Healthcare Access and Utilization Among Glaucoma Patients in a Nationwide Cohort

PrcisDespite having lower socioeconomic status on several measures, glaucoma patients do not report more barriers to healthcare access and utilization than non-glaucoma patients.PurposeTo characterize measures of socioeconomic status and barriers to healthcare access and utilization between patients with and without a diagnosis of glaucoma.MethodsPatients aged 65 years and over who enrolled in the NIH All of Us Research Program, a nationwide longitudinal cohort, were extracted. We analyzed demographic information and several measures of socioeconomic status and healthcare access and utilization. Survey responses were compared by glaucoma status (any type) with Pearson χ 2 tests, univariable logistic regression, and multivariable logistic regression adjusting for age, gender, race/ethnicity, and insurance status.ResultsOf the 49,487 patients who answered at least 1 question on the All of Us Healthcare Access and Utilization Survey, 4441 (9.0%) had a diagnosis of glaucoma. Majority of the cohort was female (28,162, 56.9%) and nonHispanic White (42,008, 84.9%). Glaucoma patients were observed to have lower rates of education ( P =0.004), employment ( P <0.001), and home ownership ( P <0.001) on χ 2 tests. On multivariable logistic regression models, those with glaucoma were significantly more likely to speak to an eye doctor (Odds ratio: 2.46; 95% confidence interval: 2.16 to 2.81) and significantly less likely to have trouble affording eyeglasses (OR: 0.85 95% CI: 0.72 to 0.99) in the prior year than those without a diagnosis of glaucoma. No significant association was found for other measures of healthcare access and utilization by glaucoma status.ConclusionAlthough glaucoma patients aged 65 years and over fared worse on several measures of socioeconomic status, no significant difference was found in measures of healthcare access and utilization

Gender Disparities in Depression, Stress, and Social Support Among Glaucoma Patients

PurposeTo understand differences in measures of depression, stress, and social support by gender among those diagnosed with glaucoma.MethodsWe obtained a cohort of glaucoma patients (any type) ages 18 years and over who answered the COVID-19 Participant Experience (COPE) survey of the NIH All of Us Research Program. We analyzed several measures of depression, stress, and social support by gender. Logistic regression was used to evaluate the association among reported stress associated with social distancing, depression (using Patient Health Questionnaire-9 [PHQ-9] scores), and measures of social support by self-reported gender, with men as the reference group. Multivariable models were adjusted for age, race and ethnicity, health insurance status, education, and income.ResultsOf 3633 glaucoma patients, 56.8% were women. Many patients had a PHQ-9 score > 4 (33.3%), indicating mild, moderate, or severe depression. In multivariable models, women were significantly more likely to report a PHQ-9 score > 4 (odds ratio [OR] = 1.40; 95% confidence interval [CI], 1.20-1.62; P < 0.001) and some or a lot of stress (OR = 1.34; 95% CI, 1.14-1.57; P < 0.001) compared with men. Further, women were significantly less likely to report having help all or most of the time if they needed someone to prepare meals (OR = 0.78; 95% CI, 0.67-0.92; P = 0.002) or perform daily chores (OR = 0.79; 95% CI, 0.67-0.91; P = 0.003) than men.ConclusionsWomen with glaucoma were more likely to experience depression and stress and were less likely to have social support on some measures than men.Translational relevanceThe disproportionate burden of psychosocial factors among women may complicate glaucoma management

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

BackgroundThe 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.MethodsA 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.ResultsOf 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.ConclusionsGlaucoma 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 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

Predicting Mortality in Critical Care Patients with Fungemia Using Structured and Unstructured Data*

Fungemia is a life-threatening infection, but predictive models of in-patient mortality in this infection are few. In this study, we developed models predicting all-cause in-hospital mortality among 265 fungemic patients in the Medical Information Mart for Intensive Care (MIMIC-III) database using both structured and unstructured data. Structured data models included multivariable logistic regression, extreme gradient boosting, and stacked ensemble models. Unstructured data models were developed using Amazon Comprehend Medical and BioWordVec embeddings in logistic regression, convolutional neural networks (CNNs), and recurrent neural networks (RNNs). We evaluated models trained on all notes, notes from only the first three days of hospitalization, and models trained on only physician notes. The best-performing structured data model was a multivariable logistic regression model that achieved an accuracy of 0.74 and AUC of 0.76. Liver disease, acute renal failure, and intubation were some of the top features driving prediction in multiple models. CNNs using unstructured data achieved similar performance even when trained with notes from only the first three days of hospitalization. The best-performing unstructured data models used the Amazon Comprehend Medical document classifier and CNNs, achieving accuracy ranging from 0.99-1.00, and AUCs of 1.00. Therefore, unstructured data - particularly notes composed by physicians - offer added predictive value over models based on structured data alone

Epidemiology and factors associated with cannabis use among patients with glaucoma in the All of Us Research Program

Purpose: To examine the epidemiology and factors of cannabis use among open-angle glaucoma (OAG) patients. Methods: In this cross-sectional study, OAG participants in the All of Us database were included. Cannabis ever-users were defined based on record of cannabis use. Demographic and socioeconomic data were collected and compared between cannabis ever-users and never-users using Chi-Square tests and logistic regression. Odds ratios (OR) of potential factors associated with cannabis use were examined in univariable and multivariable models. Results: Among 3723 OAG participants, 1436 (39%) were cannabis ever-users. The mean (SD) age of never-users and ever-users was 72.9 (10.4) and 69.2 (9.6) years, respectively (P < 0.001). Compared to never-users, Black (34%) and male (55%) participants were better represented in ever-users, while Hispanic or Latino participants (6%) were less represented (P < 0.001). Diversity was also observed in socioeconomic characteristics including marital status, housing security, and income/education levels. A higher percentage of ever-users had a degree ≥12 grades (91%), salaried employment (26%), housing insecurity (12%), and history of cigar smoking (48%), alcohol consumption (96%), and other substance use (47%) (P < 0.001). In the multivariable analysis, Black race (OR [95% CI] = 1.33 [1.06, 1.68]), higher education (OR = 1.19 [1.07, 1.32]), and history of nicotine product smoking (OR: 2.04–2.83), other substance use (OR = 8.14 [6.63, 10.04]), and alcohol consumption (OR = 6.80 [4.45, 10.79]) were significant factors associated with cannabis use. Increased age (OR = 0.96 [0.95, 0.97]), Asian race (OR = 0.18 [0.09, 0.33]), and Hispanic/Latino ethnicity (OR = 0.43 [0.27, 0.68]) were associated with decreased odds of use (P < 0.02). Conclusions: This study elucidated the previously uncharacterized epidemiology and factors associated with cannabis use among OAG patients, which may help to identify patients requiring additional outreach on unsupervised marijuana use

Epidemiology and factors associated with cannabis use among patients with glaucoma in the All of Us Research Program

PurposeTo examine the epidemiology and factors of cannabis use among open-angle glaucoma (OAG) patients.MethodsIn this cross-sectional study, OAG participants in the All of Us database were included. Cannabis ever-users were defined based on record of cannabis use. Demographic and socioeconomic data were collected and compared between cannabis ever-users and never-users using Chi-Square tests and logistic regression. Odds ratios (OR) of potential factors associated with cannabis use were examined in univariable and multivariable models.ResultsAmong 3723 OAG participants, 1436 (39%) were cannabis ever-users. The mean (SD) age of never-users and ever-users was 72.9 (10.4) and 69.2 (9.6) years, respectively (P&nbsp;&lt;&nbsp;0.001). Compared to never-users, Black (34%) and male (55%) participants were better represented in ever-users, while Hispanic or Latino participants (6%) were less represented (P&nbsp;&lt;&nbsp;0.001). Diversity was also observed in socioeconomic characteristics including marital status, housing security, and income/education levels. A higher percentage of ever-users had a degree ≥12 grades (91%), salaried employment (26%), housing insecurity (12%), and history of cigar smoking (48%), alcohol consumption (96%), and other substance use (47%) (P&nbsp;&lt;&nbsp;0.001). In the multivariable analysis, Black race (OR [95% CI]&nbsp;=&nbsp;1.33 [1.06, 1.68]), higher education (OR&nbsp;=&nbsp;1.19 [1.07, 1.32]), and history of nicotine product smoking (OR: 2.04-2.83), other substance use (OR&nbsp;=&nbsp;8.14 [6.63, 10.04]), and alcohol consumption (OR&nbsp;=&nbsp;6.80 [4.45, 10.79]) were significant factors associated with cannabis use. Increased age (OR&nbsp;=&nbsp;0.96 [0.95, 0.97]), Asian race (OR&nbsp;=&nbsp;0.18 [0.09, 0.33]), and Hispanic/Latino ethnicity (OR&nbsp;=&nbsp;0.43 [0.27, 0.68]) were associated with decreased odds of use (P&nbsp;&lt;&nbsp;0.02).ConclusionsThis study elucidated the previously uncharacterized epidemiology and factors associated with cannabis use among OAG patients, which may help to identify patients requiring additional outreach on unsupervised marijuana use

Associations between healthcare utilization and access and diabetic retinopathy complications using All of Us nationwide survey data.

PurposeInadequacies in healthcare access and utilization substantially impact outcomes for diabetic patients. The All of Us database offers extensive survey data pertaining to social determinants that is not routinely available in electronic health records. This study assesses whether social determinants were associated with an increased risk of developing proliferative diabetic retinopathy or related complications (e.g. related diagnoses or procedures).MethodsWe identified 729 adult participants in the National Institutes of Health All of Us Research Program data repository with diabetic retinopathy (DR) who answered survey questions pertaining to healthcare access and utilization. Electronic health record data regarding co-morbidities, laboratory values, and procedures were extracted. Multivariable logistic regression with bi-directional stepwise variable selection was performed from a wide range of predictors. Statistical significance was defined as p&lt;0.05.ResultsThe mean (standard deviation) age of our cohort was 64.9 (11.4) years. 15.2% identified as Hispanic or Latino, 20.4% identified as Black, 60.6% identified as White, 2.74% identified as Asian, and 16.6% identified as Other. 10-20% of patients endorsed several reasons for avoiding or delaying care, including financial concerns and lack of access to transportation. Additional significant social determinants included race and religion discordance between healthcare provider and patient (odds ratio [OR] 1.20, 95% confidence interval [CI] 1.02-1.41, p = 0.03) and caregiver responsibilities toward others (OR 3.14, 95% CI 1.01-9.50, p = 0.04).ConclusionsNationwide data demonstrate substantial barriers to healthcare access among DR patients. In addition to financial and social determinants, race and religion discordance between providers and patients may increase the likelihood of PDR and related complications

Assessing Usability of Smartwatch Digital Health Devices for Home Blood Pressure Monitoring among Glaucoma Patients

Glaucoma is a leading cause of blindness worldwide. Blood pressure (BP) dysregulation is a known risk factor, and home-based BP monitoring is increasingly used, but the usability of digital health devices to measure BP among glaucoma patients is not well studied. There may be particular usability challenges among this group, given that glaucoma disproportionately affects the elderly and can cause visual impairment. Therefore, the goal of this mixed-methods study was to assess the usability of a smart watch digital health device for home BP monitoring among glaucoma patients. Adult participants were recruited and given a smartwatch blood pressure monitor for at-home use. The eHEALS questionnaire was used to determine baseline digital health literacy. After a week of use, participants assessed the usability of the BP monitor and related mobile app using the Post-study System Usability Questionnaire (PSSUQ) and the System Usability Scale (SUS), standardized instruments to measure usability in health information technology interventions. Variations in scores were evaluated using ANOVA and open-ended responses about participants’ experience were analyzed thematically. Overall, usability scores corresponded to the 80th–84th percentile, although older patients endorsed significantly worse usability based on quantitative scores and additionally provided qualitative feedback describing some difficulty using the device. Usability for older patients should be considered in the design of digital health devices for glaucoma given their disproportionate burden of disease and challenges in navigating digital health technologies, although the overall high usability scores for the device demonstrates promise for future clinical applications in glaucoma risk stratification

Assessing Usability of Smartwatch Digital Health Devices for Home Blood Pressure Monitoring among Glaucoma Patients.

Glaucoma is a leading cause of blindness worldwide. Blood pressure (BP) dysregulation is a known risk factor, and home-based BP monitoring is increasingly used, but the usability of digital health devices to measure BP among glaucoma patients is not well studied. There may be particular usability challenges among this group, given that glaucoma disproportionately affects the elderly and can cause visual impairment. Therefore, the goal of this mixed-methods study was to assess the usability of a smart watch digital health device for home BP monitoring among glaucoma patients. Adult participants were recruited and given a smartwatch blood pressure monitor for at-home use. The eHEALS questionnaire was used to determine baseline digital health literacy. After a week of use, participants assessed the usability of the BP monitor and related mobile app using the Post-study System Usability Questionnaire (PSSUQ) and the System Usability Scale (SUS), standardized instruments to measure usability in health information technology interventions. Variations in scores were evaluated using ANOVA and open-ended responses about participants' experience were analyzed thematically. Overall, usability scores corresponded to the 80th-84th percentile, although older patients endorsed significantly worse usability based on quantitative scores and additionally provided qualitative feedback describing some difficulty using the device. Usability for older patients should be considered in the design of digital health devices for glaucoma given their disproportionate burden of disease and challenges in navigating digital health technologies, although the overall high usability scores for the device demonstrates promise for future clinical applications in glaucoma risk stratification