Aggregate output disclosure review
==================================

StatMedAnalysis | Original downloadable worksheet | 6 November 2026

Check whether a proposed research output could expose sensitive information.

How to use this worksheet
Review each table, plot and exported summary in combination with other planned releases.
Look for small or distinctive groups, subtraction opportunities and identifiers in
labels or metadata. Apply the data provider and institution rules, and seek disclosure
review when uncertain. Keep sensitive examples out of this worksheet.

Save a working copy and keep the original blank version. Use public, hypothetical or
aggregate information only; do not enter patient identifiers, credentials or confidential
records. Keep source evidence in your approved project workspace. Mark unresolved text
fields UNKNOWN or NOT REPORTED with a reason; never substitute zero for an unknown count.

Project/version __________________  Prepared by role/date __________________

Working fields
1. Output and intended audience
Response/evidence: _________________________________________________________
___________________________________________________________________________

2. Applicable disclosure rules
Response/evidence: _________________________________________________________
___________________________________________________________________________

3. Small or unique groups
Response/evidence: _________________________________________________________
___________________________________________________________________________

4. Complementary cells or differencing risk
Response/evidence: _________________________________________________________
___________________________________________________________________________

5. Labels and metadata checked
Response/evidence: _________________________________________________________
___________________________________________________________________________

6. Suppression or aggregation decision
Response/evidence: _________________________________________________________
___________________________________________________________________________

7. Utility lost and explanation
Response/evidence: _________________________________________________________
___________________________________________________________________________

8. Authorised review and release record
Response/evidence: _________________________________________________________
___________________________________________________________________________

Hypothetical worked case
A fictional table suppresses one small cell but publishes the total and every other
cell. Subtraction can recover the hidden count; complementary disclosure checks are
needed before release.

Decision rule and limitations
Release only after applicable disclosure rules and combined-output risks are addressed.
No single universal minimum cell count guarantees anonymity.

Decision _______________________  Remaining uncertainty ____________________
Next action ____________________  Owner / review date ______________________
Independent check and discrepancy resolution _______________________________

Official method or reporting reference checked 6 November 2026
https://ukdataservice.ac.uk/learning-hub/research-data-management/

This is an original planning aid, not an official checklist, validated instrument,
clinical recommendation or certificate of expert approval. Apply the referenced
guidance to the specific design and record any additional requirements.