Childhood Cancer Data Initiative Annual Symposium (Abstract Registration): Submission #48
Submission information
Submission Number: 48
Submission ID: 150078
Submission UUID: 458369c0-9547-47ef-aec4-6bc56dbec5e2
Submission URI: /nci/ccdisymposium/abstract?cid=eb_govdel_ccdi_events
Submission Update: /nci/ccdisymposium/abstract?cid=eb_govdel_ccdi_events&token=d80kU0p6IObVw_7bw-zPf8Kd5fwovrK6xb-TLXL2DEM
Created: Thu, 08/28/2025 - 08:32
Completed: Thu, 08/28/2025 - 08:35
Changed: Thu, 08/28/2025 - 08:35
Remote IP address: 10.208.28.90
Submitted by: Anonymous
Language: English
Is draft: No
serial: '48' sid: '150078' uuid: 458369c0-9547-47ef-aec4-6bc56dbec5e2 uri: '/nci/ccdisymposium/abstract?cid=eb_govdel_ccdi_events' created: '1756384339' completed: '1756384514' changed: '1756384514' in_draft: '0' current_page: '' remote_addr: 10.208.28.90 uid: '0' langcode: en webform_id: ccdi_symposium_abstract entity_type: node entity_id: '2139' locked: '0' sticky: '0' notes: '' metatag: meta data: authors_: - add_author_degree: 'MD, MSCE' add_author_first_name: Tamara add_author_last_name: Miller add_author_middle: P add_author_organization: "Emory University/Children's Healthcare of Atlanta" - add_author_degree: MS add_author_first_name: Gregory add_author_last_name: Joseph add_author_middle: '' add_author_organization: 'Emory University' - add_author_degree: MS add_author_first_name: Edward add_author_last_name: Krause add_author_middle: '' add_author_organization: "Children's Hospital of Philadelphia" - add_author_degree: '' add_author_first_name: 'Yun Gun' add_author_last_name: Jo add_author_middle: '' add_author_organization: "Children's Hospital of Philadelphia" - add_author_degree: '' add_author_first_name: Judy add_author_last_name: Lee add_author_middle: '' add_author_organization: "Children's Healthcare of Atlanta" - add_author_degree: MSIS add_author_first_name: Hannah add_author_last_name: Calkins add_author_middle: '' add_author_organization: "Children's Hospital of Philadelphia" - add_author_degree: PhD add_author_first_name: Adam add_author_last_name: Resnick add_author_middle: C add_author_organization: "Children's Hospital of Philadelphia" - add_author_degree: 'MD, PhD' add_author_first_name: Richard add_author_last_name: Aplenc add_author_middle: '' add_author_organization: "Children's Hospital of Philadelphia" - add_author_degree: PhD add_author_first_name: Allison add_author_last_name: Heath add_author_middle: '' add_author_organization: "Children's Hospital of Philadelphia" abstract: |- Background: The National Cancer Institute (NCI) Childhood Cancer Data Initiative (CCDI) has enabled the distribution of previously unshared data. A critical component to maximize the utility of these data is to have longitudinal clinical data, such as treatment data. Manual abstraction has typically been used to capture treatment data, but this process is time consuming and subject to human error. This study aimed to use automated extraction and processing of electronic health record (EHR) data using the ExtractEHR+ Toolkit to describe chemotherapy exposures for children enrolled in the Children’s Brain Tumor Network (CBTN) who have contributed data to the CCDI. Methods: Patients enrolled in CBTN at two hospitals were included. ExtractEHR extracted all medication orders and administrations, including outpatient prescriptions, heights, and weights. Medication order and administration data were merged and MedCleanEHR centrally cleaned these data to identify unique chemotherapy exposures and dose amounts. Height and weight data were used to calculate body surface area and merged with medication data. For prescriptions where a discrete dose field was not included, regular expressions were used to identify doses in free text fields. MedCleanEHR calculated cumulative chemotherapy doses each patient received. Results: The cohort included 1628 patients. ExtractEHR successfully pulled 3,849,099 medication administrations and 839,736 medication orders. Once cleaned, there were 98,877 unique chemotherapy administrations and 8,781 chemotherapy prescriptions. Conclusions: The ExtractEHR+ Toolkit can efficiently ascertains chemotherapy exposures and dosing for patients in the CBTN cohort. These data will be transferred to the CCDI to enhance clinical data in the CCDI ecosystem. abstract_title_: 'Leveraging the ExtractEHR+ Toolkit to Enhance Medication Data in the Children’s Brain Tumor Network and Childhood Cancer Data Initiative' email_address_: tamara.miller@emory.edu institution_: "Emory University/Children's Healthcare of Atlanta" presenting_author_: 'Tamara P. Miller, MD, MSCE'