Publications by authors named "Juhn Y"

Background: The limitations of conventional measures of socioeconomic status (SES) limit our ability to elucidate the role of SES as a key element of social determinants of health in kidney transplantation. This study's objective was to use an innovative SES measure, the HOUsing-based SES measure (HOUSES) index, to examine the effects of social determinants of health on access to and outcomes of kidney transplantation.

Methods: Our study included residents of Minnesota (age older than 18 y) who underwent kidney transplantation at a single center between 2010 and 2020.

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Article Synopsis
  • The study aimed to identify differences in demographic characteristics, health behaviors, and beliefs about COVID-19 between individuals who have had the infection and those who haven't.
  • It involved a survey of 1,758 adults aged 50 and older in southeast Minnesota, collecting responses on 42 items related to COVID-19 from June 2021 to February 2022.
  • Results indicated that certain demographics and adherence to public health measures, like vaccinations, were linked to lower infection rates, emphasizing the need for ongoing public health initiatives based on these protective factors.
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Background: The incidence of respiratory syncytial virus (RSV)-acute respiratory infection (ARI) in community-dwelling adults after the Omicron variant of the COVID-19 pandemic is unknown. Our aim was to assess the incidence of RSV-ARI in adults aged 18 to 64 years over 2 consecutive RSV seasons (October-April 2022-2024) in 4 US states.

Methods: This community-based prospective cohort study comprised 7501 participants in Minnesota, Wisconsin, Florida, and Arizona.

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Background: There are marked sex differences in the prevalence and severity of asthma, both during childhood and adulthood. There is a relative lack of comprehensive studies exploring sexdifferences in pediatric asthma cohorts.

Objective: To identify the most relevant sex differences in sociodemographic, clinical, and laboratory variables in a well-characterized large pediatric asthma cohort.

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Background: Despite effective vaccines against influenza, pneumococcus, and COVID-19, uptake has been suboptimal.

Research Question: Although disparities in vaccination by race and ethnicity have been observed, what is the role of other sociodemographic factors in US vaccine uptake?

Study Design And Methods: We conducted a population-based study using the Rochester Epidemiology Project (REP), a comprehensive medical records linkage system, to assess effects of sociodemographic factors including race, ethnicity, individual-level socioeconomic status (SES) via the housing-based socioeconomic status index, education, population density (urban or nonurban), and marital status with uptake of influenza, pneumococcal, and COVID-19 vaccination in high-risk adults. Adults at high risk of invasive pneumococcal disease residing in four counties in southeastern Minnesota who were aged 19 to 64 years were identified.

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Background: Personalized asthma management depends on a clinician's ability to efficiently review patient's data and make timely clinical decisions. Unfortunately, efficient and effective review of these data is impeded by the varied format, location, and workflow of data acquisition, storage, and processing in the electronic health record. While machine learning (ML) and clinical decision support tools are well-positioned as potential solutions, the translation of such frameworks requires that barriers to implementation be addressed in the formative research stages.

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Rural health disparities are well documented and continue to jeopardize the long-term health and wellness for the millions of individuals who live in rural America. The disparities observed between urban and rural residents encompass numerous morbidity and mortality measures for several chronic diseases and have been referred to as the "rural mortality penalty." Although the unmet health needs of rural communities are widely acknowledged, little is known about rural health disparities in allergies, asthma, and immunologic diseases.

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Introduction: Using a digital process that leverages electronic health records (EHRs) can ease many of the challenges presented by the traditional enrollment process for clinical trials. We tested if automated batch enrollment using a technology-enabled subject recruitment system (TESRS) enhances recruitment while preserving representation of research subjects for the study population in our study setting.

Methods: An ongoing community-based prospective adult cohort study was used to randomize 600 subjects who were eligible by age and residential address to TESRS (n = 300) and standard mailing method (n = 300), respectively, for 3 months.

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Rural populations are more vulnerable to the impacts of COVID-19 compared to their urban counterparts as they are more likely to be older, uninsured, to have more underlying medical conditions, and live further from medical care facilities. We engaged the Southeastern MN (SEMN) community (N = 7,781, 51% rural) to conduct a survey of motivators and barriers to masking to prevent COVID-19. We also assessed preferences for types of and modalities to receive education/intervention, exploring both individual and environmental factors primarily consistent with Social Cognitive Theory.

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Background: Alcohol-associated hepatitis (AH) is among the deadliest liver diseases, but its incidence is poorly defined. The aim of our study was to define the incidence of AH meeting the National Institute on Alcohol Abuse and Alcoholism criteria and to identify risk factors for AH.

Methods: We conducted a retrospective cohort study using the Rochester epidemiology project database on adult patients hospitalized with AH between January 1, 2000 and December 31, 2018.

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Introduction: Nitrogen dioxide (NO) is known to be a trigger for asthma exacerbation. However, little is known about the role of seasonal variation in indoor and outdoor NO levels in childhood asthma in a mixed rural-urban setting of North America.

Methods: This prospective cohort study, as a feasibility study, included 62 families with children (5-17 years) that had diagnosed persistent asthma residing in Olmsted County, Minnesota.

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Exclusion of special populations (older adults; pregnant women, children, and adolescents; individuals of lower socioeconomic status and/or who live in rural communities; people from racial and ethnic minority groups; individuals from sexual or gender minority groups; and individuals with disabilities) in research is a pervasive problem, despite efforts and policy changes by the National Institutes of Health and other organizations. These populations are adversely impacted by social determinants of health (SDOH) that reduce access and ability to participate in biomedical research. In March 2020, the Northwestern University Clinical and Translational Sciences Institute hosted the "Lifespan and Life Course Research: integrating strategies" "Un-Meeting" to discuss barriers and solutions to underrepresentation of special populations in biomedical research.

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Objective: Independent living is desirable for many older adults. Although several factors such as physical and cognitive functions are important predictors for nursing home placement (NHP), it is also reported that socioeconomic status (SES) affects the risk of NHP. In this study, we aimed to examine whether an individual-level measure of SES is associated with the risk of NHP after accounting for neighborhood characteristics.

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Introduction: Vaccinations against preventable respiratory infections such as Streptococcus pneumoniae and influenza are important in immunosuppressed solid organ transplant (SOT) recipients. Little is known about the role of age, race, ethnicity, sex, and sociodemographic factors including rurality, or socioeconomic status (SES) associated with vaccine uptake in this population.

Methods: We conducted a population-based study using the Rochester Epidemiology Project, a medical records linkage system, to assess socioeconomic and demographic factors associated with influenza and pneumococcal vaccination rates among adult recipients of solid organ transplantation (aged 19-64 years) living in four counties in southeastern Minnesota.

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Article Synopsis
  • This study investigates how common respiratory syncytial virus (RSV)-positive acute respiratory infections (ARI) were among older adults in southeast Minnesota before and during the COVID-19 pandemic, analyzing data from 2,325 participants over two RSV seasons (2019-2021).
  • Researchers found that before the pandemic, the incidence rate of RSV-positive ARI was 48.6 cases per 1,000 person-years, but during the pandemic, no cases were reported, indicating a significant drop in RSV infections during that time.
  • Additionally, the study measured the quality of life and physical function of participants after recovering from RSV-positive ARI, demonstrating the long-term impact of RSV infections on
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Article Synopsis
  • - The study aimed to estimate the rates of asymptomatic COVID-19 and identify associated factors in Olmsted County's population during the periods before vaccines were available by screening first responders and county employees for antibodies and analyzing PCR-confirmed cases.
  • - Among the screened groups, 10.5% of first responders and 6.7% of county employees tested positive for antibodies, with 20% of first responders and 26% of county employees being asymptomatic based on symptom information.
  • - Overall, 6% of PCR-confirmed COVID-19 cases during the study period were asymptomatic, with age, body mass index, and timing of tests influencing asymptomatic rates, indicating that younger, normal-weight individuals tested
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Background And Aims: Influenza is a challenging infectious illness for older adults. It is not completely clear whether influenza is associated with frailty or functional decline. We sought to determine the association between incident influenza infection and frailty and prefrailty in community patients over 50 years of age.

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Achieving optimal care for pediatric asthma patients depends on giving clinicians efficient access to pertinent patient information. Unfortunately, adherence to guidelines or best practices has shown to be challenging, as relevant information is often scattered throughout the patient record in both structured data and unstructured clinical notes. Furthermore, in the absence of supporting tools, the onus of consolidating this information generally falls upon the clinician.

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Background: Studies examining the role of geographic factors in coronavirus disease-2019 (COVID-19) epidemiology among rural populations are lacking.

Methods: Our study is a population-based longitudinal study based on rural residents in four southeast Minnesota counties from March through October 2020. We used a kernel density estimation approach to identify hotspots for COVID-19 cases.

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Article Synopsis
  • AI models can reinforce harmful biases, particularly affecting underserved populations, by relying on flawed data from electronic health records (EHRs), especially for low socioeconomic status (SES) groups.
  • The study compared AI performance on asthma predictions across different SES levels and found that children with lower SES had worse model accuracy and more missing health information.
  • The findings indicate a need for addressing data incompleteness in EHRs to mitigate bias and improve AI model performance in healthcare for lower SES groups, using the HOUSES index as a tool for researchers.
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Background: Inhaled corticosteroids (ICSs) are important in asthma management, but there are concerns regarding associated risk of pneumonia. While studies in asthmatic adults have shown inconsistent results, this risk in asthmatic children is unclear.

Objective: Our aim was to determine the association of ICS use with pneumonia risk in asthmatic children.

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Objective: Clinical trials, which are mainly conducted in urban medical centers, may be less accessible to rural residents. Our aims were to assess participation and the factors associated with participation of rural residents in clinical trials.

Methods: Using geocoding, the residential address of participants enrolled into clinical trials at Mayo Clinic locations in Arizona, Florida, and the Midwest between January 1, 2016, and December 31, 2017, was categorized as urban or rural.

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Background: Clinicians' asthma guideline adherence in asthma care is suboptimal. The effort to improve adherence can be enhanced by assessing and monitoring clinicians' adherence to guidelines reflected in electronic health records (EHRs), which require costly manual chart review because many care elements cannot be identified by structured data.

Objective: This study was designed to demonstrate the feasibility of an artificial intelligence tool using natural language processing (NLP) leveraging the free text EHRs of pediatric patients to extract key components of the 2007 National Asthma Education and Prevention Program guidelines.

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Article Synopsis
  • Significant variability exists in how clinicians document asthma care, indicating a need for better assessment methods beyond traditional structured data analysis.
  • A study utilized BERT, a context-aware language model, alongside manual chart reviews and weakly labeled data to improve the identification of inhaler techniques in electronic health records (EHRs).
  • Results showed that BERT models, especially when augmented with distant supervision, outperformed rule-based models, demonstrating a promising approach to enhance guideline-concordant documentation in asthma management.
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