Identifying Medical Diagnoses and Treatable Diseases by Image-Based Deep Learning.

The implementation of clinical-decision support algorithms for medical imaging faces challenges with reliability and interpretability. Here, we establish a diagnostic tool based on a deep-learning framework for the screening of patients with common treatable blinding retinal diseases. Our framework utilizes transfer learning, which trains a neural network with a fraction of the data of conventional approaches. Applying this approach to a dataset of optical coherence tomography images, we demonstrate performance comparable to that of human experts in classifying age-related macular degeneration and diabetic macular edema. We also provide a more transparent and interpretable diagnosis by highlighting the regions recognized by the neural network. We further demonstrate the general applicability of our AI system for diagnosis of pediatric pneumonia using chest X-ray images. This tool may ultimately aid in expediting the diagnosis and referral of these treatable conditions, thereby facilitating earlier treatment, resulting in improved clinical outcomes. VIDEO ABSTRACT.

Integrated Genomic and Social Network Analyses of SARS-CoV-2 Transmission in the Healthcare Setting.

BACKGROUND: Infection prevention (IP) measures are designed to mitigate the transmission of pathogens in healthcare. Using large-scale viral genomic and social network analyses, we determined if IP measures used during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic were adequate in protecting healthcare workers (HCWs) and patients from acquiring SARS-CoV-2. METHODS: We performed retrospective cross-sectional analyses of viral genomics from all available SARS-CoV-2 viral samples collected at UC San Diego Health and social network analysis using the electronic medical record to derive temporospatial overlap of infections among related viromes and supplemented with contact tracing data. The outcome measure was any instance of healthcare transmission, defined as cases with closely related viral genomes and epidemiological connection within the healthcare setting during the infection window. Between November 2020 through January 2022, 12 933 viral genomes were obtained from 35 666 patients and HCWs. RESULTS: Among 5112 SARS-CoV-2 viral samples sequenced from the second and third waves of SARS-CoV-2 (pre-Omicron), 291 pairs were derived from persons with a plausible healthcare overlap. Of these, 34 pairs (12%) were phylogenetically linked: 19 attributable to household and 14 to healthcare transmission. During the Omicron wave, 2106 contact pairs among 7821 sequences resulted in 120 (6%) related pairs among 32 clusters, of which 10 were consistent with healthcare transmission. Transmission was more likely to occur in shared spaces in the older hospital compared with the newer hospital (2.54 vs 0.63 transmission events per 1000 admissions, P < .001). CONCLUSIONS: IP strategies were effective at identifying and preventing healthcare SARS-CoV-2 transmission.

Social determinants of health and health disparities in glaucoma: A review.

Social determinants of health and barriers to care can significantly impact patients' access to glaucoma care and treatment, resulting in disparities within disease presentation, progression, management, and treatment outcomes. The widespread adoption of electronic health record systems has allowed researchers and clinicians to further explore these relationships, identifying factors such as race, ethnicity, and socioeconomic status to be risk factors for more severe disease and lower treatment adherence. These disparities highlight potential targets for interventions to combat these disparities and improve overall patient outcomes. This article provides a summary of the available data on health disparities within glaucoma disease presentation, progression, management, treatment, and outcomes and discusses interventions to improve care delivery and outcomes among patients with glaucoma.

Evaluation of bias and gender/racial concordance based on sentiment analysis of narrative evaluations of clinical clerkships using natural language processing.

There is increasing interest in understanding potential bias in medical education. We used natural language processing (NLP) to evaluate potential bias in clinical clerkship evaluations. Data from medical evaluations and administrative databases for medical students enrolled in third-year clinical clerkship rotations across two academic years. We collected demographic information of students and faculty evaluators to determine gender/racial concordance (i.e., whether the student and faculty identified with the same demographic). We used a multinomial log-linear model for final clerkship grades, using predictors such as numerical evaluation scores, gender/racial concordance, and sentiment scores of narrative evaluations using the SentimentIntensityAnalyzer tool in Python. 2037 evaluations from 198 students were analyzed. Statistical significance was defined as P < 0.05. Sentiment scores for evaluations did not vary significantly by student gender, race, or ethnicity (P = 0.88, 0.64, and 0.06, respectively). Word choices were similar across faculty and student demographic groups. Modeling showed narrative evaluation sentiment scores were not predictive of an honors grade (odds ratio [OR] 1.23, P = 0.58). Numerical evaluation average (OR 1.45, P < 0.001) and gender concordance between faculty and student (OR 1.32, P = 0.049) were significant predictors of receiving honors. The lack of disparities in narrative text in our study contrasts with prior findings from other institutions. Ongoing efforts include comparative analyses with other institutions to understand what institutional factors may contribute to bias. NLP enables a systematic approach for investigating bias. The insights gained from the lack of association between word choices, sentiment scores, and final grades show potential opportunities to improve feedback processes for students.

REFINING THE RETINAL PHENOTYPE OF PATIENTS WITH SUSPECTED PENTOSAN POLYSULFATE SODIUM RETINOPATHY.

PURPOSE: To refine the retinal phenotypes of suspected pentosan polysulfate sodium toxicity using ultra-widefield imaging. METHODS: Patients with complete dosing profiles who visited the ophthalmology department and with ultra-widefield and optical coherence tomography imaging records were identified using electronic health records at a large academic center. Retinal toxicity was initially identified using previously published imaging criteria, while grading was categorized using both previously reported and new classification systems. RESULTS: One hundred and four patients were included in this study. Twenty-six (25%) were identified as having toxicity from PPS. The mean duration of exposure and cumulative dose between the retinopathy group (162.7 months, 1,803.2 g) were longer and higher compared with the nonretinopathy group (69.7 months, 972.6 g) (both P < 0.001). There was variability of extramacular phenotype in the retinopathy group, with four eyes having only peripapillary involvement and six eyes having far peripheral extension. CONCLUSION: Retinal toxicity in the setting of prolonged exposure and increased cumulative dosing from PPS therapy produces phenotypic variability. Providers should be aware of the extramacular component of toxicity when screening patients. Understanding the different retinal phenotypes may prevent continued exposure and reduce the risk of vision-threatening foveal-involving disease.

PENTOSAN POLYSULFATE SODIUM (ELMIRON) MACULOPATHY: A Genetic Perspective.

PURPOSE: To assess genetic associations for pentosan polysufate sodium maculopathy. METHODS: Genetic testing for inherited retinal dystrophy genes using exome testing and for 14 age-related macular degeneration-associated single nucleotide polymorphisms (SNPs) using panel testing were performed. In addition, full-field electroretinograms (ffERG) were obtained to identify any cone-rod dystrophy. RESULTS: Eleven of 15 patients were women, with a mean age of 69 (range 46-85). Inherited retinal dystrophy exome testing in five patients revealed six pathogenic variants, but failed to confirm inherited retinal dystrophy in any patient genetically. FfERG performed in 12 patients demonstrated only nonspecific a- and b-wave abnormalities in 11 cases and was normal in one case. For age-related macular degeneration single nucleotide polymorphisms, CFH rs3766405 ( P = 0.003) and CETP ( P = 0.027) were found to be statistically significantly associated with pentosan polysulfate maculopathy phenotype compared with the control population. CONCLUSION: Pentosan polysulfate maculopathy is not associated with Mendelian inherited retinal dystrophy genes. However, several age-related macular degeneration risk alleles were identified to be associated with maculopathy compared with their frequency in the normal population. This suggests a role for genes in disease pathology, particularly the alternative complement pathway. These findings would benefit from further investigation to understand the risk of developing maculopathy in taking pentosan polysulfate.

Mental health and social support among glaucoma patients enrolled in the NIH All of Us COVID-19 Participant Experience (COPE) survey.

BACKGROUND: The COVID-19 pandemic created many challenges for our society. In this study, we explore how measures of mental health, coping strategies, and social support during the pandemic varied by glaucoma status. METHODS: A cohort of patients aged 40 and over enrolled in the NIH All of Us Research Program, a nationwide longitudinal cohort, who answered the COVID-19 Participant Experience (COPE) survey was obtained. We analyzed several measures of mental health, coping strategies, and social support used during the early stages of the COVID-19 pandemic. Surveys were recurring and answered from May 2020 to February 2021. Demographics and the most recently answered survey responses were obtained and stratified by glaucoma status. Pearson's Chi-squared tests and multivariable logistic regressions adjusting for age, gender, race, ethnicity, and income were used to generate p-values, odds ratios (ORs) and 95% confidence intervals (CIs) between outcome measures and glaucoma status. RESULTS: Of 42,484 patients who responded to All of Us COPE survey items, 2912 (6.9%) had a diagnosis of glaucoma. On Pearson's Chi-squared tests glaucoma patients were less likely to report drinking alcohol (P = 0.003), eating more food than usual (P = 0.004), and using marijuana (P = 0.006) to cope with social distancing than those without a diagnosis of glaucoma. Further, glaucoma patients had lower rates of probable mild, moderate, or severe depression as calculated by Patient Health Questionnaire-9 (PHQ-9) scores (P < 0.001) and had lower rates of reporting some or a lot of stress from social distancing (P < 0.001). However, glaucoma patients were less likely to report having someone to help prepare meals (P = 0.005) or help with daily chores (P = 0.003) if they became sick with COVID-19. In multivariable logistic regression analyses adjusting for confounding factors, no differences were found for measures of mental health or social support. CONCLUSIONS: Glaucoma patients did not fare worse on many measures of mental health and coping strategies during the early stages of the COVID-19 pandemic compared those without glaucoma. However, a substantial proportion of glaucoma patients still endorsed stress, social isolation, and probable depression, representing challenges for disease management.

Evaluation of Depression and Anxiety in a Diverse Population With Thyroid Eye Disease Using the Nationwide NIH All of Us Database.

PURPOSE: To evaluate the prevalence of depression and anxiety among individuals with thyroid eye disease (TED) and identify sociodemographic risk factors using the NIH All of Us database. METHODS: Three hundred ninety eight cases with TED were compared with 1,592 controls with demographics matching the 2020 US Census. Primary outcomes were diagnosed depression or anxiety; Patient Health Questionnaire-9 (PHQ-9) scores and General Anxiety Disorder-7 (GAD-7) scores were included as secondary outcomes. We performed multivariable logistic regression to generate odds ratios (ORs) and 95% confidence intervals (CIs) for the association between TED and depression and anxiety. RESULTS: Patients with TED were more likely to have depression (OR 2.72, 95% CI 2.08-3.56, p < 0.001) and anxiety (OR 2.82, 95% CI 2.16-3.70, p < 0.001) than controls. In patients with TED, female gender was an independent risk factor for both depression (OR 1.72; 95% CI 1.00-5.07, p = 0.05) and anxiety (OR 2.17, 95% CI 1.25-3.85, p = 0.006). Unemployment (OR 1.72, 95% CI 1.03-2.94, p = 0.04) and lower income (OR 0.88 for income as a continuous variable, 95% CI 0.79-0.99, p = 0.03) were risk factors for anxiety. Risk factors for more severe depression as assessed by PHQ-9 included lower income (OR 0.70, 95% CI 0.57-0.85, p < 0.001), and protective factors included Black race (OR 0.12, 95% CI 0.02-0.45, p = 0.002). Lower income was associated with more severe anxiety as assessed by GAD-7 (OR 0.77, 95% CI 0.64-0.94, p = 0.009). CONCLUSIONS: Patients with TED were more likely to develop depression and anxiety compared with controls. This study highlights the psychosocial impact of TED and associated socioeconomic risk factors.

Associations Between Thyroid Eye Disease and Glaucoma Among Those Enrolled in the National Institutes of Health All of Us Research Program.

PURPOSE: To assess the association between thyroid eye disease (TED) and glaucoma. METHODS: Patients 18 years of age and over enrolled in the NIH All of Us Research Program, a nationwide cohort, were extracted. Those with conditions relating to TED were identified and compared with 2020 US Census-matched controls without a diagnosis of TED in a 1:4 ratio. The authors used Pearson's χ 2 tests to study demographics by TED status, and logistic regression to generate odds ratios and 95% confidence intervals to evaluate the association between TED and glaucoma (any type, including glaucoma suspect), using those without TED as the reference group. Multivariable models were adjusted for age, gender, race/ethnicity, eye doctor visits, and smoking status. RESULTS: A total of 393 cases of TED and 1,572 US Census-matched controls were identified. The median age of the cohort was 63 years (interquartile range: 48-73 years). Age, gender, and race/ethnicity varied by TED status ( p < 0.001). Overall, 114 (29.0%) of TED cases had a diagnosis of glaucoma, compared with 94 (6.0%) of non-TED controls. On bivariate logistic regression models, those diagnosed with TED were significantly more likely to be diagnosed with glaucoma compared with controls (odds ratio: 6.42; 95% confidence interval: 4.76-8.70; p < 0.001). This trend persisted on multivariable logistic regression controlling for confounding factors (odds ratio: 3.37; 95% confidence interval: 1.85-6.20 p < 0.001). CONCLUSIONS: Individuals with TED were significantly more likely to be diagnosed with glaucoma. Clinicians caring for patients with TED should be aware of this elevated risk and arrange glaucoma evaluation, accordingly.

Barriers to Implementation of Teleretinal Diabetic Retinopathy Screening Programs Across the University of California.

Aim: To describe barriers to implementation of diabetic retinopathy (DR) teleretinal screening programs and artificial intelligence (AI) integration at the University of California (UC). Methods: Institutional representatives from UC Los Angeles, San Diego, San Francisco, Irvine, and Davis were surveyed for the year of their program's initiation, active status at the time of survey (December 2021), number of primary care clinics involved, screening image quality, types of eye providers, image interpretation turnaround time, and billing codes used. Representatives were asked to rate perceptions toward barriers to teleretinal DR screening and AI implementation using a 5-point Likert scale. Results: Four UC campuses had active DR teleretinal screening programs at the time of survey and screened between 246 and 2,123 patients at 1-6 clinics per campus. Sites reported variation between poor-quality photos (<5% to 15%) and average image interpretation time (1-5 days). Patient education, resource availability, and infrastructural support were identified as barriers to DR teleretinal screening. Cost and integration into existing technology infrastructures were identified as barriers to AI integration in DR screening. Conclusions: Despite the potential to increase access to care, there remain several barriers to widespread implementation of DR teleretinal screening. More research is needed to develop best practices to overcome these barriers.

Data Sources for Evaluating Health Disparities in Ophthalmology: Where We Are and Where We Need to Go.

Data provide an opportunity to discover disparities and inequities that may otherwise be unrecognized. Within the American Academy of Ophthalmology (AAO) Task Force on Disparities in Eye Care, the Leveraging Data Sub-task Force was charged with identifying data sources to study health disparities in eye care and to leverage data to advance health equity. We evaluated large data sources to determine their strengths, deficiencies, and relative accessibility in relation to the likelihood of identifying eye care disparities. We highlight the current challenges with these data sources and review key recommendations for improving future sources for studying health disparities in eye care.

Impact of Smoking on Visual Field Progression in a Long-term Clinical Follow-up.

PURPOSE: To investigate the effect of smoking on rates of progressive visual field (VF) damage over time in glaucoma. DESIGN: Retrospective cohort study. PARTICIPANTS: Five hundred eleven eyes of 354 patients with glaucoma followed up from multicenter glaucoma registries. METHODS: In this longitudinal study, 354 patients with primary open-angle glaucoma with a minimum of 3 years of follow-up and 5 VF tests were enrolled from the Diagnostic Innovations in Glaucoma Study and the African Descent and Glaucoma Evaluation Study. Univariate and multivariate linear mixed models were used to investigate the effects of smoking on rates of 24-2 VF mean deviation loss. Visual field progression was defined using pointwise linear and significant negative VF mean deviation loss. Logistic regression was used to identify baseline factors and whether different levels of smoking intensity were associated with VF progression. Kaplan-Meier survival analysis and the log-rank test were used to compare the cumulative risk ratio of progression between smoker and never smoker groups. MAIN OUTCOME MEASURES: Visual field progression. RESULTS: Five hundred eleven eyes of 354 patients were included over the median follow-up of 12.5 years. Median baseline age was 64.8 years. Of the 354 patients, 124 (35%) were Black, and 149 (42.1%) and 168 (59.8%) had reported a history of smoking or alcohol consumption, respectively. In a multivariate model, higher smoking intensity was associated with faster VF loss (coefficient, -0.05 decibels (dB)/year per 10 pack-years; 95% confidence interval [CI], -0.08 to -0.01 dB/year per 10 pack-years; P = 0.010). Developing VF progression in eyes of heavy smokers (≥ 20 pack-years) was 2.2 times more than in eyes of patients without smoking history (odds ratio, 2.21; 95% CI, 1.02-4.76; P = 0.044). Statistically significant differences were found between heavy smokers (≥ 20 pack-years) and never smokers by Kaplan-Meier analysis (P = 0.011, log-rank test). CONCLUSIONS: Heavy smokers are more likely to sustain VF loss in eyes with glaucoma. The prospective longitudinal design of this study supports the hypothesis that levels of smoking may be a significant predictor for glaucoma progression. Additionally, this information can be used for clinically relevant tobacco prevention and intervention messages.

Towards effective data sharing in ophthalmology: data standardization and data privacy.

PURPOSE OF REVIEW: The purpose of this review is to provide an overview of updates in data standardization and data privacy in ophthalmology. These topics represent two key aspects of medical information sharing and are important knowledge areas given trends in data-driven healthcare. RECENT FINDINGS: Standardization and privacy can be seen as complementary aspects that pertain to data sharing. Standardization promotes the ease and efficacy through which data is shared. Privacy considerations ensure that data sharing is appropriate and sufficiently controlled. There is active development in both areas, including government regulations and common data models to advance standardization, and application of technologies such as blockchain and synthetic data to help tackle privacy issues. These advancements have seen use in ophthalmology, but there are areas where further work is required. SUMMARY: Information sharing is fundamental to both research and care delivery, and standardization/privacy are key constituent considerations. Therefore, widespread engagement with, and development of, data standardization and privacy ecosystems stand to offer great benefit to ophthalmology.

Predictive Modeling of New-Onset Postoperative Diplopia Following Orbital Decompression for Thyroid Eye Disease.

PURPOSE: To identify risk factors for the development of new-onset, postoperative diplopia following orbital decompression surgery based on patient demographics, clinical exam characteristics, radiographic parameters, and surgical techniques. METHODS: We conducted a multi-center retrospective chart review of patients who underwent orbital decompression for thyroid eye disease (TED). Patient demographics, including age, gender, smoking history, preoperative exophthalmometry, clinical activity score (CAS), use of peribulbar and/or systemic steroids, and type of orbital decompression were reviewed. Postoperative diplopia was determined at a minimum of 3 months postoperatively and before any further surgeries. Cross-sectional area ratios of each extraocular muscle to orbit and total fat to orbit were calculated from coronal imaging in a standard fashion. All measurements were carried out using PACS imaging software. Multivariable logistic regression modeling was performed using Stata 14.2 (StataCorp, College Station, TX). RESULTS: A total of 331 patients without preoperative diplopia were identified. At 3 months postoperatively, 249 patients had no diplopia whereas 82 patients developed diplopia. The average postoperative follow-up was 22 months (range 3-156) months. Significant preoperative clinical risk factors for postoperative diplopia included older age at surgery, proptosis, use of peribulbar or systemic steroids, elevated clinical activity score, and presence of preoperative compressive optic neuropathy. Imaging findings of enlarged cross-sectional areas of each rectus muscle to the overall orbital area also conferred a significant risk of postoperative diplopia. Regarding surgical factors, postoperative diplopia was more common among those undergoing medial wall decompression, bilateral orbital surgery, and balanced decompression, whereas endoscopic medial wall decompression was found to be relatively protective. CONCLUSIONS: This study identifies risk factors associated with the development of diplopia following orbital decompression using multivariable data. This study demonstrates that several characteristics including age, clinical activity score, the cross-sectional muscle to orbit ratios, in addition to the type of orbital decompression surgery, are predictive factors for the development of new-onset postoperative diplopia.

Social determinants associated with loss of an eye in the United States using the All of Us nationwide database.

PURPOSE: To identify common factors associated with the loss of an eye using the NIH All of Us database. METHODS: In this case-controlled study, we extracted electronic health record and socio-demographic data for 231 cases of eye loss from All of Us enrollment sites. Controls (N = 924) matched the demographic characteristics of the 2020 United States Census. Bivariate analyses and multivariable logistic regression identified variables significantly associated with increased odds of eye loss. OUTCOME MEASURES: Medical and social determinants associated with increased odds of losing an eye. RESULTS: Among cases, the average age (standard deviation) was 60.1 (14.4) years. The majority (125, 54.1%) were male. 87 (37.7%) identified as African American, and 49 (21.2%) identified as Hispanic or Latino. Loss of eye was more likely in those with ocular tumor (odds ratio [OR] 421.73, 25 95% confidence interval [CI] 129.81-1959.80, p < .001), trauma (OR 13.38, 95% CI 6.64-27.43, p < .001), infection (OR 11.46, 95% CI 4.11-32.26, p = .001) or glaucoma (OR 8.33, 95% CI 4.43- 15.81, p < .001). African American (OR 2.39, 95% CI 1.39-4.09, p = .002) and Hispanic or Latino (OR 1.80, 95% CI 1.01-3.15, p = .04) participants were disproportionately affected. CONCLUSIONS: Racial and ethnic disparities exist among those with loss of an eye from underlying conditions. Addressing health inequities may mitigate the risk of this morbid outcome.

Gaps in standards for integrating artificial intelligence technologies into ophthalmic practice.

PURPOSE OF REVIEW: The purpose of this review is to provide an overview of healthcare standards and their relevance to multiple ophthalmic workflows, with a specific emphasis on describing gaps in standards development needed for improved integration of artificial intelligence technologies into ophthalmic practice. RECENT FINDINGS: Healthcare standards are an essential component of data exchange and critical for clinical practice, research, and public health surveillance activities. Standards enable interoperability between clinical information systems, healthcare information exchange between institutions, and clinical decision support in a complex health information technology ecosystem. There are several gaps in standards in ophthalmology, including relatively low adoption of imaging standards, lack of use cases for integrating apps providing artificial intelligence -based decision support, lack of common data models to harmonize big data repositories, and no standards regarding interfaces and algorithmic outputs. SUMMARY: These gaps in standards represent opportunities for future work to develop improved data flow between various elements of the digital health ecosystem. This will enable more widespread adoption and integration of artificial intelligence-based tools into clinical practice. Engagement and support from the ophthalmology community for standards development will be important for advancing this work.

Pre-clinical remote undergraduate medical education during the COVID-19 pandemic: a survey study.

BACKGROUND: The Coronavirus Disease 2019 (COVID-19) pandemic has necessitated a sudden transition to remote learning in medical schools. We aimed to assess perceptions of remote learning among pre-clinical medical students and subsequently to identify pros and cons of remote learning, as well as uncover gaps to address in ongoing curricular development. METHODS: A survey was distributed to first- and second-year medical students at the University of California San Diego School of Medicine in March 2020. Frequencies of responses to structured multiple-choice questions were compared regarding impacts of remote learning on quality of instruction and ability to participate, value of various remote learning resources, living environment, and preparedness for subsequent stages of training. Responses to open-ended questions about strengths and weaknesses of the remote curriculum and overall reflections were coded for thematic content. RESULTS: Of 268 students enrolled, 104 responded (53.7% of first-year students and 23.9% of second-year students). Overall, students felt that remote learning had negatively affected the quality of instruction and their ability to participate. Most (64.1%) preferred the flexibility of learning material at their own pace. Only 25.5% of respondents still felt connected to the medical school or classmates, and feelings of anxiety and isolation were noted negatives of remote learning. Most second-year students (56.7%) felt their preparation for the United States Medical Licensing Examination Step 1 exam was negatively affected, and 43.3% felt unprepared to begin clerkships. In narrative responses, most students appreciated the increased flexibility of remote learning, but they also identified several deficits that still need to be addressed, including digital fatigue, decreased ability to participate, and lack of clinical skills, laboratory, and hands-on learning. CONCLUSIONS: Videocasted lectures uploaded in advance, electronic health record and telehealth training for students, and training for teaching faculty to increase technological fluency may be considered to optimize remote learning curricula.

Text Processing for Detection of Fungal Ocular Involvement in Critical Care Patients: Cross-Sectional Study.

BACKGROUND: Fungal ocular involvement can develop in patients with fungal bloodstream infections and can be vision-threatening. Ocular involvement has become less common in the current era of improved antifungal therapies. Retrospectively determining the prevalence of fungal ocular involvement is important for informing clinical guidelines, such as the need for routine ophthalmologic consultations. However, manual retrospective record review to detect cases is time-consuming. OBJECTIVE: This study aimed to determine the prevalence of fungal ocular involvement in a critical care database using both structured and unstructured electronic health record (EHR) data. METHODS: We queried microbiology data from 46,467 critical care patients over 12 years (2000-2012) from the Medical Information Mart for Intensive Care III (MIMIC-III) to identify 265 patients with culture-proven fungemia. For each fungemic patient, demographic data, fungal species present in blood culture, and risk factors for fungemia (eg, presence of indwelling catheters, recent major surgery, diabetes, immunosuppressed status) were ascertained. All structured diagnosis codes and free-text narrative notes associated with each patient's hospitalization were also extracted. Screening for fungal endophthalmitis was performed using two approaches: (1) by querying a wide array of eye- and vision-related diagnosis codes, and (2) by utilizing a custom regular expression pipeline to identify and collate relevant text matches pertaining to fungal ocular involvement. Both approaches were validated using manual record review. The main outcome measure was the documentation of any fungal ocular involvement. RESULTS: In total, 265 patients had culture-proven fungemia, with Candida albicans (n=114, 43%) and Candida glabrata (n=74, 28%) being the most common fungal species in blood culture. The in-hospital mortality rate was 121 (46%). In total, 7 patients were identified as having eye- or vision-related diagnosis codes, none of whom had fungal endophthalmitis based on record review. There were 26,830 free-text narrative notes associated with these 265 patients. A regular expression pipeline based on relevant terms yielded possible matches in 683 notes from 108 patients. Subsequent manual record review again demonstrated that no patients had fungal ocular involvement. Therefore, the prevalence of fungal ocular involvement in this cohort was 0%. CONCLUSIONS: MIMIC-III contained no cases of ocular involvement among fungemic patients, consistent with prior studies reporting low rates of ocular involvement in fungemia. This study demonstrates an application of natural language processing to expedite the review of narrative notes. This approach is highly relevant for ophthalmology, where diagnoses are often based on physical examination findings that are documented within clinical notes.

Evaluation of Electronic Health Record Implementation in an Academic Oculoplastics Practice.

PURPOSE: Despite increasing electronic health record (EHR) adoption, perceptions of EHRs are negative among ophthalmologists due to concerns about productivity, costs, and documentation. The authors evaluated the effects of EHR adoption in an oculoplastics practice, which had not been previously studied. METHODS: Clinical volume, documentation time, time spent with patients, reimbursement, relative value units, and patient satisfaction were examined for 2 academic oculoplastics attendings between April 2018 and April 2019, with EHR implementation in September 2018. RESULTS: The mean number of patients seen in a half-day clinic was 31.8 versus 27.7 (p = 0.018) pre- and post-EHR implementation, respectively. EHR implementation had no effect on total monthly reimbursement (p = 0.88) or total monthly relative value units (p = 0.54). Average reimbursement (p = 0.004) and relative value units (p = 0.001) per patient encounter were significantly greater with EHR use. Patient satisfaction scores improved (p = 0.018). Mean physician time per patient increased from 6.4 to 9.0 minutes (p < 0.001). Mean documentation time per patient increased from 1.7 to 3.6 minutes (p < 0.001). Average patient wait times decreased by 9 minutes (p = 0.03) with EHR use. No scribes were used. CONCLUSIONS: EHR implementation was associated with decreased patient volume without significant differences in total reimbursement. Although EHR adoption was associated with increased physician time devoted to patients and greater time expenditure on documentation, patients experienced decreased wait times. This suggests that EHR use streamlined the overall clinic flow without sacrificing physicians' time with the patient. The author's findings suggest that EHR implementation can be accomplished in an academic oculoplastics setting without negative impact on patient experience or reimbursement considerations.

Smart Electronic Eyedrop Bottle for Unobtrusive Monitoring of Glaucoma Medication Adherence.

Glaucoma, the leading cause of irreversible blindness, affects >70 million people worldwide. Lowering intraocular pressure via topical administration of eye drops is the most common first-line therapy for glaucoma. This treatment paradigm has notoriously high non-adherence rates: ranging from 30% to 80%. The advent of smart phone enabled technologies creates promise for improving eyedrop adherence. However, previous eyedrop electronic monitoring solutions had awkward medication bottle adjuncts and crude software for monitoring the administration of a drop that adversely affected their ability to foster sustainable improvements in adherence. The current work begins to address this unmet need for wireless technology by creating a "smart drop" bottle. This medication bottle is instrumented with sensing electronics that enable detection of each eyedrop administered while maintaining the shape and size of the bottle. This is achieved by a thin electronic force sensor wrapped around the bottle and underneath the label, interfaced with a thin electronic circuit underneath the bottle that allows for detection and wireless transmission to a smart-phone application. We demonstrate 100% success rate of wireless communication over 75 feet with <1% false positive and false negative rates of single drop deliveries, thus providing a viable solution for eyedrop monitoring for glaucoma patients.