# Direct record-to-database data capture: no manual transcription, no full source verification

Source: https://onco.cc/ideas/idea-tr1-esource-ehr-to-edc/  
OnCo record `idea-tr1-esource-ehr-to-edc` (Idea). Data CC BY-NC 4.0, attribute "Data from OnCo (onco.cc)"; commercial use needs a licence.

## TL;DR

Trial staff still retype data from the hospital record into the trial database, and monitors then check every entry by hand. Piping data directly and checking by risk would cut cost and errors.

## Summary

Structured EHR data (labs, vitals, medications, imaging reports, deaths) flow into the trial database via FHIR-based eSource interfaces with audit trails; source data verification is replaced by risk-based and statistical monitoring, as permitted by ICH E6(R3). Requires standardised oncology data elements (mCODE) and vendor cooperation.

## Fields

- Kind: Idea
- Last checked: 2026-09-08
- Hypothesis: eSource trials will reduce data management and monitoring cost per patient by at least 30 percent and reduce transcription errors, with equivalent or better data quality on audit.
- Rationale: Manual transcription is the largest source of trial data error and monitoring is the largest single cost line; both are artefacts of paper-era processes. Other regulated industries moved to direct data capture decades ago.
- Proposed test: Run one cooperative-group trial with eSource at half its sites and conventional capture at the rest; compare cost, query rates and audit findings.
- Maturity: early-clinical
- Actor: engineering

## Sources

- CDISC standards: https://www.cdisc.org/
- mCODE: https://mcodeinitiative.org/

## Connected records

- technologies: [AI trial matching & clinical decision support](https://onco.cc/technologies/ai-trial-matching/)
- bottlenecks: [Data silos](https://onco.cc/bottlenecks/b-data-silos/), [Trial design, endpoints and cost](https://onco.cc/bottlenecks/b-trial-design/)

---
JSON: https://onco.cc/api/v1/entities/idea-tr1-esource-ehr-to-edc.json