Shanshan Song
Graduate Trainee, Johns Hopkins University
5 active projects
Prescriptions in Patients with a Family History of a Documented Condition
Scientific Questions Being Studied
Our primary objective is to construct and characterize a cohort of participants in the All of Us Research Program with a positive family history of disease that have been diagnosed and treated for a relevant disease.
Project Purpose(s)
- Population Health
- Social / Behavioral
- Ancestry
Scientific Approaches
To construct a cohort, we will use electronic health record data and survey data to identify eligible patients. We will also use descriptive statistics to study risk factors of prescription switching and adverse drug reactions in the cohort.
Anticipated Findings
We will identify risk factors of prescription switching and adverse drug reactions observed in a cohort of patients with a positive family history of a documented conditions.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Registered TierResearch Team
Owner:
- Shanshan Song - Graduate Trainee, Johns Hopkins University
- Casey Taylor - Early Career Tenure-track Researcher, Johns Hopkins University
[Duplicate] Prescriptions in Patients with a Family History of xx
Scientific Questions Being Studied
Our primary objective is to construct and characterize a cohort of participants in the All of Us Research Program with a positive family history of disease that have been diagnosed and treated for a relevant disease.
Project Purpose(s)
- Population Health
- Social / Behavioral
- Ancestry
Scientific Approaches
To construct a cohort, we will use electronic health record data and survey data to identify eligible patients. We will also use descriptive statistics to study risk factors of prescription switching and adverse drug reactions in the cohort.
Anticipated Findings
We will identify risk factors of prescription switching and adverse drug reactions observed in a cohort of patients with a positive family history of a documented conditions.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Registered TierData validity threshold evaluation
Scientific Questions Being Studied
This study aims to evaluate various data validity criterion and its impact on analytical sample and model outcomes.
Project Purpose(s)
- Population Health
- Social / Behavioral
- Methods Development
Scientific Approaches
We will use survey data and Fitbit data to identify eligible patients. We will also use descriptive statistics to study to evaluate how various validity threshold would influence analytical sample quality and outcome of model using such sample data.
Anticipated Findings
We will compare descriptive statistics of analytical sample identified using different validity threshold.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Registered TierDuplicate of Demo - Family History in EHR & PPI Data
Scientific Questions Being Studied
As a demonstration project, this study will summarize structured data elements available in the All of Us registered tier and compare to published survey results to describe data for reuse in disease specific outcomes. Specific questions include:
1. Could harnessing informatics tools like predictive modeling and clinical decision support to detect and alert healthcare providers to these preventative measures significantly improve the precise care we deliver to patients?
2. How can one evaluate the availability of family medical history information within the All of Us registered tier data and characterize the structured data elements from both data sources?
Project Purpose(s)
- 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 Data and Research Center to ensure compliance with program policy, including policies for acceptable data access and use.)
Scientific Approaches
We utilize the Family Medical History PPI survey to capture self-reported information but exclude participants who did not know any of their family history or who skipped every survey question. We pay particular attention to the disease/relative pairings that map to the American College of Medical Genetics and Genomics’ (ACMG) list of important diseases.
We define EHR family history information as the collection of registered tier observations with "family+history" or "FH:" anywhere in their OMOP concept name. We exclude observations of “Family social history” and remove duplicate observation and value concept pairings from the same healthcare organization regarding the same participant as these were likely due to repeated entries across multiple routine annual physical exams.
We aim to compare the data sources by summarizing the type and amount of family history information gained.
Anticipated Findings
This description of the family medical history data in the All of Us registered tier database will assist future investigators in understanding All of Us data methods and give feedback to the program on the utility of participant survey and EHR data.
We hypothesize that the survey data will provide a more complete look at family medical history due to its structured nature. Though, we are also interested in determining how much overlap there is between the PPI and EHR data. It’s plausible that the free-form nature of EHR family history information yields more detailed records. We would ultimately like to determine if a gold standard method for defining a participant’s family medical history is attainable within the All of Us registered tier data.
We anticipate facing informatics challenges because of collecting data from different sources, mapping these data to a common data model, and attempting to harness data from these sources to find the common source of truth.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Registered TierDuplicate of How to Work With Wearable Device Data (tier 5)
Scientific Questions Being Studied
We recommend that all researchers explore the notebooks in this workspace to learn the basics of how to work with Fitbit data, which is the first pilot of wearable device data currently available within the All of Us Registered Tier dataset. What should you expect? This notebook will give an overview characterization of the Fitbit data elements currently available in the current Curated Data Repository (CDR) and provide best practices and tips for how to retrieve them.
Project Purpose(s)
- Educational
- Methods Development
- Other Purpose (This is an All of Us Tutorial Workspace. It is meant to provide instruction for key Researcher Workbench components and All of Us data representation.)
Scientific Approaches
This Tutorial Workspace contains one Jupyter Notebook written in Python. The notebook contains information on how to extract and work with the current set of All of Us Fitbit data. What are the anticipated findings from the study? How would your findings contribute to the body of scientific knowledge in the field? By reading and running the notebook in this Tutorial Workspace, researchers will learn how to query information about steps, heart rate, and daily activity summary.
Anticipated Findings
By reading and running the notebook in this Tutorial Workspace, researchers will understand how to work with Fitbit CDR data from the workbench. They will learn how to query information about steps, heart rate, and daily activity summary.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Registered TierRequest 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.
