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Learning important common data elements from shared study data: The All of Us program analysis.

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The All of Us program uses common data elements (CDEs) and the OMOP Common Data Model to standardize clinical study data. This integration facilitates analysis and monitoring of health and lifestyle changes.

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Area of Science:

  • Health Informatics
  • Clinical Data Management
  • Biomedical Research

Background:

  • Harmonizing data collection across human clinical studies is crucial for robust research.
  • Large-scale initiatives like the All of Us (AoU) program aim to standardize data using common data elements (CDEs).
  • The OMOP Common Data Model is increasingly adopted for standardizing research and real-world data.

Purpose of the Study:

  • To analyze the data standardization approach within the All of Us (AoU) program.
  • To evaluate the extent of common data element (CDE) and unique data element (UDE) usage in AoU.
  • To assess the integration of research and electronic health record data using the OMOP Common Data Model.

Main Methods:

  • Defined elements from established terminologies (LOINC, SNOMED CT) as CDEs.
  • Defined custom concepts in Participant Provided Information (PPI) as UDEs.
  • Analyzed element and value distributions across research Case Report Forms (CRFs) and data contexts.

Main Results:

  • AoU utilized 1,033 research elements, with most being UDEs (84.1%).
  • LOINC and SNOMED CT were primary sources for CDEs, with many LOINC CDEs originating from prior initiatives (e.g., PhenX, PROMIS).
  • The OMOP model facilitated integration of research and routine healthcare data for 64 elements, enabling health and lifestyle monitoring.

Conclusions:

  • The All of Us program effectively employs the OMOP Common Data Model for data standardization and integration.
  • Increased use of CDEs in large studies like AoU enhances data comparability and analytical efficiency.
  • Standardized data collection improves the ease of understanding and analyzing clinical study data, reducing challenges associated with study-specific formats.