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The Scottish Health Informatics Programme Health Statistics User Group

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Title: SHIP Author: vwarwick Last modified by: Frank Sullivan Created Date: 9/30/2009 2:37:09 PM Document presentation format: On-screen Show (4:3) Other titles – PowerPoint PPT presentation

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Title: The Scottish Health Informatics Programme Health Statistics User Group


1
The Scottish Health Informatics ProgrammeHealth
Statistics User Group
  • Frank Sullivan FRSE, FRCP(Glas.), FRCGP
  • NHSTayside Prof of RD in GP 1y care Director
    Health Informatics Centre

2
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3
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4
Deterministic linkage
CHNo
Lab Data
Screening
Hospital SMR
Dental
Investigations
Primary Care
Social Services
Pharmacy
5
Community Health Number
28 12 57 02 5 0
Sex
Date of Birth
Checksum
Sequence
6
Record-Linked DataCompleting the Jigsaw
Lab Data
Dental
GP
CHNo
Pharmacy
Hospital
Social Services
Screening
Investigations
7
Scottish data from cradle to grave
AE
8
Navigation
  • Who we are
  • Aims of SHIP
  • Core programmes
  • Research programmes
  • The plan
  • Safe havens
  • The detail

9
Navigation
  • Who we are
  • Aims of SHIP
  • Core programmes
  • Research programmes
  • The plan
  • Safe havens
  • The detail

10
Who we are
  • Our funding comes from

Universities of Dundee, Edinburgh, Glasgow and St
Andrews and the Information Services Division of
NHS Scotland
11
Governance
Scientific Management Group
International Advisory Board
SHIP Programme Manager
Core Programmes
Research Programmes
12
  • Who we are
  • Aims of SHIP
  • Core programmes
  • Research programmes
  • The plan
  • Safe havens
  • The detail

13
The present
  • Linkage of a national diabetes dataset (SCI-DC)
    to a a datamart of Scottish Morbidity Register
    (ACaDMe)
  • RD approval from each board
  • 8 page form, covering letter, CV, proposal,
    sponsor letter, funder letter
  • Ethics approval 23 page form
  • PAC approval 11 pages
  • 14 Caldicott guardian approvals
  • Calidcott guardians difficult to identify
  • Took 4 months to get all replies
  • many needed chasing, 5 requested further
    information

14
We aim to
  • Create a research portal for EPRs already held by
    NHS Scotland that will provide rapid, secure,
    access to the type of data that clinical
    scientists require.

15
We aim to
  • Develop and evaluate systems that work across
    institutional boundaries to allow linkage between
    large, federated, third party research datasets
    and the NHS research portal.

16
  • Who we are
  • Aims of SHIP
  • Core programmes
  • Research programmes
  • The plan
  • Safe havens
  • The detail

17
Core Programmes
C4 Engaging The Public
C3 Engaging Researchers
C2 Gov-ernance
C1 Provisioning Datasets
18
C1 Provisioning Datasets
  • Aims
  • To create a research portal for EPRs already held
    by NHS Scotland, the Scottish Health Information
    Service for Research (SHIS-R).
  • To develop and evaluate innovative technical
    approaches that allow linkage between large,
    federated, third party research datasets between
    themselves and with SHIS-R.
  • To develop and evaluate systems that work across
    institutional boundaries with adequate data
    manipulation and statistical functionality that
    provide rapid, secure, access to the type of data
    that clinical scientists require.

19
C2 Governance
  • Aim
  • To analyse the ethico-legal and cultural
    challenges associated with the secondary use of
    EPRs with a view to mapping the elements
    necessary to contribute to an optimal governance
    regime
  • 3 dimensions
  • Scottish
  • International
  • Interdisciplinary

20
C3 Engaging Researchers
  • Aims
  • To host a biennial conference Exploiting
    Existing Data for Health Research . It has 5
    themes
  • The value of record linkage in health research
  • Record linkage for health care improvement
  • Longitudinal record linkage
  • The methodological challenges of record linkage
  • Confidentiality, disclosure and ethical issues
  • To develop and deliver training programmes and
    workshops for EPR research

21
C4 Public Engagement
  • Aims
  • To synthesise existing evidence on citizens
    attitudes towards sharing personal data for
    research.
  • To generate new evidence on the acceptability of
    different levels of data sharing under varying
    conditions.
  • To engage the wider public with the aims and
    outcomes of the SHIP through specific
    consultation exercises.
  • To link the public engagement activities into the
    development of governance frameworks (C2).
  • To examine novel methods of making health data
    available to the public.

22
  • Who we are
  • Aims of SHIP
  • Core programmes
  • Research programmes
  • The plan
  • Safe havens
  • The detail

23
Research Programmes
RP2 National Epidemiology
RP4 Demographic, Socio-Economic Environmental
Data Linkage
RP1 EPR Support of Clinical trials
RP3 Pharmaco- vigilance
24
RP1 Support of Clinical Trials
  • Aim
  • To evaluate how EPRs can best support the conduct
    of a range of clinical trials
  • Can we identify eligible patients?
  • Can we extract follow-up information from GP
    records?
  • Can we get endpoints from routinely collected
    data?

25
RP2 National Epidemiology
  • Aim
  • To perform epidemiological studies on a national
    scale and use the information to estimate current
    and future health costs using diabetes as an
    exemplar.
  • Develop risk engines for CVD in diabetes to
    inform statin prescribing
  • Use retinopathy data to look at screening
    intervals
  • Explore glycaemic control and CVD
  • Explore novel associations between diabetes and
    other diseases
  • Modelling current and future diabetes care costs

26
RP3 Pharmacovigilance
  • Aim
  • To link community prescribing data to EPRs to
    demonstrate the feasibility of national
    pharmacovigilance
  • using longitudinal datasets that link drug
    exposure and morbidity to discover previously
    unknown drug effects
  • developing novel methods of analysis and
    comparing them with traditional approaches
    Variational Bayes Algorithms

27
Year 2 of RP3
  • Development of Specific analytic tools and
    software for supervised learning
    (classification)
  • Development of Specific tools for unsupervised
    learning (clustering)
  • Definition of specific ADR hypotheses to test
  • Definition of the specific drugs to include in
    unsupervised inference of likely ADRs and
    pleiotropic effects
  • These tools will exploit several different kinds
    of contrast including survival analyses, case
    cross over analyses case control etc.

28
RP4 Demographic, Socio-Economic and
Environmental Data Linkage
  • Aims
  • to link information given by respondents in
    genetic studies back through time using the
    records of births, marriages and deaths since
    1855.
  • Complex genealogies are being built up which will
    be used to look at genetic effects in
    epidemiological studies
  • to estimate the effects of exposure to various
    environmental agents on health by linking
    environmental pollution data to hospital
    admissions and the Scottish Longitudinal Study
    (SLS)

29
  • Who we are
  • Aims of SHIP
  • Core programmes
  • Research programmes
  • The plan
  • Safe havens
  • The detail

30
Formulating the plans
  • Review of existing practice (completed August
    2010)
  • Information governance of use of patient data in
    medical research in Scotland current and future
    scenarios
  • Public engagement
  • 8 focus groups by March 2011
  • Expert working groups (final report 11/11/10)
  • On Governance, IT and Administration
  • Consultation with key stakeholders
  • Secure data linkage access workshop 09/02/10
  • Governance public engagement workshop 13/12/10

31
Improving Governance
  • Increasing transparency reducing uncertainty
  • Setting standards Principles Best Practices
  • Clarifying Responsibilities Data Flows Data
    Controllers
  • Seeking buy-in from stakeholders

32
Good Governance Framework
  • Principles foundational starting points for
    deliberation and action
  • Best practice instances of implementation of
    principles to a high standard
  • Content
  • Public interest and the importance of research
  • Privacy/Anonymisation/Consent/Data Protection
  • Authorising/advisory bodies
  • Governance/Access
  • Trusted Third Parties (where appropriate)
  • Clinical Trials
  • Cross-sector sharing and sharing agreements
  • Public engagement and benefit sharing

33
Public Interest / Personal Privacy
  • Scientifically sound and ethically robust
    research is in the interest of protecting the
    health of the public.

Every effort should be made to consider and
minimise risks of identification to data subjects
34
Consent
Consent
yes
no
Anonymisation
Authorisation
and / or
35
The Vision
  • Aims to improve accessibility and provide
    metadata
  • Streamlined approvals process for health data
  • Work with SAHSC to provide local access for
    researchers at SAHSC nodes
  • A website for researchers with details of the
    process and available data
  • A national indexing service

36
Proposed Infrastructure
  • National Indexing Service
  • located in NHS NSS
  • National Safe Haven
  • Separately located in NSS
  • Linkage Agent
  • Within the national safe haven
  • Model to be mirrored at SAHSC nodes

37
  • Who we are
  • Aims of SHIP
  • Core programmes
  • Research programmes
  • The plan
  • Safe havens
  • The detail

38
Safe Havens
  • Thomas and Walport Data Sharing Review (2008)
  • environments for population based research
    and statistical analysis in which the risk of
    identifying individuals is minimised

39
Safe Projects
  • A committee decides whether the access request is
    for a valid statistical purpose

40
Safe People
  • Researchers may have to be
  • Attached to a known institution
  • Asked to attend a course
  • Bound by a strict code
  • Subject to sanctions

41
Safe Data
  • Global recoding
  • Combining categories
  • Top and bottom recoding
  • For normal distributions
  • Record swapping
  • Interchanging sensitive values between records
  • Post Randomisation Method
  • Misclassifies categorical data according to a
    predetermined probability mechanism eg 20 chance
    that a male is female
  • (Over)imputation
  • Values randomly deleted and likely values from
    similar donor records are substitued

42
Safe Settings
  • Dumb terminal prevents removal of data
  • No memory stick
  • No CD or DVD
  • No internet
  • Can be expanded to the users own computer using
    eg Citrix or Terminal Services.

43
Safe Outputs
  • Statistical Disclosure Control
  • Results produced may be checked by officers of
    the safe haven to make sure they do not contain
    any disclosive results.

44
  • Who we are
  • Aims of SHIP
  • Core programmes
  • Research programmes
  • The plan
  • Safe havens
  • The detail

45
Privacy Advisory Committee (approval of linkage
requests)
Data Source 1
Data Source 2
Data Source 3
Aggregate non- disclosive data
University dataset
SCI DC
ISD
Indexing Service
Key coded data only
Governance Safe Guards
Data Archive
Disclosure Control
Linkage Agent
Project work space
Id like to link some data
Secure Access Facility
SAFE HAVEN
46
Linkage part 1
47
Linkage part 2
48
Exploiting Existing Data for Health
Research International Conference 9-11th Sept
'11 University of St Andrews www.scot-ship.ac.uk
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