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The Region 4 Stork (R4S) Collaborative Project

Part 4a: High-Throughput Data Entry Portals - Tool Runner

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July 2013

Accurate identification of newborns with metabolic disease can significantly improve patient outcomes. Conversely, a missed diagnosis can result in significant morbidity and may even result in death. While a false-positive diagnosis does not carry the burden of increased morbidity or mortality, there are social and psychological costs that may generate significant harm. The Region 4 Stork Collaborative was developed to improve detection of true positive cases of metabolic disease and improve accurate diagnosis. The R4S project uses Mayo-developed software that provides postanalytical interpretation of complex metabolic profiles. The R4S project offers physicians worldwide the opportunity to utilize this software to analyze their patients’ test results, and compare them with other locations’ results.

R4S Collaborative Project Part 4 discusses high-throughput data entry portals. To improve download time, Part 4 has been separated into 2 subjects: 4A focuses on the Tool Runner tool, while 4B focuses on the All Conditions tool.


  • Piero Rinaldo, MD, PhD
    • Co-director of the Biochemical Genetics Laboratory
    • Professor of Laboratory Medicine and Pathology
    • T. Denny Sanford Professor of Pediatrics at Mayo Clinic

Viewers may request access to the R4S database.

The Region 4 Stork (R4S) Series

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