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Disclosure Control in Practice: issues and approaches. Andy Sutherland Health and Social Care Information Centre. Outline. Background – transparency, open data, confidentiality, Code of Practice and other requirements Basics of disclosure control Approaches used Issues Reflections.

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Disclosure Control in Practice: issues and approaches

Andy Sutherland

Health and Social Care Information Centre

outline
Outline
  • Background – transparency, open data, confidentiality, Code of Practice and other requirements
  • Basics of disclosure control
  • Approaches used
  • Issues
  • Reflections
background
Background
  • Transparency, open data
    • Publish in as much detail as possible
    • Make machine readable
    • Allow and encourage re-use
  • Confidentiality
    • Data Protection Act, Common Law requirements etc.
code of practice
Code of Practice
  • Principle 5, practice 1
    • “Ensure that official statistics do not reveal the identity of an individual, or any private information relating to them, taking into account other relevant sources of information.”
  • Principle 5, practice 4
    • “Ensure that arrangements for confidentiality are sufficient to protect the privacy of individual information, but not so restrictive as to limit unduly the practical utility of official statistics.”
  • National Statistician’s Guidance
other guidance
Other Guidance
  • ONS work on health

http://www.ons.gov.uk/ons/guide-method/best-practice/disclosure-control-of-health-statistics/index.html

  • Scottish Government guidance

http://www.scotland.gov.uk/Topics/Statistics/About/Methodology/Glossary

  • Various consultations ongoing

http://www.ico.gov.uk/news/latest_news/2012/ico-consults-on-new-anonymisation-code-of-practice-31052012.aspx

  • DH v ICO [abortion statistics case]

http://www.ico.gov.uk/foikb/PolicyLines/FOIPolicyPersonaldata-anonymisedstatistics.htm

user comment
User comment
  • “…Basically ONS and IC only care about disclosure control and don't give a toss as to whether data are any use to users.”
why disclosure control is needed
Why disclosure control is needed?
  • Basic revision class!
    • Number of A+E consultants by hospital, March 2012
why disclosure control is needed1
Why disclosure control is needed?
  • Basic revision class!
    • Number of A+E consultants by hospital and ethnicity, March 2012
hscic process and approaches
HSCIC process and approaches
  • 150 publications per year
  • Other releases
    • Ad-hoc queries
    • Data access or analysis systems
  • Standard risk assessment process
  • “Small Numbers Panel” assesses complex cases
small numbers panel
Small Numbers Panel
  • Head of Profession for Statistics (Chair)
  • Head of Information Governance
  • Programme Manager, Information Services
    • statistical, legal and business/user input.
issues 1
Issues (1)
  • Understanding of scope
    • Distinguishing cases where disclosure control is needed (“I don’t want inadvertently to release identifiable information”) from those where different legal approaches are needed (“I know this is identifiable but I need to do it anyway”).
issues 2
Issues (2)
  • Seeing the wider context
  • Proposal to publish practice-level prescribing data
    • Legality
    • Level of granularity and frequency of publication
    • Feasibility
    • Costs, benefits and risks
    • Perverse outcomes
issues 3 maternity tables
Issues (3) – Maternity tables
  • Enhanced, easier for users to interpret
    • Overview of main delivery types
    • Easy to compare (in one table)
    • Available as automated reports to provider level - http://www.hesonline.nhs.uk/Ease/servlet/ContentServer?siteID=1937&categoryID=1815
  • Unexpected consequences
    • More suppression due to tables within tables
    • ‘Unknown’ values were used for secondary suppression, these are used to calculate rates; now try to avoid using for secondary suppression.
method of delivery 2008 09
Method of delivery (2008-09)

Unable to aggregate to SHA level

Unable to aggregate delivery types (e.g. Spontaneous), therefore cannot calculate rates

method of delivery 2009 10
Method of delivery (2009-10)

Unable to calculate rates as lots of ‘Unknowns’ are suppressed

Able to used aggregated data (SHA level)

Able to use aggregated data (Delivery types), therefore can calculate rates

Rate = Spontaneous / (Total – Unknown)

suppression example
Suppression Example

Table D: Method of delivery – example (2009-10)

  • Primary suppression
    • All values equal to 5 or less (excluding unknowns)
suppression example1
Suppression Example

Table D: Method of delivery – example (2009-10)

  • Secondary suppression
    • All values corresponding to primary suppressed values
    • Row and column, effectively four tables
    • ‘Other’ suppressed, therefore also ‘Unknown’ –
    • unable to calculate the rate
suppression example2
Suppression Example

Table D: Method of delivery – example (2010-11)

  • Suppression
    • Similar primary and secondary suppression values
    • ‘Other’ no longer suppressed as not disclosive
    • Therefore ‘Unknown’ not suppressed, can calculate rate
issues 4
Issues (4)
  • Blanket protocols
    • Can be difficult to adapt in light of changing environment, and act as a brake on wider release
    • Often need to suppress as a whole rather than just where disclosure is an issue
    • Often needed as individual manual suppression can be time consuming
issues 5
Issues (5)
  • Implications of providing “systems” and machine readable files, rather than just reports
    • Allows potentially disclosive cross classifications to be produced
    • Standard primary and secondary suppression approach breaks down
    • Record swapping (cf census) is a possibility
    • For our less critical applications prefer a combination of primary suppression and rounding
issues 51
Issues (5)
  • Understanding the data and risks
    • Clinical Audits
    • Classic disclosure control problem with sensitive data overlaid by incomplete (but improving) data collection.
    • Risk management approach likely to change in time, and may become more difficult when data is better!
reflections
Reflections
  • No approach is infallible – it is a matter of assessing risk
  • Important to consider user needs
  • This is one (important) component of the release process
  • Don’t assume more information will be more helpful!
  • Blanket protocols should allow some “flex”
  • “Jigsaw identification” remains a worry
final word
Final word
  • Our approaches and their outcomes are on our website. Feel free to inspect and comment.

www.ic.nhs.uk

andy.sutherland@ic.nhs.uk