professor dipak kalra digital health assembly 2015

Electronic Health Records for Clinical Research

GLOBAL SHARING FOR GLOBAL

HEALTH:

TRUSTWORTHY REUSE OF HEALTH

DATA

Digital Health Assembly, Cardiff

Dipak Kalra President of EuroRec

Professor of Health Informatics, UCL

Responding to a convergence of needs

2

Need to remove the bottlenecks to accessing and combining

health data from diverse sources across Europe

Clinical Research needs

Optimise clinical research processes

•achieve faster and more accurate

patient identification

• identify sites that have access to the

most suitable patients

• reduce protocol amendments

Enhance access to Real World Data

•study the use of new medicines in real

populations

•conduct comparative effectiveness

studies

•monitor long term safety

•gather evidence for adaptive licensing

Healthcare needs

Improve quality and safety of care

•enhance care co-ordination

• increase adherence to clinical

evidence

• reduce medical errors and treatment

delays

Support patients in self-care and health

maintenance

Improve efficiency of care

•optimise care pathways to improve

outcomes

•collate evidence for public health

strategy and decision-making

Interoperability Data security, privacy &

ethics

Scalability and

sustainability

Common challenges to the use of health data for person

centred care, and the re-use of health data for clinical research

3

Confidence in data


A unique initiative

EHR4CR – Electronic Health Records for Clinical

Research

Re-use of EHR data for optimising Clinical trials

Mandated by IMI

One of the largest European public/private

partnership projects in this area

4-year project (2011-2015)

Extended into 2016 for making the transition to a sustainable

platform.

Budget of € >16m

5

For more information:

http://www.ehr4cr.eu/


Brings together key stakeholders

6

35 participants

including

pharmaceutical

industry, academia ,

hospitals, small and

medium-sized

enterprises, patient

associations and

public authorities

11 hospital

sites

Advisory

boards and

other experts

Identifying and recruiting suitable patients and trial sites are principal causes of trial delays

Delayed trials waste costly resources and slow access to new drugs

Patient recruitment a major cause of trial delays

7

50% of today’s clinical trials fail to achieve the target recruitment rate4

Almost

half of all trial

delays caused by patient recruitment problems2

1. State of the Clinical Trials Industry: A Sourcebook of Charts and Statistics, Center Watch, 2008. 2. Study Participant Recruitment and Retention in Clinical Trials: Emerging strategies in Europe, the US and Asia, Business Insights, June 2007. 3. Beasley, “Recruiting” 2008 4. Tufts -http://clinicalperformancepartners.com/wp-content/uploads/2012/07/Fixing-Feasibility-Final-Jan-2012.pdf

Each day a drug is delayed from market, sponsors lose up to

$8m3

The percentage of studies that complete enrolment on time:

18% in Europe,

7% in the US1


1. A self-sustaining economic model

2. A roadmap for pan-European adoption

A SET OF TOOLS AND SERVICES

Project deliverables

8

BUSINESS MODEL

A set of tools and services

Validated through pilots

Different therapeutic areas (e.g. oncology, neuroscience, diabetes, CVS…)

Several countries (under different legal frameworks)

1. Protocol Feasibility

2. Patient Identification and Recruitment

3. Clinical Trial Data Exchange

TECHNICAL PLATFORM

Requirements informed by stakeholders

95% in favour of reuse of EHR data

(internal & external stakeholders)

Identified issues that need to be addressed

Priority services: protocol feasibility,

patient identification and recruitment,

exchanging data with EHRs for clinical trial

data collection, adverse event reporting

Interviews with stakeholders helped inform

software requirements (Protocol Feasibility

Service and Patient Identification and

Recruitment Service)

9

203 respondents from

23 EU countries

Pharma, academia, CROs,

Patient advocacy groups, Health

agencies, IT providers

EU survey

95% rated compliance with

ethical, legal and privacy

requirements as the

highest, or equal highest

driving force for success

of EHR4CR1

1. Kalra D, Schmidt A, Potts HWW, Dupont D, Sundgren M, De Moor G, on behalf of the EHR4CR Research

consortium. Case Report from the EHR4CR Project: A European Survey on Electronic Health Records Systems

for Clinical Research. iHealth Connections 2011; 1(2): 108-113.

Gateway to a pan-European network of clinical sites.

The EHR4CR initiative

10

EHR4CR

A trustworthy service platform able to unlock clinical

information stored in EHRs for improving clinical research

Open platform

Service Oriented Architecture

Standards based

Maximal service decoupling

Objectives

Stimulate alternative tool development

Open towards vendors/tool providers

Open to different semantic interoperability approaches

Create added-value by enabling service re-use beyond

EHR4CR

Infrastructure

Semantics

(end-user) Tools

Hospital

Connectors

Protocol feasibility demonstration

11


Subject Identification & Recruitment

12

(Re-)define study Invite sites of interest Start study Track progress

Identify & Recruit Report Update Accept


Model: value propositions

To establish the value

Compare EHR4CR conditions to

current practice

13

Cost-Benefit Assessment (CBA)

Inputs Volumes

Time

Effort

Cost

EHR4CR

Services

Efficiency Gains

Reduction in

man-time and

costs

Robust

Methodology

Monte Carlo

Simulations

Growth Swift and scalable

market

penetration

To forecast business results

Balance sheets revenues minus expenses

Profitability ratio revenues divided by expenses

Business Model Simulation

Profitability and

Sustainability

Validation experts opinions


Where we are now…

EHR4CR - IMI

research project

14

Operational pan-

European platform

Project pilot hospitals

11 major hospitals in 5 countries.

Germany (2), France (2), UK (5),

Switzerland (1), Poland (1)

12 studies, de-identified data

from >500k patients over 11

sites

Scaling up the

solutions!

Technology

Operations

Governance

Sustainability

Operational pan-European platform

Permanent network of clinical sites

giving access to millions of patients in close

to real time

Trial design and recruitment supported by

real-world evidence on a European scale


ENSURING TRUST

WHEN RE-USING

EHRS FOR

RESEARCH

Information governance framework and products

16

EHR4CR governance design principles

Analyse de-identified health records at participating hospital sites

Platform only connected to dedicated repository approved by each

hospital for EHR4CR use

For protocol feasibility and patient identification/recruitment, only

patient counts (totals and sub-totals) are returned from each

hospital to the central EHR4CR Platform, never patient level data

Platform never stores or communicates data about single data subjects

Data about individuals, who might be invited into a study, remain

internal to the hospital and abide by its local governance rules

Only treating physicians can re-identify candidate patients

EHR data is only shared - within the hospital - with a clinical

research team if the patient has given that specific consent

17

Ensuring robust governance

Only approved users are formally registered and given secure log in credentials

Users have no means of requesting or obtaining patient level data through the services

Even patient numbers are suppressed if the numbers are very low

State of the art information security measures are used throughout

Audit logs are captured at key communications points:

Pharma sites, within the Platform and at hospitals

A Code of Practice and Standard Operating Rules will govern the actions of all parties using the EHR4CR services

18


Slides courtesy of

Brendan Delaney Professor of General Practice, KCL

Translational Research and Patient Safety in Europe

www.transformproject.eu

• €7.5M EU Framework 7 Project

• March 2010-May 2015*

• Funded under the Patient Safety Work program of FP7

– To support decision making

– To support clinical trials

– As part of a ‘Rapid Learning Healthcare System’

*requested extension to Nov ‘15


Aims of TRANSFoRm

• To develop methods, models, services, validated architectures and demonstrations to support the learning health system, via three use cases:

– Epidemiological research using primary care records, including genotype-phenotype studies and other record linkages across multiple sites

– Research workflow embedded in the EHR with PROMS

– Decision support for diagnosis linked to an EHR


An Learning Health System that is

trusted and valued

• Building confidence and trust in the data inputs.

– PROVENANCE model

– Model for collecting meta-data for data quality

– PROMs via mobile and web

• Building confidence and trust in the process

– Analysis of EU data protection policies using a graphical approach and a ‘zone model’ (Kuchinke et al Int J Med Inf 214)

– Approach to privacy based on existing processes of data owners and processors based on the zone model


Non-care zone

Care zone

Subzone 2

Research zone

Data controller

Res

earc

h q

ues

tio

n

Secondary DB

privacy

filter

Subzone 1

Care DB

GP

filter

privacy

New linked DB

privacy

filter

researcher

Data controller

database

Res

earc

h q

ues

tio

n

filter

privacy Privacy filter

L Linker

L

L

EMIF IMI Project

EMIF consortium

25

56 partners

14 European countries

represented

56 MM € worth of resources

(in-kind / in-cash)

“3 projects in one”

5 year project

(2013 – 2017)

To be the trusted European hub for health care data intelligence

enabling new insights into diseases and treatments

Focus of EMIF Secondary use of health data to improve life sciences research

26

The value of healthcare data for secondary uses in

clinical research and development - Gary K. Mallow,

Merck, HIMSS 2012

Project Vision: “Think Big”

27

To enable and conduct novel research into human health

by utilising human health data at an unprecedented scale

• Access to information on ~ 50 million patients

• AD research on 10-times more subjects than ADNI

• Metabolics research on > 20,000 obese & T2DM subjects

• Linkage of clinical and omics data

• Build a network of data sources and relevant research

• Development of a secure (privacy, legal) modular platform

EMIF – platform for modular extension

28

Available data source – EMIF-Platform

29

EMIF systems view

30

EMIF proposed service levels

31

EMIF Catalogue main headings

32

1. Database Administrative Information

2. Database Characteristics

3. Database Population

4. Data Held

5. Ability to Gather Supplementary Data

6. Ethical Issues

7. De-identification, Linkage

8. Data Set Description, Metadata

9. Examples of Events and Outcomes

10.Documents and Publications

11.Comments

12.EMIF Database Fingerprint Provenance

EMIF profiling tools: examples

33

Detailed analysis - e.g. using TranSMART

34

EMIF: transient “Private Research Environments”

35

EMIF-Platform

Data

Aggregators

Users will only have access to

data they need for an

approved study

Enables each data source to

release only the data set needed

for a study

Only focused ethical approvals are

needed

Constrained set of data sharing

stipulations to comply with

Contains the number of users,

uses, time window of access

Tractable disclosure control

Contained accountability for EMIF User

• Permitted through data

sharing agreements

• Covered by ethical approvals

• Governed by disclosure and

usage policies

• Held by TTP

• Protected by PET

• Fully audited

• Limited availability

Data Sources

EMIF Ethical Code of Practice - in development

36

Developed in order to help ensure:

that the EMIF Platform and Services are used in ways that

comply with legislation and policies on data protection

that EMIF is visibly upholding best practices in the protection of

personal privacy

that EMIF is promoting best practices in the conduct of clinical

research using health data for the public good

EMIF Ethical Code of Practice - main principles

37

Defines the concept of bona fide research, and bona

fide research organisations

Formalises the provisions of data sharing agreements

Stipulates transparency by data sources

of the nature, quality and currency of their data, identifier and

linkage mechanisms

of the arrangements for data sharing, including permitted uses,

approvals process, access fees, publication policy, governance

arrangements

Stipulates the conduct of data users

adhering to permitted uses, maintaining records of users and

use, protecting patient privacy, acknowledging data sources

EMIF Ethical Code of Practice - main principles

38

The CoP also covers:

Collection and use of data subject consent

Ethical approvals

Data and privacy protection

Information security measures

Re-identification and informing research subjects

Collection and use of human biological samples

Establishes oversight by, and escalation to, an Ethical and Governance

Team

39

Need to remove the bottlenecks to accessing and combining

health data from diverse sources across Europe

• Distributed queries

• Only patient counts leave a hospital

• Specific use for protocol feasibility and

patient recruitment

• Platform never stores or communicates

data about single data subjects

• Only treating physicians can re-identify

candidate patients

• Standard operating rules

• Robust identify management,

information security and audit

• Provenance metadata captured throughout

the architecture

• Strong separation between zones for

clinical use and research use

• Pseudo-identification and linkage managed

by a trusted “middle” zone

• Transient data pools per specific

research question and team

• Ethical code of practice

• Limited to bona fide research

• Requirement for data sharing

agreements

• Transparency of data sources

• Pre-agreed purposes of use

• Stipulated conduct of all parties to

protect privacy, ensure equity and

appropriate acknowledgement

There is a need for harmonised best practices & sustainability

The European Institute for Innovation through Health

Data

41

Specifications and standards

Value

assessment

research

programs

Accreditation

and

Certification

Oversight,

governance,

auditing

Guardian of

shared

Intellectual

Property

Best

practices in

standards

development

and adoption

Critical to the sustainability of a clinical research e-infrastructure

Provides a trusted environment for a research platforms ecosystem to develop

Not-for-profit, formally registered company providing services to registered members (e.g. data providers, data users, service providers)

Funded by license fee, subscriptions, certification, membership (cover cost of operations and providing services to registered members)

Incomes reinvested to improve services & fund public interest research

Governing the EHR4CR ecosystem

42

EHR4CR

SERVICE PROVIDER

APPLICATION PROVIDERS

SERVICE

USER NETWORK

PROVIDER

SERVICE

USER

OTHER DATA

AGGREGATORS

DATA PROVIDER

RESEARCH

SPONSOR

RESEARCH

SPONSOR

DATA PROVIDER

Educate and train

research and ICT

staff

ICT SOLUTION PROVIDERS

Accredit staff

and

organisations

Certify service

providers

and EHR systems

Oversee and audit

governance &

security

RESEARCH

ORGANISATIONS

APPLICATION PROVIDERS

Demonstrating value from the use of health data

43

Develop comprehensive

value assessment programme, to demonstrate:

•faster and more efficient clinical trials •better information for public health •improved quality of EHR data •good practice in privacy protection •successful eHealth/eResearch ICT sector •budget impact assessments for key

stakeholders •positive patient and societal acceptance

Value

to hospitals

Public awareness of the

benefits to patients

Value

to Pharma

Grow a Network

of Excellence

Promote globally

44

Harmonised health information and

standards

Solutions for better quality health data,

and legitimate uses of health data

Intelligence derived from health data

e.g. research, clinical outcomes

Quality assessments, certification and

audit

Synergy and consensus amongst

stakeholders

Best practices in information

governance

The European Institute

for Innovation through

Health Data

Main activities

Building synergy and consensus

The Institute will act as a focal point bringing stakeholders together to share

experiences, agree common priorities and approaches, working towards

convergence and cross-fertilisation between:

45

Patient associations

Citizen, family and carer associations

Health professional associations

Clinical and informatics academia

Healthcare providers

National decision makers

Third party payers, commissioners

EHR system and applications vendors

Medical Device vendors

Pharma, Bio-tech

Regulators

Standards development organisations (SDO)

Multi-national decision makers

Social care providers

Electronic health (eHealth) competence centers

46

THANK YOU

professor dipak kalra digital health assembly 2015

Healthcare

data electronic health

global health

clinical evidence

health maintenance

clinical research processes

reuse of health data

europe clinical research

us1 electronic health