The Scottish Health Informatics Programme

Health Statistics User Group

Frank Sullivan FRSE, FRCP(Glas.), FRCGP

NHSTayside Prof of R&D in GP &1y care Director Health Informatics Centre

Deterministic linkage

DentalDentalHospitaHospital SMRl SMR

CHNo

Primary Primary CareCare

Lab Lab DataData

PharmaPharmacycy

Social Social ServicesServices

InvestigatioInvestigationsns

ScreeninScreeningg

Community Health Number

Date of BirthDate of Birth SexSex ChecksumChecksum

28 12 57 28 12 57 02 02 55 00

Sequence

Record-Linked DataCompleting the Jigsaw

CHNoHospitHospitalal

Social Social ServiceService

ss

PharmacPharmacyy

Lab Lab DataData

DentalDental

InvestigationInvestigationss

ScreeniScreeningng

GPGP

A&E

Maternity

BIRTH

DEATH

Neonatal Record SMR11

Child health surveillance

Immunisation

GP consultations

Dental SMR13

Out patients SMR00 Hospital Admissions SMR01

Mental Health SMR04

Prescribing Screening

Community care SMR50

Cancer registrations SMR06

Cancer registry

Scottish data from cradle to grave …

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

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

Who we are

Our funding comes from:

Universities of Dundee, Edinburgh, Glasgow and St Andrews and the Information Services Division of NHS Scotland

Governance

Scientific Management Group

SHIP Programme Manager

InternationalAdvisory

Board

Core Programmes

ResearchProgrammes

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

The present

Linkage of a national diabetes dataset (SCI-DC) to a a datamart of Scottish Morbidity Register (ACaDMe)

• R&D 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

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.

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.

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

Core Programmes

C1:Provisioning

Datasets

C2:Gov-

ernance

C3:Engaging

Researchers

C4:Engaging

ThePublic

C1: Provisioning DatasetsAims• 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.

C2: GovernanceAimTo 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:o Scottisho Internationalo Interdisciplinary

C3: Engaging Researchers

Aims• To host a biennial conference “Exploiting Existing Data

for Health Research” . It has 5 themes:o The value of record linkage in health researcho Record linkage for health care improvemento Longitudinal record linkageo The methodological challenges of record linkageo Confidentiality, disclosure and ethical issues

• To develop and deliver training programmes and workshops for EPR research

C4: Public EngagementAims• 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.

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

Research Programmes

RP1: EPRSupport of Clinical trials

RP2: NationalEpidemiology

RP3:Pharmaco-vigilance

RP4: Demographic, Socio-Economic& Environmental Data Linkage

RP1: Support of Clinical TrialsAimTo 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?

RP2: National EpidemiologyAimTo perform epidemiological studies on a national scale

and use the information to estimate current and future health costs using diabetes as an exemplar.o Develop risk engines for CVD in diabetes to inform statin

prescribingo Use retinopathy data to look at screening intervalso Explore glycaemic control and CVDo Explore novel associations between diabetes and other

diseaseso Modelling current and future diabetes care costs

RP3: Pharmacovigilance

Aim• To link community prescribing data to EPRs to

demonstrate the feasibility of national pharmacovigilance

o using longitudinal datasets that link drug exposure and morbidity to discover previously unknown drug effects

o developing novel methods of analysis and comparing them with traditional approaches Variational Bayes Algorithms

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.

RP4: Demographic, Socio-Economic and Environmental Data LinkageAims• to link information given by respondents in genetic studies

back through time using the records of births, marriages and deaths since 1855. o 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)

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

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

Improving Governance

• Increasing transparency & reducing uncertainty

• Setting standards: Principles & Best Practices

• Clarifying Responsibilities: Data Flows & Data Controllers

• Seeking buy-in from stakeholders

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

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

Consent

Consent

Anonymisation Authorisationand/ or

yes

no

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

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

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

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”

Safe Projects

A committee decides whether the access request is for a valid statistical purpose

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

• 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

Safe Data

Safe SettingsDumb terminal prevents

removal of data:• No memory stick• No CD or DVD• No internet

Can be expanded to the user’s own computer using eg Citrix or Terminal Services.

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.

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

Governance Safe Guards

Aggregate non-disclosive data

Data Archive

Disclosure Control

Indexing Service

University dataset

SCI DCISD

Secure Access Facility

Privacy Advisory Committee(approval of linkage requests)

Data Source 1 Data Source 2 Data Source 3

SAFE HAVEN

I’d like to link some data

LinkageAgent

Project work space

Key coded data only

Linkage part 1

Local IDsStudy numbers

Local IDsStudy numbers Indexing

Service

Datasource 1

Local IDsNamesAddressesDates of birth

Datasource 2

Local IDsNamesAddressesDates of birth

Linkage part 2

Study numbersPayload data

Study numbersPayload data

Safe Haven

Study numbersPayloaddataPayloaddata

Datasource 1 Datasource 2

Exploiting Existing Data for

Health Research

International Conference

9-11th Sept '11University of

St Andrewswww.scot-ship.ac.uk