Key result
Data standardization using a Common Data Model reduces errors and speeds ECHO-wide cohort analyses.
Why the study?
Large collaborative studies like the ECHO-wide Cohort face key methodological challenges in data collection standardization and data harmonization across diverse cohorts.
Data standardization and harmonization using a Common Data Model are essential for collaborative research designs like the ECHO-wide Cohort to enhance research reproducibility.
Supports harmonization in pediatric cohorts; leaves open cardiovascular outcome impacts pending prospective validation.
The United States (U.S.) National Institutes of Health-funded Environmental influences on Child Health Outcomes (ECHO)-wide Cohort was established to conduct high impact, transdisciplinary science to improve child health and development. The cohort is a collaborative research design in which both extant and new data are contributed by over 57,000 children across 69 cohorts. In this review article, we focus on two key challenging issues in the ECHO-wide Cohort: data collection standardization and data harmonization. Data standardization using a Common Data Model and derived analytical variables based on a team science approach should facilitate timely analyses and reduce errors due to data misuse. However, given the complexity of collaborative research designs, such as the ECHO-wide Cohort, dedicated time is needed for harmonization and derivation of analytic variables. These activities need to be done methodically and with transparency to enhance research reproducibility. IMPACT: Many collaborative research studies require data harmonization either prior to analyses or in the analyses of compiled data. The Environmental influences on Child Health Outcomes (ECHO) Cohort pools extant data with new data collection from over 57,000 children in 69 cohorts to conduct high-impact, transdisciplinary science to improve child health and development, and to provide a national database and biorepository for use by the scientific community at-large. We describe the tools, systems, and approaches we employed to facilitate harmonized data for impactful analyses of child health outcomes.
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Jacobson et al. (2024) conducted a review in Child health and development (n=57,000). Data standardization and harmonization was evaluated. Data standardization using a Common Data Model and derived analytical variables based on a team science approach facilitates timely analyses and reduces errors in the ECHO-wide Cohort study.
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