Effect of Screening for Undiagnosed Atrial Fibrillation on Stroke Prevention.

BACKGROUND: Atrial fibrillation (AF) often remains undiagnosed, and it independently raises the risk of ischemic stroke, which is largely reversible by oral anticoagulation. Although randomized trials using longer term screening approaches increase identification of AF, no studies have established that AF screening lowers stroke rates. OBJECTIVES: To address this knowledge gap, the GUARD-AF (Reducing Stroke by Screening for Undiagnosed Atrial Fibrillation in Elderly Individuals) trial screened participants in primary care practices using a 14-day continuous electrocardiographic monitor to determine whether screening for AF coupled with physician/patient decision-making to use oral anticoagulation reduces stroke and provides a net clinical benefit compared with usual care. METHODS: GUARD-AF was a prospective, parallel-group, randomized controlled trial designed to test whether screening for AF in people aged ≥70 years using a 14-day single-lead continuous electrocardiographic patch monitor could identify patients with undiagnosed AF and reduce stroke. Participants were randomized 1:1 to screening or usual care. The primary efficacy and safety outcomes were hospitalization due to all-cause stroke and bleeding, respectively. Analyses used the intention-to-treat population. RESULTS: Enrollment began on December 17, 2019, and involved 149 primary care sites across the United States. The COVID-19 pandemic led to premature termination of enrollment, with 11,905 participants in the intention-to-treat population. Median follow-up was 15.3 months (Q1-Q3: 13.8-17.6 months). Median age was 75 years (Q1-Q3: 72-79 years), and 56.6% were female. The risk of stroke in the screening group was 0.7% vs 0.6% in the usual care group (HR: 1.10; 95% CI: 0.69-1.75). The risk of bleeding was 1.0% in the screening group vs 1.1% in the usual care group (HR: 0.87; 95% CI: 0.60-1.26). Diagnosis of AF was 5% in the screening group and 3.3% in the usual care group, and initiation of oral anticoagulation after randomization was 4.2% and 2.8%, respectively. CONCLUSIONS: In this trial, there was no evidence that screening for AF using a 14-day continuous electrocardiographic monitor in people ≥70 years of age seen in primary care practice reduces stroke hospitalizations. Event rates were low, however, and the trial did not enroll the planned sample size.(Reducing Stroke by Screening for Undiagnosed Atrial Fibrillation in Elderly Individuals [GUARD-AF]; NCT04126486).

Atrial Fibrillation Burden on a 14-Day ECG Monitor: Findings From the GUARD-AF Trial Screening Arm.

BACKGROUND: The "burden" of atrial fibrillation (AF) detected by screening likely influences stroke risk, but the distribution of burden is not well described. OBJECTIVES: This study aims to determine the frequency of AF and the distribution of AF burden found when screening individuals ≥70 years of age with a 14-day electrocardiograph monitor. METHODS: This is a cohort study of the screening arm of a randomized AF screening trial among those ≥70 years of age without a prior AF diagnosis (between 2019 and 2021). Screening was performed with a 14-day continuous electrocardiogram patch monitor. RESULTS: Analyzable patches were returned by 5,684 (95%) of screening arm participants; the median age was 75 years (Q1-Q3: 72-78 years), 57% were female, and the median CHA2DS2-VASc score was 3 (Q1-Q3: 2-4). AF was detected in 252 participants (4.4%); 29 (0.5%) patients had continuous AF and 223 (3.9%) had paroxysmal AF. Among those with paroxysmal AF, the average indices of AF burden were of low magnitude with right-skewed distributions. The median percent time in AF was 0.46% (Q1-Q3: 0.02%-2.48%), or 75 (Q1-Q3: 3-454) minutes, and the median longest episode was 38 (Q1-Q3: 2-245) minutes. The upper quartile threshold of 2.48% time in AF corresponded to 7.6 hours. Age greater than 80 years was associated with screen-detected AF in our multivariable model (OR: 1.46; 95% CI: 1.06-2.02). CONCLUSIONS: Most AF detected in these older patients was very low burden. However, one-quarter of those with AF had multiple hours of AF, raising concern about stroke risk. These findings have implications for targeting populations for AF screening trials and for responding to heart rhythm alerts from mobile devices (GUARD-AF [A Study to Determine if Identification of Undiagnosed Atrial Fibrillation in People at least 70 Years of Age Reduces the Risk of Stroke]; NCT04126486).

Risk of Atherosclerotic Cardiovascular Disease Hospitalizations after COPD Hospitalization among Older Adults.

BACKGROUND: Meta-analyses have suggested the risk of cardiovascular disease (CVD) events is significantly higher after a chronic obstructive pulmonary disease (COPD) exacerbation. However, many of these studies have included a broad array of CVD events or have been limited to highly selected patient populations potentially not generalizable to the broader population of COPD. METHODS: We assessed the risk of atherosclerotic cardiovascular disease (ASCVD)hospitalizations after COPD hospitalization compared to before COPD hospitalization and identified patient factors associated with ASCVD hospitalizations after COPD hospitalization. This retrospective cohort study used claims data from 920,550 Medicare beneficiaries hospitalized for COPD from 2016-2019 in the US. The primary outcome was risk of a ASCVD hospitalization composite outcome (myocardial infarction, percutaneous coronary intervention, coronary artery by-pass graft surgery, stroke, or transient ischemic attack) in the 30-days and 1 year after-COPD hospitalization relative to the same time period before-COPD hospitalization. Time in the before- and after-COPD hospitalization time periods to a composite ASCVD hospitalization outcome were modeled using an extension of the Cox Proportional-Hazards model, the Anderson-Gill model with adjustment for patient characteristics. Additional analyses evaluated for interactions in subgroups associated with the composite ASCVD hospitalization outcome. RESULTS: Among 920,550 patients in the 30-day and 1-year cohorts, (mean age, 73-74 years) the hazard ratio estimate (HR; 95% CI) for the composite ASCVD hospitalization outcome after-COPD hospitalization vs before-COPD hospitalization for the 30-day cohort was 0.99 (0.93, 1.05; p = 0.67) and for the 1-year cohort was 0.99 (0.97, 1.02; p = 0.53) following adjustment. We observed 3 subgroups that were significantly associated with higher risk for ASCVD hospitalizations 1 year after COPD hospitalization: 76+ years old, women, COPD hospitalization severity. CONCLUSION: Among Medicare beneficiaries hospitalized for COPD, the risk of ASCVD hospitalizations was not significantly increased 30-day or 1-year after COPD-hospitalization relative to before-COPD hospitalization. In sub-group analyses, we identified age 76+ years old, female sex, and COPD hospitalization severity as high risk subgroups with increased risk of ASCVD events 1-year after-COPD hospitalization. Further research is needed to characterize the COPD exacerbation populations at highest ASCVD hospitalization risk.

Association between characteristics of employing healthcare facilities and healthcare worker infection rates and psychosocial experiences during the COVID-19 pandemic.

BACKGROUND: Healthcare facility characteristics, such as ownership, size, and location, have been associated with patient outcomes. However, it is not known whether the outcomes of healthcare workers are associated with the characteristics of their employing healthcare facilities, particularly during the COVID-19 pandemic. METHODS: This was an analysis of a nationwide registry of healthcare workers (the Healthcare Worker Exposure Response and Outcomes (HERO) registry). Participants were surveyed on their personal, employment, and medical characteristics, as well as our primary study outcomes of COVID-19 infection, access to personal protective equipment, and burnout. Participants from healthcare sites with at least ten respondents were included, and these sites were linked to American Hospital Association data to extract information about sites, including number of beds, teaching status, urban/rural location, and for-profit status. Generalized estimating equations were used to estimate linear regression models for the unadjusted and adjusted associations between healthcare facility characteristics and outcomes. RESULTS: A total of 8,941 healthcare workers from 97 clinical sites were included in the study. After adjustment for participant demographics, healthcare role, and medical comorbidities, facility for-profit status was associated with greater odds of COVID-19 diagnosis (aOR 1.76, 95% CI 1.02-3.03, p = .042). Micropolitan location was associated with decreased odds of COVID-19 infection after adjustment (aOR = 0.42, 95% CI 0.24, 0.71, p = .002. For-profit facility status was associated with decreased odds of burnout after adjustment (aOR = 0.53, 95% CI 0.29-0.98), p = .044). CONCLUSIONS: For-profit status of employing healthcare facilities was associated with greater odds of COVID-19 diagnosis but decreased odds of burnout after adjustment for demographics, healthcare role, and medical comorbidities. Future research to understand the relationship between facility ownership status and healthcare outcomes is needed to promote wellbeing in the healthcare workforce. TRIAL REGISTRATION: The registry was prospectively registered: ClinicalTrials.gov Identifier (trial registration number) NCT04342806, submitted April 8, 2020.

Neuropsychiatric Comorbidities and Psychotropic Medication Use in Medicare Beneficiaries With Dementia by Sex and Race.

BACKGROUND: Neuropsychiatric symptoms affect the majority of dementia patients. Past studies report high rates of potentially inappropriate prescribing of psychotropic medications in this population. We investigate differences in neuropsychiatric diagnoses and psychotropic medication prescribing in a local US cohort by sex and race. METHODS: We utilize Medicare claims and prescription fill records in a cohort of 100% Medicare North and South Carolina beneficiaries ages 50 and above for the year 2017 with a dementia diagnosis. We identify dementia and quantify diagnosis of anxiety, depression and psychosis using validated coding algorithms. We search Medicare claims for antianxiety, antidepressant and antipsychotic medications to determine prescriptions filled. RESULTS: Anxiety and depression were diagnosed at higher rates in White patients; psychosis at higher rates in Black patients. (P < .001) Females were diagnosed with anxiety, depression and psychosis at higher rates than males (P < .001) and filled more antianxiety and antidepressant medications than males. (P < .001) Black and Other race patients filled more antipsychotic medications for anxiety, depression and psychosis than White patients. (P < .001) Antidepressants were prescribed at higher rates than antianxiety or antipsychotic medications across all patients and diagnoses. Of patients with no neuropsychiatric diagnosis, 11.4% were prescribed an antianxiety medication, 22.8% prescribed an antidepressant and 7.6% prescribed an antipsychotic. CONCLUSIONS: The high fill rate of antianxiety (benzodiazepine) medications in dementia patients, especially females is a concern. Patients are prescribed psychotropic medications at high rates. This practice may represent potentially inappropriate prescribing. Patient/caregiver education with innovative community outreach and care delivery models may help decrease medication use.

Beta amyloid PET scans for dementia diagnoses: Practice and research implications from CARE-IDEAS.

Beta amyloid PET scans are a minimally invasive biomarker that may inform Alzheimer's disease (AD) diagnosis. The Caregiver's Reactions and Experience (CARE) study, an IDEAS supplement, aimed to understand experiences of PET scan recipients and their care partners regarding motivations for scans, reporting and interpreting results, and impact of results. Patients with mild cognitive impairment or dementia who agreed to join the CARE-IDEAS study and their care partners participated in a baseline survey and follow-up survey approximately 18 months later, supplemented by in-depth qualitative interviews with subsets of participants. Patients who received scans and volunteered for follow-up research were more likely to be male, better educated, and have higher income than the general population. Survey information was merged with Medicare data. This article integrates findings from several CARE-IDEAS publications and provides implications for practice and research. Although most participants accurately reported scan results, they were often confused about their meaning for prognosis. Some participants reported distress with results, but there were no significant changes in measured depression, burden, or economic strain over time. Many respondents desired more information about prognosis and supportive resources. Scan results were not differentially associated with changes in service use over time. Findings suggest a need for carefully designed and tested tools for clinicians to discuss risks and benefits of scans and their results, and resources to support patients and care partners in subsequent planning. Learning of scan results provides a point-of-contact that should be leveraged to facilitate shared decision-making and person-centered longitudinal AD care.

Nursing Home Workers' Experience During the COVID-19 Pandemic.

PURPOSE: To understand nursing home workers' experience during the coronavirus disease 2019 (COVID-19) pandemic and investigate the prevalence of health-related quality of life, emotional distress, job satisfaction, and the impact of the pandemic. METHOD: The Healthcare Worker Exposure Response and Outcomes (HERO) Registry served as the data source for this descriptive cross-sectional analysis. Recruitment was conducted nationally. Eligible nursing home workers (N = 1,409) enrolled in the study online, self-reported demographic and employment characteristics, and completed electronic surveys. RESULTS: Nursing home workers reported overall good physical health, frequent depressive symptoms, burnout, and a high prevalence of feeling tired, stressed, having trouble sleeping, and feeling worried. Age and race were found to be positively associated with the impact of the pandemic. CONCLUSION: Findings demonstrate the difficulties and challenges nursing home workers faced during the COVID-19 pandemic. Future research needs to evaluate the relationships among nursing home workers' roles, mental health, depressive symptoms, and prevalence of burnout with a larger, more diverse sample. [Research in Gerontological Nursing, 17(3), 131-140.].

Racial Disparities in Low-Value Care in the Last Year of Life for Medicare Beneficiaries With Neurodegenerative Disease.

Background and Objectives: There are racial disparities in health care services received by patients with neurodegenerative diseases, but little is known about disparities in the last year of life, specifically in high-value and low-value care utilization. This study evaluated racial disparities in the utilization of high-value and low-value care in the last year of life among Medicare beneficiaries with dementia or Parkinson disease. Methods: This was a retrospective, population-based cohort analysis using data from North and South Carolina fee-for-service Medicare claims between 2013 and 2017. We created a decedent cohort of beneficiaries aged 50 years or older at diagnosis with dementia or Parkinson disease. Specific low-value utilization outcomes were selected from the Choosing Wisely initiative, including cancer screening, peripheral artery stenting, and feeding tube placement in the last year of life. Low-value outcomes included hospitalization, emergency department visits, neuroimaging services, and number of days receiving skilled nursing. High-value outcomes included receipt of occupational and physical therapy, hospice care, and medications indicated for dementia and/or Parkinson disease. Results: Among 70,650 decedents, 13,753 were Black, 55,765 were White, 93.1% had dementia, and 7.7% had Parkinson disease. Adjusting for age, sex, Medicaid dual enrollment status, rural vs urban location, state (NC and SC), and comorbidities, Black decedents were more likely to receive low-value care including colorectal cancer screening (adjusted hazard ratio [aHR] 1.46 [1.32-1.61]), peripheral artery stenting (aHR 1.72 [1.43-2.08]), and feeding tube placement (aHR 2.96 [2.70-3.24]) and less likely to receive physical therapy (aHR 0.73 [0.64-0.85)], dementia medications (aHR 0.90 [0.86-0.95]), or Parkinson disease medications (aHR 0.88 [0.75-1.02]) within the last year of life. Black decedents were more likely to be hospitalized (aHR 1.28 [1.25-1.32]), more likely to be admitted to skilled nursing (aHR 1.09 [1.05-1.13]), and less likely to be admitted to hospice (aHR 0.82 [0.79-0.85]) than White decedents. Discussion: We found racial disparities in care utilization among patients with neurodegenerative disease in the last year of life, such that Black decedents were more likely to receive specific low-value care services and less likely to receive high-value supportive care than White decedents, even after adjusting for health status and socioeconomic factors.

Elevated Amyloid-ß PET Scan and Cognitive and Functional Decline in Mild Cognitive Impairment and Dementia of Uncertain Etiology.

BACKGROUND: Elevated amyloid-ß (Aß) on positron emission tomography (PET) scan is used to aid diagnosis of Alzheimer's disease (AD), but many prior studies have focused on patients with a typical AD phenotype such as amnestic mild cognitive impairment (MCI). Little is known about whether elevated Aß on PET scan predicts rate of cognitive and functional decline among those with MCI or dementia that is clinically less typical of early AD, thus leading to etiologic uncertainty. OBJECTIVE: We aimed to investigate whether elevated Aß on PET scan predicts cognitive and functional decline over an 18-month period in those with MCI or dementia of uncertain etiology. METHODS: In 1,028 individuals with MCI or dementia of uncertain etiology, we evaluated the association between elevated Aß on PET scan and change on a telephone cognitive status measure administered to the participant and change in everyday function as reported by their care partner. RESULTS: Individuals with either MCI or dementia and elevated Aß (66.6% of the sample) showed greater cognitive decline compared to those without elevated Aß on PET scan, whose cognition was relatively stable over 18 months. Those with either MCI or dementia and elevated Aß were also reported to have greater functional decline compared to those without elevated Aß, even though the latter group showed significant care partner-reported functional decline over time. CONCLUSIONS: Elevated Aß on PET scan can be helpful in predicting rates of both cognitive and functional decline, even among cognitively impaired individuals with atypical presentations of AD.

Factors associated with anxiety during the first two years of the COVID-19 pandemic in the United States: An analysis of the COVID-19 Citizen Science study.

COVID-19 increased the prevalence of clinically significant anxiety in the United States. To investigate contributing factors we analyzed anxiety, reported online via monthly Generalized Anxiety Disorders-7 (GAD-7) surveys between April 2020 and May 2022, in association with self-reported worry about the health effects of COVID-19, economic difficulty, personal COVID-19 experience, and subjective social status. 333,292 anxiety surveys from 50,172 participants (82% non-Hispanic white; 73% female; median age 55, IQR 42-66) showed high levels of anxiety, especially early in the pandemic. Anxiety scores showed strong independent associations with worry about the health effects of COVID-19 for oneself or family members (GAD-7 score +3.28 for highest vs. lowest category; 95% confidence interval: 3.24, 3.33; p<0.0001 for trend) and with difficulty paying for basic living expenses (+2.06; 1.97, 2.15, p<0.0001) in multivariable regression models after adjusting for demographic characteristics, COVID-19 case rates and death rates, and personal COVID-19 experience. High levels of COVID-19 health worry and economic stress were each more common among participants reporting lower subjective social status, and median anxiety scores for those experiencing both were in the range considered indicative of moderate to severe clinical anxiety disorders. In summary, health worry and economic difficulty both contributed to high rates of anxiety during the first two years of the COVID-19 pandemic in the US, especially in disadvantaged socioeconomic groups. Programs to address both health concerns and economic insecurity in vulnerable populations could help mitigate pandemic impacts on anxiety and mental health.

Collecting patient-reported outcome measures in the electronic health record: Lessons from the NIH pragmatic trials Collaboratory.

The NIH Pragmatic Trials Collaboratory supports the design and conduct of 27 embedded pragmatic clinical trials, and many of the studies collect patient reported outcome measures as primary or secondary outcomes. Study teams have encountered challenges in the collection of these measures, including challenges related to competing health care system priorities, clinician's buy-in for adoption of patient-reported outcome measures, low adoption and reach of technology in low resource settings, and lack of consensus and standardization of patient-reported outcome measure selection and administration in the electronic health record. In this article, we share case examples and lessons learned, and suggest that, when using patient-reported outcome measures for embedded pragmatic clinical trials, investigators must make important decisions about whether to use data collected from the participating health system's electronic health record, integrate externally collected patient-reported outcome data into the electronic health record, or collect these data in separate systems for their studies.

Post-traumatic stress disorder symptoms among healthcare workers during the COVID-19 pandemic: Analysis of the HERO Registry.

Little is known about the mental health consequences of the COVID-19 pandemic in healthcare workers (HCWs). Past literature has shown that chronic strain caused by pandemics can adversely impact a variety of mental health outcomes in HCWs. There is growing recognition of the risk of stress and loss of resilience to HCWs during the COVID-19 pandemic, although the risk of post-traumatic stress disorder (PTSD) symptoms in HCWs during the COVID-19 pandemic remains poorly understood. We wanted to understand the relationship between the COVID-19 pandemic and the risk of PTDS symptoms in HCWs during the COVID-19 pandemic. We surveyed 2038 health care workers enrolled in the Healthcare Worker Exposure Response & Outcomes (HERO) study, which is a large standardized national registry of health care workers. Participants answered questions about demographics, COVID-19 exposure, job burnout, and PTSD symptoms. We characterize the burden of PTSD symptoms among HCWs, and determined the association between high PTSD symptoms and race, gender, professional role, work setting, and geographic region using multivariable regression. In a fully adjusted model, we found that older HCWs were less likely to report high PTSD symptoms compared with younger HCWs. Additionally, we found that physicians were less likely to report high PTSD symptoms compared with nurses. These data add to the growing literature on increased risks of mental health challenges to healthcare workers during the COVID-19 pandemic.

Dementia and Parkinson's disease diagnoses in electronic health records vs. Medicare claims data: a study of 101,980 linked patients.

BACKGROUND: Medicare claims and electronic health record data are both commonly used for research and clinical practice improvement; however, it is not known how concordant diagnoses of neurodegenerative diseases (NDD, comprising dementia and Parkinson's disease) are in these data types. Therefore, our objective was to determine the sensitivity and specificity of neurodegenerative disease (NDD) diagnoses contained in structured electronic health record (EHR) data compared to Medicare claims data. METHODS: This was a retrospective cohort study of 101,980 unique patients seen at a large North Carolina health system between 2013-2017, which were linked to 100% North and South Carolina Medicare claims data, to evaluate the accuracy of diagnoses of neurodegenerative diseases in EHRs compared to Medicare claims data. Patients age > 50 who were enrolled in fee-for-service Medicare were included in the study. Patients were classified as having or not having NDD based on the presence of validated ICD-CM-9 or ICD-CM-10 codes associated with NDD or claims for prescription drugs used to treat NDD. EHR diagnoses were compared to Medicare claims diagnoses. RESULTS: The specificity of any EHR diagnosis of NDD was 99.0%; sensitivity was 61.3%. Positive predictive value and negative predictive value were 90.8% and 94.1% respectively. Specificity of an EHR diagnosis of dementia was 99.0%, and sensitivity was 56.1%. Specificity of an EHR diagnosis of PD was 99.7%, while sensitivity was 76.1%. CONCLUSIONS: More research is needed to investigate under-documentation of NDD in electronic health records relative to Medicare claims data, which has major implications for clinical practice (particularly patient safety) and research using real-world data.

Optimizing data integration in trials that use EHR data: lessons learned from a multi-center randomized clinical trial.

BACKGROUND: Despite great promise, trials that ascertain patient clinical data from electronic health records (EHR), referred to here as "EHR-sourced" trials, are limited by uncertainty about how existing trial sites and infrastructure can be best used to operationalize study goals. Evidence is needed to support the practical use of EHRs in contemporary clinical trial settings. MAIN TEXT: We describe a demonstration project that used EHR data to complement data collected for a contemporary multi-center pharmaceutical industry outcomes trial, and how a central coordinating center supported participating sites through the technical, governance, and operational aspects of this type of activity. We discuss operational considerations related to site selection, data extraction, site performance, and data transfer and quality review, and we outline challenges and lessons learned. We surveyed potential sites and used their responses to assess feasibility, determine the potential capabilities of sites and choose an appropriate data extraction strategy. We designed a flexible, multimodal approach for data extraction, enabling each site to either leverage an existing data source, create a new research datamart, or send all data to the central coordinating center to produce the requisite data elements. We evaluated site performance, as reflected by the speed of contracting and IRB approval, total patients enrolled, enrollment yield, data quality, and compared performance by data collection strategy. CONCLUSION: While broadening the type of sites able to participate in EHR-sourced trials may lead to greater generalizability and improved enrollment, sites with fewer technical resources may require additional support to participate. Central coordinating center support is essential to facilitate the execution of operational processes. Future work should focus on sharing lessons learned and creating reusable tools to facilitate participation of heterogeneous trial sites.

Comparing Natural Language Processing and Structured Medical Data to Develop a Computable Phenotype for Patients Hospitalized Due to COVID-19: Retrospective Analysis.

Background: Throughout the COVID-19 pandemic, many hospitals conducted routine testing of hospitalized patients for SARS-CoV-2 infection upon admission. Some of these patients are admitted for reasons unrelated to COVID-19 and incidentally test positive for the virus. Because COVID-19-related hospitalizations have become a critical public health indicator, it is important to identify patients who are hospitalized because of COVID-19 as opposed to those who are admitted for other indications. Objective: We compared the performance of different computable phenotype definitions for COVID-19 hospitalizations that use different types of data from electronic health records (EHRs), including structured EHR data elements, clinical notes, or a combination of both data types. Methods: We conducted a retrospective data analysis, using clinician chart review-based validation at a large academic medical center. We reviewed and analyzed the charts of 586 hospitalized individuals who tested positive for SARS-CoV-2 in January 2022. We used LASSO (least absolute shrinkage and selection operator) regression and random forests to fit classification algorithms that incorporated structured EHR data elements, clinical notes, or a combination of structured data and clinical notes. We used natural language processing to incorporate data from clinical notes. The performance of each model was evaluated based on the area under the receiver operator characteristic curve (AUROC) and an associated decision rule based on sensitivity and positive predictive value. We also identified top words and clinical indicators of COVID-19-specific hospitalization and assessed the impact of different phenotyping strategies on estimated hospital outcome metrics. Results: Based on a chart review, 38.2% (224/586) of patients were determined to have been hospitalized for reasons other than COVID-19, despite having tested positive for SARS-CoV-2. A computable phenotype that used clinical notes had significantly better discrimination than one that used structured EHR data elements (AUROC: 0.894 vs 0.841; P<.001) and performed similarly to a model that combined clinical notes with structured data elements (AUROC: 0.894 vs 0.893; P=.91). Assessments of hospital outcome metrics significantly differed based on whether the population included all hospitalized patients who tested positive for SARS-CoV-2 or those who were determined to have been hospitalized due to COVID-19. Conclusions: These findings highlight the importance of cause-specific phenotyping for COVID-19 hospitalizations. More generally, this work demonstrates the utility of natural language processing approaches for deriving information related to patient hospitalizations in cases where there may be multiple conditions that could serve as the primary indication for hospitalization.

Comparative Outcomes of Sacubitril/Valsartan Use After Hospitalization for Heart Failure Among Medicare Beneficiaries Naïve to Renin-Angiotensin System Inhibitors.

Sacubitril/valsartan improves outcomes in patients with heart failure with reduced ejection fraction (HFrEF) compared with angiotensin-converting enzyme inhibitors (ACEis). However, data on postdischarge outcomes in renin-angiotensin system inhibitor (RASi)-naïve patients are limited. We included Medicare beneficiaries aged ≥65 years who were hospitalized for HFrEF in the Get With The Guidelines-Heart Failure registry between October 2015 and June 2019, had part D prescription coverage, and were not on RASi therapy during the 6 months before hospital admission. We examined the associations between sacubitril/valsartan prescription at hospital discharge and outcomes at 30 days and 1 year after discharge using overlap-weighted median regression and Cox proportional hazards models. The end points included "home time" (defined as days alive and out of any health care institution), mortality, and rehospitalization. Among 3,572 patients with HFrEF and who are naïve to RASi therapy, at discharge, 290 (8.1%) were prescribed sacubitril/valsartan and 1,390 (38.9%) were prescribed ACEis and angiotensin receptor blockers. After adjusting for baseline characteristics, patients prescribed sacubitril/valsartan had a longer median home time (parameter estimate 27.0 days, 95% confidence interval [CI] 12.40 to 41.6, p <0.001) and lower all-cause mortality (hazard ratio [HR] 0.74, 95% CI 0.61 to 0.91, p = 0.004) at 1 year than patients not prescribed sacubitril/valsartan. The prescription of sacubitril/valsartan was not significantly associated with all-cause rehospitalization (HR 0.87, 95% CI 0.74 to 1.03, p = 0.10) or heart failure rehospitalization (HR 0.87, 95% CI 0.70 to 1.07, p = 0.19). In a restricted comparison of patients discharged on sacubitril/valsartan versus ACEis and angiotensin receptor blockers, there were no significant differences in the outcomes. In conclusion, in this contemporary population of RASi-naïve patients with HFrEF from routine clinical practice, compared with not initiating, the initiation of sacubitril/valsartan at discharge was associated with longer home time and improvements in overall survival.

Gender and intention to leave healthcare during the COVID-19 pandemic among U.S. healthcare workers: A cross sectional analysis of the HERO registry.

IMPORTANCE: The COVID-19 pandemic stressed the healthcare field, resulting in a worker exodus at the onset and throughout the pandemic and straining healthcare systems. Female healthcare workers face unique challenges that may impact job satisfaction and retention. It is important to understand factors related to healthcare workers' intent to leave their current field. OBJECTIVE: To test the hypothesis that female healthcare workers were more likely than male counterparts to report intention to leave. DESIGN: Observational study of healthcare workers enrolled in the Healthcare Worker Exposure Response and Outcomes (HERO) registry. After baseline enrollment, two HERO 'hot topic' survey waves, in May 2021 and December 2021, ascertained intent to leave. Unique participants were included if they responded to at least one of these survey waves. SETTING: HERO registry, a large national registry that captures healthcare worker and community member experiences during the COVID-19 pandemic. PARTICIPANTS: Registry participants self-enrolled online and represent a convenience sample predominantly composed of adult healthcare workers. EXPOSURE(S): Self-reported gender (male, female). MAIN OUTCOME: Primary outcome was intention to leave (ITL), defined as having already left, actively making plans, or considering leaving healthcare or changing current healthcare field but with no active plans. Multivariable logistic regression models were performed to examine the odds of intention to leave with adjustment for key covariates. RESULTS: Among 4165 responses to either May or December surveys, female gender was associated with increased odds of ITL (42.2% males versus 51.4% females reported intent to leave; aOR 1.36 [1.13, 1.63]). Nurses had 74% higher odds of ITL compared to most other health professionals. Among those who expressed ITL, three quarters reported job-related burnout as a contributor, and one third reported experience of moral injury. CONCLUSIONS AND RELEVANCE: Female healthcare workers had higher odds of intent to leave their healthcare field than males. Additional research is needed to examine the role of family-related stressors. TRIAL REGISTRATION: ClinicalTrials.gov identifier NCT04342806.

Potential bias and lack of generalizability in electronic health record data: reflections on health equity from the National Institutes of Health Pragmatic Trials Collaboratory.

Embedded pragmatic clinical trials (ePCTs) play a vital role in addressing current population health problems, and their use of electronic health record (EHR) systems promises efficiencies that will increase the speed and volume of relevant and generalizable research. However, as the number of ePCTs using EHR-derived data grows, so does the risk that research will become more vulnerable to biases due to differences in data capture and access to care for different subsets of the population, thereby propagating inequities in health and the healthcare system. We identify 3 challenges-incomplete and variable capture of data on social determinants of health, lack of representation of vulnerable populations that do not access or receive treatment, and data loss due to variable use of technology-that exacerbate bias when working with EHR data and offer recommendations and examples of ways to actively mitigate bias.

Disruption in Blood Pressure Control With the COVID-19 Pandemic: The PCORnet Blood Pressure Control Laboratory.

OBJECTIVE: To explore trends in blood pressure (BP) control before and during the COVID-19 pandemic. PATIENTS AND METHODS: Health systems participating in the National Patient-Centered Clinical Research Network (PCORnet) Blood Pressure Control Laboratory Surveillance System responded to data queries, producing 9 BP control metrics. Averages of the BP control metrics (weighted by numbers of observations in each health system) were calculated and compared between two 1-year measurement periods (January 1, 2019, through December 31, 2019, and January 1, 2020, through December 31, 2020). RESULTS: Among 1,770,547 hypertensive persons in 2019, BP control to <140/<90 mm Hg varied across 24 health systems (range, 46%-74%). Reduced BP control occurred in most health systems with onset of the COVID-19 pandemic; the weighted average BP control was 60.5% in 2019 and 53.3% in 2020. Reductions were also evident for BP control to <130/<80 mm Hg (29.9% in 2019 and 25.4% in 2020) and improvement in BP (reduction of 10 mm Hg in systolic BP or achievement of systolic BP <140 mm Hg; 29.7% in 2019 and 23.8% in 2020). Two BP control process metrics exhibited pandemic-associated disruption: repeat visit in 4 weeks after a visit with uncontrolled hypertension (36.7% in 2019 and 31.7% in 2020) and prescription of fixed-dose combination medications among those with 2 or more drug classes (24.6% in 2019 and 21.5% in 2020). CONCLUSION: BP control decreased substantially during the COVID-19 pandemic, with a corresponding reduction in follow-up health care visits among persons with uncontrolled hypertension. It is unclear whether the observed decline in BP control during the pandemic will contribute to future cardiovascular events.