Project Overview: Creating a Visual Guide for New Users of the N3C Enclave

Part 1:

• Basic Information on how to create an N3C account and join a research project

• How to connect with the greater N3C Community

• Basics of EHR data and the OMOP data structure

• Resources for building programming skills (R, Python, SQL)

• Using the N3C tool Contour

Part 2: Conducting an N3C Research Study

Part 3: Disseminating N3C Research Results

N3C Enclave (covid.cd2h.org)

• Official Name: The National COVID Cohort Collaborative

• Purpose: Collection of secure and deidentified patient data to further COVID-19 research

• Collaborative Space: For research and data collection

• Data Standards: All data is submitted according to the Common Data Model

• 3 Levels of Data:

  • Level 1: Synthetic Data

    • “Fake” data that statistically resembles original data

  • Level 2: De-identified Data

    • Data stripped of 18 direct identifiers (based on HIPAA privacy policies)

  • Level 3: Limited Data Set

    • Data stripped of 16 direct identifiers (provides dates and zip codes)

Challenges

• Long Wait Time for N3C Account Approval

• Project Focus Adjustments:

  • Shifted focus to OMOP and general resources

  • Attended N3C Office Hours for help and learned about collaborative community events

  • Attended public lectures disseminating N3C Research Results

• Diverse Audience:

  • Varying levels of research experience

  • Includes citizen scientists, students, and fully-fledged researchers

  • New to Public Health, Programming, and EHR data

• Material Focus:

  • Focused at the most basic level

  • Provided resources to more advanced external resources

OMOP - Common Data Model

• OMOP: Observational Medical Outcomes Partnership

• Goal: Standardize data into a common format to prevent the need for transformations

• Data Submission: Every entity that submits data to the N3C enclave must follow this format

• Tables for Different Categories:

  • Person: Demographic information

  • Observation Period: Length of condition

  • Drug Exposure: Details of drug usage

  • Concept_IDs: Used to create a standardized vocabulary/dictionary

OMOP Example

Reflection

• Experience: First encounter with EHR data, OMOP data model, and the N3C Enclave

• Learnings:

  • Insights into collaborative research communities

  • Strengthened research and data skills

  • Application of skills during senior thesis

  • Future research opportunities using the N3C Enclave