Validation and clinical discovery demonstration of a real-world data extraction platform

ObjectiveTo validate and demonstrate the clinical discovery utility of a novel patient-mediated, medical record collection and data extraction platform developed to improve access and utilization of real-world clinical data. MethodsClinical variables were extracted from the medical records of consented patients with metastatic breast cancer. To validate the extracted data, case report forms completed using the structured data output of the platform were compared to manual chart review for 50 patients. To demonstrate the platforms clinical discovery utility, we assessed associations between time to distant metastasis (TDM) and tumor histology, molecular type, and germline BRCA status in the platform-extracted data of 194 patients. ResultsThe platform-extracted data had 97.6% precision (91.98%-100% by variable type) and 81.48% recall (58.15%-95.00% by variable type) compared to manual chart review. In our discovery cohort, the shortest TDM was significantly associated with metaplastic (739.0 days) and inflammatory histologies (1,005.8 days), HR-/HER2- molecular types (1,187.4 days), and positive BRCA status (1,042.5 days) as compared to other histologies, molecular types, and negative BRCA status, respectively. Multivariable analyses did not produce statistically significant results, but the average TDMs are reported. DiscussionThe platform-extracted clinical data are precise and comprehensive. The data can generate clinically-relevant insights. ConclusionThe structured real-world data produced by a patient-mediated, medical record-extraction platform are reliable and can power clinical discovery.