ABSTRACT
PURPOSE: Physician turnover is costly to health care systems and can affect patient experience due to discontinuity of care. This study aimed to assess the frequency of turnover by ophthalmologists and characteristics associated with turnover. DESIGN: A retrospective cross-sectional study. PARTICIPANTS: Actively practicing US ophthalmologists included in the Centers for Medicare & Medicaid Services (CMS) Physician Compare and Physician and Other Supplier Public Use File between 2014 and 2021. METHODS: Using two separate publicly available Medicare data sets, we collated data for ophthalmologists associated with practices in each year between 2014 and 2021. We calculated the rate of turnover as (1) annually in each year window and (2) cumulatively as the total proportion of 2014 practices separated by 2021. Multivariate logistic regression analysis was used to identify physician and practice characteristics associated with cumulative turnover. Additionally, we evaluated changes in annual turnover surrounding the Coronavirus disease 2019 pandemic. MAIN OUTCOME MEASURES: Ophthalmologist turnover, defined as a change of an ophthalmologist's National Provider Identifier practice affiliation from one year to the next. RESULTS: Of 13,264 ophthalmologists affiliated with 3,306 unique practices, 34.1% separated from at least one practice between 2014 and 2021. Annual turnover ranged from 3.7% (2017) to 19.4% (2018), with an average rate of 9.4%. Factors associated with increased turnover included solo practice (adjusted odds ratio [aOR], 9.59, p<0.01), university-affiliation (aOR, 1.55, p<0.01), practice location in the Northeast (aOR 1.39, p<0.01), and practice size of 2-4 members (aOR, 1.21, p<0.01). Factors associated with decreased turnover included male gender (aOR, 0.87, p<0.01), and greater than 5 years of practice: 6-10 years (aOR, 0.63), 11-19 years (aOR, 0.54), 20-29 years (aOR, 0.36), and ≥30 years (aOR, 0.18) (p < 0.01 for all). In the initial year of the COVID-19 pandemic (2020), annual turnover grew from 7.8% to 11.0%, then fell to 8.7% in the pandemic post-vaccine period (2021). CONCLUSIONS: One-third of US ophthalmologists separated from at least one practice from 2014-2021. Turnover patterns differ by various physician and practice characteristics, the knowledge of which may prove useful when developing strategies to optimize future workforce stability. Because reasons for turnover cannot be solely determined using administrative data, further investigation is warranted given the potential clinical and financial implications.
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The emergence and rapid evolution of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) caused a global crisis that required a detailed characterization of the dynamics of mutational pattern of the viral genome for comprehending its epidemiology, pathogenesis and containment. We investigated the molecular evolution of the SASR-CoV-2 genome during the first, second and third waves of COVID-19 in Uttar Pradesh, India. Nanopore sequencing of the SARS-CoV-2 genome was undertaken in 544 confirmed cases of COVID-19, which included vaccinated and unvaccinated individuals. In the first wave (unvaccinated population), the 20A clade (56.32%) was superior that was replaced by 21A Delta in the second wave, which was more often seen in vaccinated individuals in comparison to unvaccinated (75.84% versus 16.17%, respectively). Subsequently, 21A delta got outcompeted by Omicron (71.8%), especially the 21L variant, in the third wave. We noticed that Q677H appeared in 20A Alpha and stayed up to Delta, D614G appeared in 20A Alpha and stayed in Delta and Omicron variants (got fixed), and several other mutations appeared in Delta and stayed in Omicron. A cross-sectional analysis of the vaccinated and unvaccinated individuals during the second wave revealed signature combinations of E156G, F157Del, L452R, T478K, D614G mutations in the Spike protein that might have facilitated vaccination breach in India. Interestingly, some of these mutation combinations were carried forward from Delta to Omicron. In silico protein docking showed that Omicron had a higher binding affinity with the host ACE2 receptor, resulting in enhanced infectivity of Omicron over the Delta variant. This work has identified the combinations of key mutations causing vaccination breach in India and provided insights into the change of [virus's] binding affinity with evolution, resulting in more virulence in Delta and more infectivity in Omicron variants of SARS-CoV-2. Our findings will help in understanding the COVID-19 disease biology and guide further surveillance of the SARS-CoV-2 genome to facilitate the development of vaccines with better efficacies.
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PURPOSE: To examine trends in ophthalmic trauma secondary to five major sports (baseball, soccer, tennis, football, basketball) and identify differences between patient characteristics and time period (pre-COVID vs COVID) of injury. METHODS: The National Electronic Injury Surveillance System was queried to extract cases related to the sports of interest from 2011-2020. Entries were analyzed by age, sex, diagnosis, location, and disposition, with narrative descriptions assessed to characterize the mechanism of injury and visual sequelae. National incidence was extrapolated and Pearson's ?2 and Fisher's exact tests were performed. RESULTS: Among 98,995 presentations, most involved male (83.5%) and pediatric patients (59.2%). Contusion/abrasion (57.3%) was the predominant diagnosis, with injuries primarily precipitated by contact with a ball (44.9%) and occurring in the recreational setting (49.0%). Visual sequelae were documented in 6.4% of injuries. Patients were commonly treated/examined and released (95.6%). Between sports, significant differences in diagnosis (p < .001), mechanism of injury (p < .001), location (p < .001), visual sequelae (p < .001), and disposition (p = .005) were observed. Stratification by age indicated significant differences in diagnosis, mechanism of injury, and location (all p < .001). Stratification by sex indicated significant differences in the mechanism of injury (p < .001) and visual sequelae (p = .04). Stratification by time period indicated significant differences in diagnosis (p = .002) and mechanism of injury (p = .001). CONCLUSION: There are notable differences in sports-related ocular injuries by patient characteristic, revealing important considerations for their clinical evaluation and the development of safety guidelines.
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INTRODUCTION: Amidst the COVID-19 pandemic, telemedicine has emerged as a safe and cost-effective alternative to traditional ophthalmology clinic visits. This study evaluated patient attitudes towards telemedicine at a full-service, retina-only practice to identify areas for growth in implementation. METHODS: A survey was distributed to established patients at University Retina and Macula Associates following the completion of a telemedicine encounter in July 2021. On a 5-point Likert scale, patients compared telemedicine to in-person visits for six domains: ability to ease COVID-related anxiety, efficiency, patient education, quality of care, fulfillment of personal needs, and convenience. Pearson's χ2 and Fisher's exact test were used to assess correlations between demographic factors and patient attitudes or preference towards telemedicine. RESULTS: Among 103 respondents, two-thirds (68.7%) preferred in-person compared to telemedicine encounters. Overall, patients had a neutral attitude towards telemedicine [mean Likert rating (SD) = 3.11/5 ± 0.82]. Questions assessing "patient education" and "telemedicine efficiency" received the greatest proportion of positive and negative responses, respectively. Positive attitudes were more frequent among patients with prior telemedicine experience (87.5%) compared to never-users (71.8%; p = 0.046). Patients ≥ 75 years old tended to negatively assess telemedicine regarding reduction of COVID-19-related anxiety, efficiency, patient education, and physician facetime (p < 0.05 for all). A positive but non-significant trend was observed between higher education level and positive attitude towards telemedicine (p = 0.18). Telehealth never-users more often negatively rated receiving adequate facetime with the physician virtually (54.7%) compared to prior users (25.6%; p = 0.004). Younger age, prior history of telemedicine use, and higher education level were associated with increased preference for telemedicine (p < 0.05 for all). CONCLUSION: Our findings revealed hesitance remains among patients towards adoption of telemedicine. Targeting age-, experience-, and education-related barriers will be invaluable for increasing acceptance of this healthcare delivery model.