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

[This corrects the article DOI: 10.1371/journal.pone.0269231.].

A deductive thematic analysis of nurses with job-related problems who completed suicide during the early COVID-19 pandemic: A preliminary report.

BACKGROUND: Prior to the novel coronavirus (COVID-19) pandemic, nurses died by suicide more frequently than the general population. Antecedents prior to death include known job problems, such as disciplinary action; diversion of medications; inability to work due to chronic pain; and physical and mental illness. AIM: The aim of this study was to explore the suicide experience of nurses who died with known job-related problems during the early phase of the COVID-19 pandemic compared to what has been previously described. METHOD: Deductive reflexive thematic analysis was used to analyze narratives of nurses with known job problems who died by suicide from the Centers for Disease Control and Prevention's National Violent Death Reporting System. RESULTS: Forty-three nurses with known job-related problems completed suicide between March and December 2020. Factors associated with death were similar to previous findings with notable exceptions, increased prevalence of suicidal ideation and post-traumatic stress prior to the event. Pandemic-specific issues were noted including reduction in hours, fear of disease transmission, civil unrest, and grief-related trauma. LINKING EVIDENCE TO ACTION: Suicide prevention programs need to address both institutional and individual factors associated with nurse suicide. As previously recommended, transitions into retirement and job loss are vulnerable times warranting psychological support. Further, strategies to reduce the impact of stressors and increase support for nurses are needed at the organizational level. A systems level approach to hardwire coping strategies is indicated pre-licensure and throughout nurses' careers. A new focus on how to process personal and professional grief is warranted. Resources are needed for nurses traumatized by life (rape, childhood trauma) or work-related experiences.

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.

Reflexive thematic analysis of job-related problems associated with pharmacist suicide, 2003-2019.

BACKGROUND: Few qualitative studies have focused on suicide and specific job-related problems associated with suicide in pharmacists. Greater knowledge of specific work-related stressors amongst pharmacists could inform suicide prevention strategies. OBJECTIVE: To identify job-related stressors associated with pharmacist suicides and compare stressors to those previously reported in physicians and nurses. METHODS: Free-text law enforcement and medical examiner data for pharmacist suicides were extracted from the National Violent Death Registry (NVDRS) for 2003-2019. Reflexive thematic analysis was deployed via a deductive approach utilizing codes and themes found in previous research on nurse and physician suicides. New codes were also identified through inductive coding. RESULTS: A total of 291,872 suicides occurred between 2003 and 2019, of which 392 were pharmacist deaths. Of these, 62 pharmacist suicides were coded with job-related problems. Almost all deductive themes/codes extracted from nurses and physicians were present in pharmacists. Common codes found in the pharmacist dataset that were also found previously in physicians and nurses were: history of mental health, substance use disorder, hopelessness impending or proceeding job loss, and access to lethal weapons and/or drugs. Novel codes were added through inductive content analysis. Codes novel to pharmacists were: verbalized suicidal ideation (SI) or intent, diversion for the purpose of suicide, and the fear of job loss. Disciplinary action at the institutional level was associated with the fear of job loss and cited as the event triggering suicide completion. CONCLUSION: Pharmacists have similar job-related stressors associated with suicide as physicians and nurses. Evaluating the process of disciplinary action is warranted. Future research is indicated to evaluate causal relationship between work-related stressors and mental health outcomes leading to suicide in pharmacists.

Entangled: A mixed method analysis of nurses with mental health problems who die by suicide.

Nurses die by suicide at a higher rate than the general population. Previous studies have observed mental health problems, including substance use, as a prominent antecedent before death. The purpose of this study was to explore the characteristics of nurses who died by suicide documented in the death investigation narratives from the National Violent Death Reporting System from 2003 to 2017 using thematic analysis and natural language processing. One thousand three hundred and fifty-eight subjects met these inclusion criteria. Narratives from 601 subjects were thematically analyzed and 2544 individual narratives were analyzed using natural language processing. The analyses revealed five themes: "mental health treatment," "poor general health and chronic pain," "substance use," "worsening mental health after bereavement," and "repeating a family member's suicide." Mental health/substance use, chronic illness, and chronic pain were seen to coexist in a complex, interdependent manner that appeared to be entangled in the nurses' narratives before death. These findings echo the need for reducing the stigmatization of mental health problems in nursing and removing barriers to help-seeking behaviors as early preventative interventions. Future research is needed to determine if a comprehensive healthcare integration approach to address these entangled problems would reduce suicide vulnerability in nurses and improve their quality of life.

Social Determinants of Health Data Availability for Patients with Eye Conditions.

Purpose: To quantify and characterize social determinants of health (SDoH) data coverage using single-center electronic health records (EHRs) and the National Institutes of Health All of Us research program. Design: Retrospective cohort study from June 2014 through June 2021. Participants: Adults 18 years of age or older with a diagnosis of diabetic retinopathy, glaucoma, cataracts, or age-related macular degeneration. Methods: For All of Us, research participants completed online survey forms as part of a nationwide prospective cohort study. In local EHRs, patients were selected based on diagnosis codes. Main Outcome Measures: Social determinants of health data coverage, characterized by the proportion of each disease cohort with available data regarding demographics and socioeconomic factors. Results: In All of Us, we identified 23 806 unique adult patients, of whom 2246 had a diagnosis of diabetic retinopathy, 13 448 had a diagnosis of glaucoma, 6634 had a diagnosis of cataracts, and 1478 had a diagnosis of age-related macular degeneration. Survey completion rates were high (99.5%-100%) across all cohorts for demographic information, overall health, income, education, and lifestyle. However, health care access (12.7%-29.4%), housing (0.7%-1.1%), social isolation (0.2%-0.3%), and food security (0-0.1%) showed significantly lower response rates. In local EHRs, we identified 80 548 adult patients, of whom 6616 had a diagnosis of diabetic retinopathy, 26 793 had a diagnosis of glaucoma, 40 427 had a diagnosis of cataracts, and 6712 had a diagnosis of age-related macular degeneration. High data coverage was found across all cohorts for variables related to tobacco use (82.84%-89.07%), alcohol use (77.45%-83.66%), and intravenous drug use (84.76%-93.14%). However, low data coverage (< 50% completion) was found for all other variables, including education, finances, social isolation, stress, physical activity, food insecurity, and transportation. We used chi-square testing to assess whether the data coverage varied across different disease cohorts and found that all fields varied significantly (P < 0.001). Conclusions: The limited and highly variable data coverage in both local EHRs and All of Us highlights the need for researchers and providers to develop SDoH data collection strategies and to assemble complete datasets.

Thematic analysis and natural language processing of job-related problems prior to physician suicide in 2003-2018.

INTRODUCTION: Although previous studies have consistently demonstrated that physicians are more likely than non-physicians to experience work-related stressors prior to suicide, the specific nature of these stressors remains unknown. The current study aimed to better characterize job-related problems prior to physician suicide. METHODS: The study utilized a mixed methods approach combining thematic analysis and natural language processing to develop themes representing death investigation narratives of 200 physician suicides with implicated job problems in the National Violent Death Reporting System database between 2003 and 2018. RESULTS: Through thematic analysis, six overarching themes were identified: incapacity to work due to deterioration of physical health, substance use jeopardizing employment, interaction between mental health and work-related issues, relationship conflict affecting work, legal problems leading to work-related stress, and increased financial stress. Natural language processing analysis confirmed five of these themes and elucidated important subthemes. CONCLUSIONS: This is the first known study that integrated thematic analysis and natural language processing to characterize work-related stressors preceding physician suicide. The findings highlight the importance of bolstering systemic support for physicians experiencing job problems associated with their physical and mental health, substance use, relationships, legal matters, and finances in suicide prevention efforts.

Novel Association between Opioid Use and Increased Risk of Retinal Vein Occlusion Using the National Institutes of Health All of Us Research Program.

Purpose: To assess for risk factors for retinal vein occlusion (RVO) among participants in the National Institutes of Health All of Us database, particularly social risk factors that have not been well studied, including substance use. Design: Retrospective, case-control study. Participants: Data were extracted for 380 adult participants with branch retinal vein occlusion (BRVO), 311 adult participants with central retinal vein occlusion (CRVO), and 1520 controls sampled among 311 640 adult participants in the All of Us database. Methods: Data were extracted regarding demographics, comorbidities, income, housing, insurance, and substance use. Opioid use was defined by relevant diagnosis and prescription codes, with prescription use > 30 days. Controls were sampled at a 4:1 control to case ratio from a pool of individuals aged > 18 years without a diagnosis of RVO and proportionally matched to the demographic distribution of the 2019 U.S. census. Multivariable logistic regression identified medical and social determinants significantly associated with BRVO or CRVO. Statistical significance was defined as P < 0.05. Main Outcome Measure: Development of BRVO or CRVO based on diagnosis codes. Results: Among patients with BRVO, the mean (standard deviation) age was 70.1 (10.5) years. The majority (53.7%) were female. Cases were diverse; 23.7% identified as Black, and 18.4% identified as Hispanic or Latino. Medical risk factors including glaucoma (odds ratio [OR], 3.29; 95% confidence interval [CI], 2.22-4.90; P < 0.001), hypertension (OR, 2.15; 95% CI, 1.49-3.11; P < 0.001), and diabetes mellitus (OR, 1.68; 95% CI, 1.18-2.38; P = 0.004) were re-demonstrated to be associated with BRVO. Black race (OR, 2.64; 95% CI, 1.22-6.05; P = 0.017) was found to be associated with increased risk of BRVO. Past marijuana use (OR, 0.68; 95% CI, 0.50-0.92; P = 0.013) was associated with decreased risk of BRVO; however, opioid use (OR, 1.98; 95% CI, 1.41-2.78; P < 0.001) was associated with a significantly increased risk of BRVO. Similar associations were found for CRVO. Conclusions: Understanding RVO risk factors is important for primary prevention and improvement in visual outcomes. This study capitalizes on the diversity and scale of a novel nationwide database to elucidate a previously uncharacterized association between RVO and opioid use.

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

PURPOSE: Inadequacies 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). METHODS: We 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<0.05. RESULTS: The 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, and 19.3% 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). CONCLUSIONS: Nationwide 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.

Longitudinal analysis of suicides among pharmacists during 2003-2018.

BACKGROUND: Suicide is one of the leading causes of death worldwide, and estimates of suicide among health professionals are higher than the general population. High rates of suicide among physicians and nurses have been described previously, but there is a lack of data for suicides completed by pharmacists. OBJECTIVE: The purpose of this study was to quantify the incidence, means, and characteristics of pharmacist suicides in the United States. METHODS: Data were obtained from the Centers for Disease Control and Prevention's National Violent Death Reporting System (NVDRS) for the years 2003-2018. The dataset contained all suicides, coded by occupation, reported by medical examiners and law enforcement from 39 states and Washington DC and Puerto Rico. Suicide characteristics were compared between pharmacists and nonpharmacists. Age-adjusted rates were calculated for 2004, 2009, and 2014. RESULTS: During 2003-2018, the NVDRS contained 316 pharmacist suicides compared with 213,146 nonpharmacist suicides. The age-adjusted rates per 100,000 people were 19.6, 20.1, and 18.2 for 2004, 2009 and 2014, respectively. The most common means of suicide was firearm. Associated factors for suicide included job problems, current mental illness treatment, and suicide note. CONCLUSION: Suicide rates among pharmacists are higher than the general population. Future research is needed to evaluate the context of job-related problems to mitigate risk. Encouraging help-seeking behaviors to identify and treat pharmacist depression is warranted.

Physician death by suicide in the United States: 2012-2016.

Reports of incidence of physician suicide in the United States (US) are outdated. The aims of this research were to assess incidence, methods, and associated risk factors of physicians compared to non-physicians in the general US population. Retrospective suicide data (victim age 25 and over) from the 2012-2016 National Violent Death Reporting System were analyzed to test for differences in rates, methods, and risk factors of male and female physicians to non-physicians. The dataset included 498 physician suicides (403 males and 95 females) and 74,420 non-physicians (57,188 males and 17,232 females). No significant difference was found in suicide incidence between gender and age-adjusted physicians vs. non-physicians, though the female physician rate of suicide appeared higher than female non-physicians. The male to female physician ratio of suicide was about 2:1, whereas the ratio in non-physicians was closer to 4:1. Female physicians used poisoning and hanging most often as a method of suicide, where males used firearms. Depressed mood (as perceived by self or others), mental health problems (defined by a diagnosis of depression, a prescribed antidepressants or toxicology report of antidepressants), poor general medical health, and work-related stressors were more frequently associated with physician than with non-physician suicides. In conclusion, results suggest a possible heightened risk to female physicians, which warrants further investigation. Several physician-specific modifiable suicide risk factors present opportunities for prevention.

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.

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.