PROJECT SUMMARY/ABSTRACT The National Cancer Institute (NCI) Childhood Cancer Data Initiative (CCDI) is building an ecosystem to gather data and learn from all patients with childhood cancer. An important component of this is increasing the availability of longitudinal clinical data that can be integrated with other crucial data submitted to the CCDI. The current standard practice for acquiring these types of data is manual abstraction by a clinical research coordinator, which is time consuming and subject to human error. Electronic health records (EHRs) have the potential to expand the amount of data flowing into the CCDI ecosystem. However, they also present several challenges due to lack of structure and standardization. This objective of this study is to combine two previously developed approaches to obtaining data in order to provision clean, clinically-relevant data to the CCDI. The first package, ExtractEHR, extracts data from the EHR, and utilizes a series of post-processing coding to transform the raw EHR data into clinically relevant, human understandable data about the childhood cancer experience. The second approach uses Fast Healthcare Interoperability Resources (FHIR)-based methods to provide a technical framework for more scalable workflows and interchange of clinical data. This study aims to combine ExtractEHR with the FHIR framework development to enable the expansion of clinical data available to CCDI. The proposal will determine scalable ways for ongoing contributions by achieving the following two specific aims. The first aims is to extract and process EHR data to provide clinical context regarding treatment and outcomes for patients with molecular data in the CCDI ecosystem. To achieve this goal, ExtractEHR will be extract data on patients previously consented to Children’s Brain Tumor Network (CBTN) protocols at two large children’s hospitals, the Children’s Hospital of Philadelphia (CHOP) and Children’s Healthcare of Atlanta (CHOA). Extracted data will be processed to provide clinically-relevant treatment and outcomes data that will be transferred to the CCDI. This will demonstrate the feasibility and operability of a seamless workflow by delivering a set of EHR data to CCDI to facilitate collaboration and discussion with CCDI teams on which aspects of the workflow or data to optimize and/or expand on. The second aim is to develop a FHIR-based version of ExtractEHR and determine its scalability and success in interacting with the post-processing workflow needed to obtain clinically meaningful data. Efforts will be made to export ExtractEHR functionality into a FHIR framework at CHOP and to test this process at CHOA. This study will create pipelines that provide granular data from cleaned and processed EHR data that offers clinical context for patients included in the CCDI and will determine if FHIR-based approaches can be used as a scalable method for using ExtractEHR to ascertain data to be included in the CCDI ecosystem.