Laboratory data integrity review process flowchart
A laboratory data integrity review process chart for scoping affected records, assessing provenance and audit-trail evidence, containing concerns, assigning follow-up and documenting disposition.
What the laboratory data integrity review process is
A data integrity concern can begin with a routine review, an unexpected audit-trail entry, a missing source record or an observation from another process. The first responsibility is to identify the affected data and systems without prematurely deciding what the finding means.
The chart separates that scope and evidence review from the later disposition. If the evidence does not support reliability, affected data can be contained and a follow-up path assigned; if further remediation is needed, Quality Assurance records the owners and actions rather than letting the concern disappear in a review note.
What this flowchart covers
In this template
- Data Owner, Data Reviewer and Quality Assurance lanes define the handoffs from scoping to assessment and follow-up.
- Affected data and systems identified? creates a loop to secure records and clarify scope before evaluation.
- Evidence supports data reliability? separates a documented conclusion from containment and investigation of a concern.
- Further escalation or remediation needed? assigns a follow-up path before the final disposition is recorded.
When to use this template
- You need an editable workflow for routine data-integrity reviews and concerns raised by laboratory records or systems.
- Data owners, reviewers and quality staff need a shared route for protecting records while facts are assessed.
- A review may lead to continued controlled use, investigation, remediation or another local disposition that needs named owners.
How it works
Map the data landscape
List the record types, instruments, applications and repositories that this workflow covers. Add the people who can secure access or preserve evidence when a concern is opened.
Define the review evidence
Replace the provenance, access and audit-trail examples with the evidence your procedure requires. Do not turn the template into a claim that one set of checks is sufficient for every system.
Separate containment from conclusion
State what your team does to protect affected data while it is assessed, and who can decide its disposition. Keeping those actions separate avoids treating an initial containment step as a final conclusion.
Connect follow-up workflows
Link the investigation, corrective-action, system-owner or management routes used when remediation is needed. Record the owner and review point for each follow-up instead of treating escalation as an endpoint.
Frequently asked questions
What does a laboratory data integrity review process cover?
It covers opening a review or concern, identifying affected data and systems, assessing relevant evidence, deciding whether records can support their intended use, containing concerns and assigning any needed follow-up before documenting disposition.
Why does the chart contain data before a final conclusion?
Containment protects records and affected work while the facts are assessed. It is not a declaration that the data is invalid; the final disposition follows the review and any investigation or remediation required by the laboratory's procedure.
Does this template define data-integrity requirements?
No. It is an editable process map, not a compliance standard or universal control list. Laboratories should define the systems, evidence, escalation criteria and roles that apply to their own quality system.