Objective Federated research networks, like Evolve to Next-Gen Accrual of patients to Clinical Trials (ENACT), aim to facilitate medical research by exchanging electronic health record (EHR) data. However, poor data quality can hinder this goal. While networks typically set guidelines and standards to address this problem, we developed an organically evolving, data-centric method using patient counts to identify data quality issues, applicable even to sites not yet in the network. Materials and Methods We distribute high-performance patient counting scripts as part of Integrating Biology at the Bedside (i2b2), which all ENACT sites operate. They produce counts of patients associated with ENACT ontology terms for each site. At the ENACT Hub, our pipeline aggregates site-contributed counts to produce network statistics, which our self-service web application, Data Quality Explorer (DQE), ingests to help sites conduct data quality investigation relative to the network. Results Thirteen ENACT sites have contributed their patient counts, and currently seven sites have signed up to use DQE to analyze data quality issues. We announced a call to all ENACT sites to contribute additional patient counts. Discussion Identifying site data quality problems relative to the network is novel. Using a metric based on evolving network statistics complements rigid data quality checks. It is adaptable to any network and has low barriers of entry, with patient counting being the sole requirement. Conclusion We implemented a metric for conducting data quality investigation in ENACT using patient counting and network statistics. Our end-to-end pipeline is privacy-preserving and the underlying design is generalizable.

The authors have declared no competing interest.

This work is funded in part by National institute of Health award U24TR004111. Dr. Weber is additionally supported by NIH awards R01LM013345, U01CA198934, and the i2b2 tranSMART Foundation.

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

Each participating site of the ENACT Network has obtained approval by their institution's Institutional Review Boards (IRBs) for sharing the data sharing presented in this manuscript They are listed below: IRB of Beth Israel Deaconess Medical Center gave ethical approval for this work. IRB of Boston Medical Center gave ethical approval for this work. IRB of Keck Hospital of University of Southern California gave ethical approval for this work. IRB of Mayo Clinic gave ethical approval for this work. IRB of Mass General Brigham gave ethical approval for this work. IRB of University of Pittsburgh gave ethical approval for this work. IRB of University of California Los Angeles gave ethical approval for this work. IRB of University of California San Diego gave ethical approval for this work. IRB of University of Florida gave ethical approval for this work. IRB of University of Kentucky gave ethical approval for this work. IRB of Utah gave ethical approval for this work. IRB of University of Texas Houston gave ethical approval for this work. IRB of University of Texas Medical Branch gave ethical approval for this work. IRB of University of Texas South Western gave ethical approval for this work.

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