Metadata Construction in Collaborative Research Networks Hanieh Razzaghi, MPH

PEDSnet A National Pediatric Learning Health System (Forrest et al What is PEDSnet? Clinical Data Research Network (CDRN) Facilitate large-scale research Employs a Common Data Model Aggregates pediatric EHR data from multiple institutions Challenges Opportunities lack of EHR data’s orientation toward research analytics diversity in EHR configurations semantic heterogeneity data peculiarities in pediatrics large-scale Building partnerships between researchers, clinicians, data-oriented scientists Common Data Model (OMOP) – unified vocabulary Building a framework for metadata to facilitate research

PEDSnet Data Flow and Opportunities for Metadata PEDSnet sites (at various locations) PEDSnet Common Data Model Extract-transform-load (ETL) data quarterly Regular online meetings GitHub version control Data Quality and Characterization Query Fulfillment Data Science PCORnet Common Data Model Data Modeling ETL specifications Data Quality Study Participation

Metadata Construction Opportunities Data Life Cycle Step Process Metadata Content Metadata Provenance analyst approach in identifying appropriate source tables/fields   description of source tables (e.g., dates of use, purpose, use in site operations) source gaps ETL Process analyst approach of resolving sources of ontology mismappings ontology conflicts between source (local EHR) and PEDSnet data model semantic and structural differences between source and PEDSnet data Data Operations Management frequency of updates process of data integration ID management domains populated storage and transfer information size of database permissions and access control Data Quality applying data quality checks frequency of application determination of domains, fields that checks apply to integrating data from DQ catalog with data in GH repository (e.g., response time, resolution status, ranking, causes) Scientific Data Request documents needed to complete request process documenting decisions made by investigator for dataset exploring key concepts in research proposal to specific terms of interest mapping of data variables to data model integrating information about data quality, provenance, and ETL process interface for researchers to understand how research proposal may look in a dataset