Capturing Sensitive Data&

Data Linkage

Capturing Sensitive Data

Data Protection Act 1998 (Section 33) – Allows data to be used for research purposes

The Information Commissioner - data collected for National Statistics and educational research can include identifiable items.

Capturing Sensitive Data

• Maximise the quality and value of information gained from single sources

• Enhance user’s understanding of statistical information

• Efficient collection of data (value for money)

• Provide opportunities for the cross-analysis, exchange and re-use of data

Data Linkage Project

Existing Data Linkage

School Leaver Destinations –

Destination of leavers from publicly funded schools (Careers Scotland)

Pupil characteristics taken from the September Pupil Census

Data Linkage Project Aims

• Maximise the value of available administrative data and system

• Relate significant events that are remote from one another in time or location

• Facilitate the widespread and safe use of matched education data

• To establish as quickly, cheaply and accurately as possible which education related records belong to the same individual.

Investigate the data collected (quality and consistency)

Design/redesign administrative systems to allow integration and data sharing.

• Standard definitions, names and codes• Standard geographies• National (and international) standards

Matching Techniques…...

Exact matching leads to inexact results

e.g. requiring exact match on SCN, date of birth, sex - expect at least 10-15% errors because of discrepancies

Probability matching more accurate

• Quantifies the implications of levels of agreement and disagreement

• 2% true links missed

Development of the linkage methodology

Why use Probability Matching ?Surname First D ate of Postcode

initial birth

Thistle P 02/ 06/ 71 G61 3EU

Thistle P 02/ 06/ 71 G61 3EUThistle P 20/ 06/ 71 G61 3EUThistel P 02/ 06/ 70 G61 3EUThistle P 02/ 06/ 71 EH3 6TT

Areas for consideration

• Data Investigation and Data Cleaning

• Bring together the pairs of records to be compared (‘Blocking’)

• Linkage methodology

• Reporting and Refinement

• Anonymisation

Data Protection, Confidentiality and Security

• Access to person identifiable data• Defined procedures for the secure handling of

sensitive data• Organisational protocols

• Access & storage• Formal application• Impose Conditions (anonymisation)

Project Summary

• Proof of concept

• Data available for linkage

• Linkage methodology

• Conclusions and results