reviewArtificial intelligence has advanced rapidly in recent years and has provided powerful tools to aid with the diagnosis, management, and treatment of ophthalmic diseases. This article aims to review the most current clinical artificial intelligence applications in anterior segment diseases, with an emphasis on microbial keratitis, keratoconus, dry eye syndrome, and Fuchs endothelial dystrophy.Recent findingsMost current artificial intelligence approaches have focused on developing deep learning algorithms based on various imaging modalities. Algorithms have been developed to detect and differentiate microbial keratitis classes and quantify microbial keratitis features. Artificial intelligence may aid with early detection and staging of keratoconus. Many advances have been made to detect, segment, and quantify features of dry eye syndrome and Fuchs. There is significant variability in the reporting of methodology, patient population, and outcome metrics.SummaryArtificial intelligence shows great promise in detecting, diagnosing, grading, and measuring diseases. There is a need for standardization of reporting to improve the transparency, validity, and comparability of algorithms.

The aim was to identify the facilitators and barriers to implementing glaucoma screening programs in 2 community clinics.Methods: A concurrent mixed-methods process analysis using CER. Key stakeholders-including patients, providers, and staff membersfrom 2 community clinics were interviewed using a semistructured interview guide. Interviews had 2 parts: (1) asking patients about community-based facilitators and barriers to implementing glaucoma screening and care and (2) eliciting feedback about a personalized coaching program. The transcripts were coded using Grounded Theory. Number of participants and number of representative citations were counted per theme. The qualitative analysis was coded using Dedoose 8.3.17 (Los Angeles, CA).Results: Thematic saturation was reached after coding 12 interviews. 30 participants were interviewed, 13 from Hamilton Clinic (Flint, MI; 8 patients, 5 providers and staff members) and 17 from Hope Clinic (Ypsilanti, MI; 6 patients, 11 providers and staff members). The most commonly cited themes were: Priorities (98 citations, 30 participants), Knowledge (73, 26) Transportation (63,26), Cost (60,23), and Convenience/Access (63,22). Broadly applicable barriers to glaucoma care, such as Cost, Transportation, and Trust were identified alongside community-specific barriers such as Language and Convenience/Access. Participants rated their likelihood to follow up with an ophthalmologist after participating in the personalized coaching program at a mean of 8.83 (on a scale of 1 to 10 with 10 being the most confident).Conclusions: CER enables researchers to identify communityspecific barriers and facilitators, allowing more effective program implementation.