The Impact of COVID-19 on Neuro-Ophthalmology Office Visits and Adoption of Telemedicine Services

Background: The COVID-19 public health emergency (PHE) has significantly changed medical practice in the U.S., including an increase in the utilization of telemedicine. Here, we characterize change in neuro-ophthalmic care delivery during the early COVID-19 PHE, including a comparison of care delivered via telemedicine and in office. Methods: Neuro-ophthalmology outpatient encounters from three practices in the United States (four providers) were studied during the early COVID-19 PHE (March 15, 2020-June 15, 2020) and during the same dates one year prior. For unique patient visits, patient demographics, visit types, visit format, and diagnosis were compared between years and between synchronous telehealth and in-office formats for 2020. Results: There were 1276 encounters for 1167 patients. There were 30% fewer unique patient visits in 2020 vs. 2019 (477 vs. 670) and 55% fewer in office visits (299 vs. 670). Compared to 2019, encounters in 2020 were more likely to be established, to occur via telemedicine and relate to an efferent diagnosis. In 2020, synchronous telehealth visits were more likely to be established compared with in-office encounters. Conclusions: In the practices studied, a lower volume of neuro-ophthalmic care was delivered during the early COVID-19 public health emergency than in the same period in 2019. The type of care shifted toward established patients with efferent diagnoses and the modality of care shifted toward telemedicine

The Impact of COVID-19 on Neuro-Ophthalmology Office Visits and Adoption of Telemedicine Services

Background: The COVID-19 public health emergency (PHE) has significantly changed medical practice in the United States, including an increase in the utilization of telemedicine. Here, we characterize change in neuro-ophthalmic care delivery during the early COVID-19 PHE, including a comparison of care delivered via telemedicine and in office. Methods: Neuro-ophthalmology outpatient encounters from 3 practices in the United States (4 providers) were studied during the early COVID-19 PHE (March 15, 2020-June 15, 2020) and during the same dates 1 year prior. For unique patient visits, patient demographics, visit types, visit format, and diagnosis were compared between years and between synchronous telehealth and in-office formats for 2020. Results: There were 1,276 encounters for 1,167 patients. There were 30% fewer unique patient visits in 2020 vs 2019 (477 vs 670) and 55% fewer in-office visits (299 vs 670). Compared with 2019, encounters in 2020 were more likely to be established, to occur via telemedicine and to relate to an efferent diagnosis. In 2020, synchronous telehealth visits were more likely to be established compared with in-office encounters. Conclusions: In the practices studied, a lower volume of neuro-ophthalmic care was delivered during the early COVID-19 public health emergency than in the same period in 2019. The type of care shifted toward established patients with efferent diagnoses and the modality of care shifted toward telemedicine

The Impact of COVID-19 on Neuro-Ophthalmology Office Visits and Adoption of Telemedicine Services

Background: The COVID-19 public health emergency (PHE) has significantly changed medical practice in the United States, including an increase in the utilization of telemedicine. Here, we characterize change in neuro-ophthalmic care delivery during the early COVID-19 PHE, including a comparison of care delivered via telemedicine and in office. Methods: Neuro-ophthalmology outpatient encounters from 3 practices in the United States (4 providers) were studied during the early COVID-19 PHE (March 15, 2020-June 15, 2020) and during the same dates 1 year prior. For unique patient visits, patient demographics, visit types, visit format, and diagnosis were compared between years and between synchronous telehealth and in-office formats for 2020. Results: There were 1,276 encounters for 1,167 patients. There were 30% fewer unique patient visits in 2020 vs 2019 (477 vs 670) and 55% fewer in-office visits (299 vs 670). Compared with 2019, encounters in 2020 were more likely to be established, to occur via telemedicine and to relate to an efferent diagnosis. In 2020, synchronous telehealth visits were more likely to be established compared with in-office encounters. Conclusions: In the practices studied, a lower volume of neuro-ophthalmic care was delivered during the early COVID-19 public health emergency than in the same period in 2019. The type of care shifted toward established patients with efferent diagnoses and the modality of care shifted toward telemedicine

Differentiation of Active Corneal Infections from Healed Scars Using Deep Learning

PurposeTo develop and evaluate an automated, portable algorithm to differentiate active corneal ulcers from healed scars using only external photographs.DesignA convolutional neural network was trained and tested using photographs of corneal ulcers and scars.ParticipantsDe-identified photographs of corneal ulcers were obtained from the Steroids for Corneal Ulcers Trial (SCUT), Mycotic Ulcer Treatment Trial (MUTT), and Byers Eye Institute at Stanford University.MethodsPhotographs of corneal ulcers (n = 1313) and scars (n = 1132) from the SCUT and MUTT were used to train a convolutional neural network (CNN). The CNN was tested on 2 different patient populations from eye clinics in India (n = 200) and the Byers Eye Institute at Stanford University (n = 101). Accuracy was evaluated against gold standard clinical classifications. Feature importances for the trained model were visualized using gradient-weighted class activation mapping.Main outcome measuresAccuracy of the CNN was assessed via F1 score. The area under the receiver operating characteristic (ROC) curve (AUC) was used to measure the precision-recall trade-off.ResultsThe CNN correctly classified 115 of 123 active ulcers and 65 of 77 scars in patients with corneal ulcer from India (F1 score, 92.0% [95% confidence interval (CI), 88.2%-95.8%]; sensitivity, 93.5% [95% CI, 89.1%-97.9%]; specificity, 84.42% [95% CI, 79.42%-89.42%]; ROC: AUC, 0.9731). The CNN correctly classified 43 of 55 active ulcers and 42 of 46 scars in patients with corneal ulcers from Northern California (F1 score, 84.3% [95% CI, 77.2%-91.4%]; sensitivity, 78.2% [95% CI, 67.3%-89.1%]; specificity, 91.3% [95% CI, 85.8%-96.8%]; ROC: AUC, 0.9474). The CNN visualizations correlated with clinically relevant features such as corneal infiltrate, hypopyon, and conjunctival injection.ConclusionsThe CNN classified corneal ulcers and scars with high accuracy and generalized to patient populations outside of its training data. The CNN focused on clinically relevant features when it made a diagnosis. The CNN demonstrated potential as an inexpensive diagnostic approach that may aid triage in communities with limited access to eye care