Seungwon Yang
Early Career Tenure-track Researcher, Louisiana State University
4 active projects
Duplicate of Demo - All of Us Descriptive Statistics
Scientific Questions Being Studied
As a demonstration project, this study will present the overview of the data types available based on participant count, separating the surveys into Part 1 which includes the first three surveys ("The Basics”, “Overall Health” and “Lifestyle) participants completed, and Part 2 (“Healthcare Access & Utilization”, “Family History”, and “Personal Medical History”) which includes the second set of three surveys that were made available 90 days after enrollment. This study will also look at the overview of the electronic health records (EHR) data available and the physical measurements (PM) data obtained at time of enrollment to the program. We will also look at the total number of participants who have any survey response, PM, and EHR data combined and break it down by age, race, sex at birth, gender identity and look at the breakdown by under-representative biomedical research (UBR) groups.
Project Purpose(s)
- Educational
- Methods Development
- Other Purpose (This work is a result of an All of Us Research Program Demonstration Project. The projects are efforts by the Program designed to meet the program's goal of ensuring the quality and utility of the Research Hub as a resource for accelerating discovery in science and medicine. This work was reviewed and overseen by the All of Us Research Program Science Committee and the All of Us Data and Research Center to ensure compliance with program policy, including acceptable data access and use.)
Scientific Approaches
In this study, we will apply data visualization libraries to aggregate information about the Cohort. We will measure age by using the age reflected when the CDR was generated. Presence of a data type survey, PM, or EHR is counted if at least one observation is present within each category. We will use "The Basics" survey to select race and ethnicity and responses will be mapped to the race variable in the OMOP Person table. All participants responding ‘American Indian or Alaska Native’ will be removed from the CDR as All of Us engages the NIH Tribal Council on the research use of data. Program designations of status as UBR will be adapted to data available in the CDR .
Anticipated Findings
In this study, we anticipate creating plots to describe all of the participant breakdown by age, race, ethnicity, gender, sex at birth and per datatype. We will be using these plots for our All of Us Research Program Demonstration Projects publication as visuals describing the initial cohort released at Beta launch of the Researcher Workbench.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Registered TierResearch Team
Owner:
- Seungwon Yang - Early Career Tenure-track Researcher, Louisiana State University
Duplicate of Phenotype - Depression (tier 5)
Scientific Questions Being Studied
The Notebooks in this Workspace can be used to implement well-known phenotype algorithms in one’s own research.
Project Purpose(s)
- Educational
- Methods Development
- Other Purpose (This is an All of Us Phenotype Library Workspace created by the Researcher Workbench Support team. It is meant to demonstrate the implementation of key phenotype algorithms within the All of Us Research Program cohort.)
Scientific Approaches
Not Applicable
Anticipated Findings
By reading and running the Notebooks in this Phenotype Library Workspace, researchers can implement the following phenotype algorithms:
This Workspace contains an implementation of a phenotype algorithm for depression: This algorithm was obtained from the eMERGE network. Citation: TBA. KPWA/UW. Depression. PheKB; 2018 Available from: https://phekb.org/phenotype/1095
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Registered TierResearch Team
Owner:
- Seungwon Yang - Early Career Tenure-track Researcher, Louisiana State University
Duplicate of Demo - Hypertension Prevalence
Scientific Questions Being Studied
We are using the All of Us Researcher Workbench interface to answer the question, "Is hypertension prevalence in the All of Us Research Program similar to hypertension prevalence in the 2015–2016 National Health and Nutrition Examination Survey (NHANES) ?". Clinical approaches to understanding and treating hypertension may benefit from the integration of a precision medicine approach that integrates data on environments, social determinants of health, behaviors, and genomic factors that contribute to hypertension risk. Hypertension is a major public health concern and remains a leading risk factor for stroke and cardiovascular disease.
Project Purpose(s)
- Other Purpose (This work is an AoU demo project. Demo projects are efforts by the AoU Research Program designed to meet the program goal of ensuring the quality and utility of the Research Hub as a resource for accelerating discovery in science and medicine. As an approved demo project, this work was reviewed and overseen by the AoU Research Program Science Committee and the AoU Data and Research Center to ensure compliance with program policy, including policies for acceptable data access and use. )
Scientific Approaches
In this cross-sectional, population-based study, we used All of Us baseline data from patient (age>18) provided information (PPI) surveys and electronic health record (EHR) blood pressure measurements and retrospectively examined the prevalence of hypertension in the EHR cohort using Systemized Nomenclature of Medicine (SNOMED codes and blood pressure medications recorded in the EHR. We used the EHR data (SNOMED codes on 2 distinct dates and at least one hypertension medication) as the primary definition, and then add subjects with elevated systolic or elevated diastolic blood pressure on measurements 2 and 3 from PPI. We extracted each participant’s detailed dates of SNOMED code for essential hypertension from the Researcher Workbench table ‘cb_search_all_events’. We calculated an age-standardized HTN prevalence according to the age distribution of the U.S. Census, using 3 groups (18-39, 40-59, ≥ 60).
Anticipated Findings
The prevalence of hypertension in the All of Us cohort is similar to that of published literature. All of Us age-adjusted HTN prevalence was 27.9% compared to 29.6% in National Health and Nutrition Examination Survey. The All of Us cohort is a growing source of diverse longitudinal data that can be utilized to study hypertension nationwide. The prevalence of hypertension varies in the United States (U.S.) by age, sex, and socioeconomic status. Hypertension can often be treated successfully with medication, and prevented or delayed with lifestyle modifications. Even with these established hypertension intervention and prevention strategies, the prevalence of hypertension continues to be at levels of public health concern. The diversity within All of Us may provide insight into factors relevant to hypertension prevention and treatments in a variety of social and geographic contexts and population strata in the U.S.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Registered TierResearch Team
Owner:
- Seungwon Yang - Early Career Tenure-track Researcher, Louisiana State University
Examining the Overall Opioid Crisis in the Underrepresented Population
Scientific Questions Being Studied
1. What are the status of opioid use disorder among different races and people with difference socio-economic status from underrepresented populations in the U.S.?
2. Which analysis methods are effective for understanding the research question #1 above?
3. What are the best approach to apply the developed methods and used datasets from this study in a data analysis course?
Project Purpose(s)
- Disease Focused Research (Opioid Use Disorder)
- Population Health
- Social / Behavioral
- Educational
- Methods Development
Scientific Approaches
(1) Datasets:
Survey and EHR data from underrepresented populations who had Opioid Use Disorder
(2) Research methods:
Supervised and unsupervised learning, deep learning algorithms
(3) Tools:
Python programming language and related packages for data analysis
Anticipated Findings
The anticipated findings from this study will be:
(1) to identify most vulnerable groups of people (e.g., race and socio-economic status) for Opioid Use Disorder in underrepresented populations
(2) to find effective methods from the machine/deep learning field to understand (1)
(3) to come up with term project ideas for a data analysis course based on the methods and datasets from this study
Demographic Categories of Interest
- Race / Ethnicity
Data Set Used
Registered TierResearch Team
Owner:
- Seungwon Yang - Early Career Tenure-track Researcher, Louisiana State University
Collaborators:
- Joohyun Kim - Other, Vanderbilt University Medical Center
Request a Review of this Research Project
You can request that the All of Us Resource Access Board (RAB) review a research purpose description if you have concerns that this research project may stigmatize All of Us participants or violate the Data User Code of Conduct in some other way. To request a review, you must fill in a form, which you can access by selecting ‘request a review’ below.
