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April 12, 2026JCO Clinical Cancer Informatics0 citations

Feasibility of Automated Laboratory Data Ascertainment and Transfer From Hospitals Into Medidata Rave Across Pediatric National Cancer Institute–Supported Cooperative Groups

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TMTamara P. MillerRARichard AplencCMCharles G. Minard

Key Points

  • The pilot aimed to evaluate the feasibility of automating laboratory data transfer to Medidata Rave from hospitals in pediatric oncology trials.
  • Included data from 78 patients across seven PBTC or PEP-CTN trials.
  • Utilized the ExtractEHR R package for automated data extraction.
  • Compared results from automated extraction and manual data ascertainment.
  • Categorized discrepancies between extracted and manually ascertained data.
  • All sites successfully extracted laboratory data, achieving at least one complete upload.
  • Discrepancies identified, particularly in bilirubin and platelet count, were often due to mismatched values or units.
  • Collaboration with hospital technical teams was essential for successful data extraction.

Abstract

PURPOSE Electronic data capture (EDC) has the potential to improve trial data accuracy and efficiency. The Children's Oncology Group Pediatric Early Phase Clinical Trials Network (PEP-CTN) and Pediatric Brain Tumor Consortium (PBTC) conducted a joint pilot that aimed to assess feasibility of automated transfer of laboratory data from electronic health records to the Medidata Rave EDC (Rave). Second, we compared data from automated extraction (EXTRACTED) and manual ascertainment (MANUAL) during the original studies using two representative tests, bilirubin and platelet count (PLT). METHODS Data from 78 patients treated on seven completed PBTC or PEP-CTN trials at seven hospitals were included. Each consortium created a Rave instance to receive data. Sites elected to use local methods or the ExtractEHR R package. Postextraction data were uploaded to the Rave Batch Uploader (BU)–associated file transfer protocol client and BU uploaded data into Rave. After successful upload, discrepancies between EXTRACTED and MANUAL data were categorized. RESULTS All sites successfully extracted required laboratory data and had 1+ complete upload. PBTC/PEP-CTN operational effort and close collaboration with hospital site technical teams was required. Owing to study closure timing, only two sites checked EXTRACTED data from their first patient list; this identified incomplete mapping that was fixed before second patient list extraction. Beyond incomplete mapping, discrepancies for bilirubin and PLT were commonly due to mismatched values or units (Consortium 1 PLT: 3/10 (30%); Consortium 2 PLT: 152/176 (86%)). CONCLUSION This study demonstrated that automated laboratory data ascertainment is feasible in pediatric cooperative oncology group trials. Although this required up-front central operational and local site-based effort, lessons learned from this pilot can inform future studies using automated data capture.

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Cite This Study

Miller et al. (2026) studied this question.

synapsesocial.com/papers/69db380f4fe01fead37c6275https://doi.org/10.1200/cci-25-00359
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