Free Lesson Preview
Module 1: Lesson 1
Understand EHR-to-EDC integration models, identify practical challenges, verify automatically transferred data, and determine source documentation in integrated environments.
A hemoglobin value posts in the electronic health record at 2:14 PM. By 2:15 PM, without any human intervention, that value appears in the study's electronic data capture system -- mapped to the correct visit, the correct CRF field, the correct participant. No transcription. No manual data entry. No possibility of the coordinator typing 12.4 when the result was 14.2.
This is the promise of EHR-to-EDC integration, and it is genuine. The elimination of manual transcription removes an entire category of error that has occupied much of this course. But here is what the promise does not mention: at 2:14 PM, when that hemoglobin posted, it was a preliminary result. The hematology analyzer flagged the sample for manual review. By 3:45 PM, the laboratory technician corrected the value from 12.8 to 11.6 g/dL -- a clinically significant difference in a trial with a hemoglobin-based exclusion criterion. The integration engine, which runs on a scheduled transfer every 60 minutes, had already sent the 12.8 value to the EDC. The corrected 11.6 value will not transfer until the next cycle. And unless someone is watching for exactly this kind of discrepancy, the study database will carry an incorrect hemoglobin value that no one transcribed wrong -- because no one transcribed it at all.
This lesson examines the operational reality of EHR-to-EDC integration from the coordinator's perspective. In Module 2, you learned when and how the electronic medical record serves as source documentation. In Module 4, you learned to navigate EDC systems and enter data accurately. This lesson addresses what happens when those two systems are connected by automated data transfer -- and why that connection, far from eliminating the coordinator's data quality responsibilities, transforms them in ways that demand new vigilance.
Clinical Research Coordinator
Full course · Data Collection and Source Documentation
Free Lesson Preview
Module 1: Lesson 1
Understand EHR-to-EDC integration models, identify practical challenges, verify automatically transferred data, and determine source documentation in integrated environments.
A hemoglobin value posts in the electronic health record at 2:14 PM. By 2:15 PM, without any human intervention, that value appears in the study's electronic data capture system -- mapped to the correct visit, the correct CRF field, the correct participant. No transcription. No manual data entry. No possibility of the coordinator typing 12.4 when the result was 14.2.
This is the promise of EHR-to-EDC integration, and it is genuine. The elimination of manual transcription removes an entire category of error that has occupied much of this course. But here is what the promise does not mention: at 2:14 PM, when that hemoglobin posted, it was a preliminary result. The hematology analyzer flagged the sample for manual review. By 3:45 PM, the laboratory technician corrected the value from 12.8 to 11.6 g/dL -- a clinically significant difference in a trial with a hemoglobin-based exclusion criterion. The integration engine, which runs on a scheduled transfer every 60 minutes, had already sent the 12.8 value to the EDC. The corrected 11.6 value will not transfer until the next cycle. And unless someone is watching for exactly this kind of discrepancy, the study database will carry an incorrect hemoglobin value that no one transcribed wrong -- because no one transcribed it at all.
This lesson examines the operational reality of EHR-to-EDC integration from the coordinator's perspective. In Module 2, you learned when and how the electronic medical record serves as source documentation. In Module 4, you learned to navigate EDC systems and enter data accurately. This lesson addresses what happens when those two systems are connected by automated data transfer -- and why that connection, far from eliminating the coordinator's data quality responsibilities, transforms them in ways that demand new vigilance.
Clinical Research Coordinator
Full course · Data Collection and Source Documentation
This is just the beginning
The full CRC track covers 8 courses from study start-up to close-out — the skills sponsors actually look for.
Start the CRC trackThis is just the beginning
The full CRC track covers 8 courses from study start-up to close-out — the skills sponsors actually look for.
Start the CRC track