In a Tufts CSDD survey of 257 sponsors and CROs, it took an average of 8.1 days from a patient visit to data entry in EDC, and 36.3 days from last patient last visit to database lock (Wilkinson et al., Therapeutic Innovation & Regulatory Science). Companies that had their full database live before first patient averaged 5 days from visit to entry and 31 days to lock; those that went live later took 10 and 54 (Tufts CSDD release via Business Wire).
The visit-to-entry gap is mostly waiting: for a coordinator to have time, for paper worksheets to be transcribed, for a backlog to clear before a monitoring visit. When eSource feeds EDC, integrated data reaches the study database as soon as the visit is documented, and every step after it can start sooner.
What changes along the data path
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Step
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Manual transcription
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eSource feeding EDC
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Visit to data in EDC
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Days, depending on staff time
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As soon as the visit is documented, for integrated fields
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Edit checks fire
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When data is typed in
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Shortly after the visit
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Queries raised
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Days or weeks after the visit
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While the visit is fresh
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Query answered
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Site searches old notes
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Site answers with the visit still in mind
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Data cuts for reviews
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Wait for catch-up entry
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Run on current data
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Database lock
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Final weeks spent on backlog
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Mostly cleaning and reconciliation
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1. The entry lag shrinks for integrated data
The 8-day average is not typing time. It is the queue in front of typing. Removing re-entry for integrated fields removes that queue for those fields.
2. Queries are raised while the visit is fresh
An edit check that fires the day after a visit is easier to resolve than one that fires two weeks later. Sites answer from memory and current notes, rather than searching for a record.
3. Data reviews and safety reviews use current data
Data monitoring committees, interim analyses and medical review all depend on a data cut. When data reaches EDC quickly, those cuts reflect the study as it is, with less effort spent chasing missing entries beforehand.
4. Less catch-up before monitoring visits and milestones
Sites often enter a backlog of data before each monitoring visit or data cut. Integration removes much of that peak workload, which also reduces errors made in a rush.
5. Lock becomes a cleaning step, not a catch-up step
With data current throughout the study, the period after the last visit is spent on final cleaning, coding and reconciliation, not on entering and querying data that should have been in the database weeks earlier.
Data timeliness checklist
- Measure visit-to-entry time by site, for integrated and manual fields separately
- Track query age and time to resolution
- Set a target for open queries at each data cut
- Plan data cuts on current data, not after a catch-up push
- Run SAE reconciliation and coding monthly
- Have the full database and integration live before first patient
What this means by role
- Clinical data managers: earlier queries, smaller backlogs and a shorter path to lock.
- Clinical operations directors: faster data supports earlier decisions on safety, sites and enrolment.
- Biostatistics and medical review: data cuts reflect the study as it is.
- CRCs: fewer catch-up sessions before monitoring visits.
- CRAs: fewer missing-data items to chase at each visit.
How Cloudbyz approaches this
Cloudbyz eSource and EDC are built natively on Salesforce. According to Cloudbyz product materials, eSource covers visit management, eCRFs, vitals, lab reports, AE capture, device integrations and query management, with export of data to EDC, and EDC supports edit checks, query management and data export. How much data flows without re-entry depends on how each study's eSource templates and EDC forms are configured.
See data move from visit to EDC
The Cloudbyz team can walk through a visit recorded in eSource and appearing in EDC. Book a demo or visit cloudbyz.com.
