2

The value proposition

Clinical data from your EHR can be leveraged –providing value outside the walls of the hospital.

Agenda

1. Your clinical data is important for your organization and your patients.

2. Re-using and improving your clinical data is even more important and implicates an investment.

3. Why not monetize this important resource?

4. Who could use this resource?

5. What is the value?

6. EC is showing the way forward!

“The clinical Trial network ERA est arrivé”

7. Practical ways to do it

8. What is in for you! = monetization (ROI)

Which values are important for hospitals & care providers?

Better

patient careImproved

clinical

research

Income

streamEnhanced

reputation

Healthcare Transformation Journey

6

Data gaps

•Missing data elements (e.g.

outcomes)

•RTC’s require details that

may not be routinely

collected

•Coding often only at first

level (e.g. ICD-9) therefore

missing granularity

•80% of info stored as

unstructured data

Strong Incentives to Make R&D More Effective and Efficient

Data quality

•“Longitudinality”

•Coding for administrative

reasons (up-down coding)

•Coding often months after

patient encounter

•Data provenance – who

entered the data?

“Semantics”

•Many standards – many

versions

•Complex care – many HCP’s

involved – many hand-overs

•Need to pool data cross sites

and cross different countries

•Pharma focused on CDISC

Privacy

• Clearly a top priority

• Different interpretations by

country, by region-complex

• Trust

Challenges with re-use

of patient level data

Parallel industry-centric growth in ICTPhysician/Investigator

In some

countries nearly

90% of all

healthcare

records are

digitalPatienthealth

records

Patient Care Data57% of R&D

investment is

within Clinical

Development1

Clinical trial research data

Electronic data capture of

Clinical Trial data

Over 40% of

clinical trial

data are

entered into

health record

and EDC1

Let’s find a market with the same needs so we can mirror our capabilities

R&D cost ever increasing R&D output ever decreasing

The Pharmaceutical Industry in figures. Key data 2012 – efpia report

Pharmaceutical companies have strong incentives to make R&D more effective and efficient

Pharmaceutical companies have strong incentives to make R&D more effective and efficient

857 million research $ are used for the Clinical trial phase per new chemical or biological entity.

A typical clinical trial take approx. 5 years. What if we can shorten this period by providing more complete and better quality clinical data?

With access to data from EHRs, researchers can bring medicines to the market quicker.

Pharmaceutical companies have strong incentives to make R&D more effective and efficient

11

Interoperability Data security,

privacy & ethics Scalability and

sustainability

To address key challenges to enable the re-use of EHR for clinical research

Confidence

in data

InterSystems HealthShare®

• The “gold standard” healthcare technology platform

• Access, aggregate, and normalize data from disparate sources

• InterSystems iKnow™ technology to render unstructured data meaningful and useful

• Embedded analytics capabilities

• High performance – works with transactional data

• Massively scalable – from one hospital to nationwide systems

Ideal for:

• Feasibility of clinical trials

• Patient selection for clinical trials

InterSystems is a data specialist

Existing Initiatives

The era of “networked” clinical trials is upon us

• Life sciences needs the data you already have in your EHR

• They are willing to pay for it

• Are you ready to provide it?

The Innovative Medicines Initiative (IMI) is Europe's largest public-private initiative aiming to speed up the development of better and safer medicines for patients.

IMI supports collaborative research projects and builds networks of industrial and academic experts in order to boost pharmaceutical innovation in Europe.

IMI is a joint undertaking between the European Union and the pharmaceutical industry association EFPIA.

A unique initiative = a real project EHR4CR

• Mandated by IMI

• One of the largest European public/private partnership projects in this area

• 4-year project (2011-2015)

• Extended through 2016

• Budget of € >16m

For further information see

www.ehr4cr.eu or contact

Geert Thienpont (EuroRec)

geert.thienpoint@ramit.be

Electronic Health Records Systems for Clinical Research

Summary

Current medical needs, the growth of targeted therapies and personalized

medicines and escalating R&D costs result in formidable cost pressures on

healthcare systems and the pharmaceutical industry. Clinical research is

also growing in complexity, labour intensity and cost. There is a growing

realization that the development and integration of Electronic

Health Record systems (EHRs) for medical research can:

•Enable substantial efficiency gains

•Make Europe more attractive for R&D investment

•Provide patients better access to innovative medicines and improved

health outcomes.

Universities, research organisations, public bodies & non-profit

eClinical Forum Association, France

European Association of Health Law, University of Edinburgh, UK

European Institute for Health Records, France

European Molecular Biology Laboratory, Germany

European Platform for Patients‘ Oganisations, Science and Industry, Belgium

Friedrich-Alexander University, Erlangen-Nürnberg, Germany

Heinrich-Heine University, Düsseldorf (representing ECRIN), Germany

King‘s College London, UK

Medical University of Warsaw, Poland

National and Kapodistrian University of Athens, Greece

National Institute for Health & Medical Research (INSERM), France

Public Service – Hospitals of Paris, France

Telematics Platform Medical Research Networks, Germany

University College London, UK

University Hospital of Geneva, Switzerland

University of Dundee, UK

University of Edinburgh, UK

University of Glasgow, UK

University of Manchester, UK

University of Rennes 1, France

Westfälische Wilhelms University, Münster, Germany

EFPIA

Amgen NV, Belgium

AstraZeneca AB, Sweden

Bayer Schering Pharma AG, Germany

Eli Lilly, UK

F. Hoffmann-La Roche Ltd, Switzerland

GlaxoSmithKline Research & Development, UK

Janssen Pharmaceutica NV, Belgium

Merck KGaA, Germany

Novartis Pharma AG, Switzerland

Sanofi-Aventis Research and Development, France

Participants

Prof. Dr. Georges de Moor

The EuroRec Institute, Belgium

The EHR4CR platform selection

InterSystems HealthShare enables participation in networked clinical trials

• Integrates data from multiple sources (EHRs, local applications, etc.)

• InterSystems iKnow technologyenables analysis and inclusion ofinformation buried in unstructureddata fields

• Delivers data (in a variety of formats) to a trusted third party

A 2ND unique initiative = a second real project EMIF

• Mandated by IMI

• One of the largest European public/private partnership projects in this area

• 4-year project (2013-2015)

• Extended through 2016

• Budget of € >16m

• Difference with EHR4CR= data

not coming only from EHR’sFor further information see

www.emif.eu or contact

Bart VanNieuwenhuysse

(Janssen Pharma)

Better quality EHR data

Improved monitoring, performance benchmarking, reporting and

management (e.g. reimbursement coding)

Drives optimization of patient care and improved efficiencies

Better patient care

Improved clinical

research

Income stream

Enhanced reputation

Initiatives like EHR4CR and EMIF create value for hospitals...

10

01

011

01

01

Improved access to health record data will speed up

• protocol design

• patient recruitment

• data capture

• safety reporting

… and pharmaceutical companies

A win for all stakeholders is critical

Pharma,

academia,

CROs

Hospitals

Health

authoritie

s

Health

communit

y/

governme

nts

and EU

Patients

Some use cases

InterSystems iKnow Technology

• Unique technology for text exploration and analysis

• “Bottom-up” approach eliminates the need for pre-defined libraries

• Fully integrated with InterSystems DeepSee™

embedded analytics technology

• Connects to third-party tools or applications via an API or standard SQL

27

Examples of the iKnow Text Analytics Breakthroughs in Action

Intelligent EHR

Navigation

PopulationScreening

PredictingPatientsat Risk

PatientCohort Identification

and Selection

28

Intelligent EHR Navigation

No time to read through all clinical notes.

Risk of missing the important needle in the haystack.

29

Intelligent EHR

Navigation

30

Intelligent EHR

Navigation

31

Intelligent EHR

Navigation

Patient Cohort Identification and Selection

Need access to real-world data

Structured data alone not rich enough

Selection criteria should not be based on guesswork

33

Acta Oncol. 2012 Sep 5.

Metformin use and improved response to therapy in esophageal adenocarcinoma.

Skinner HD, McCurdy MR, Echeverria AE, Lin SH,

Welsh JW, O'Reilly MS, Hofstetter WL, Ajani JA, Komaki R,

Cox JD, Sandulache VC, Myers JN, Guerrero TM

Department of Radiation Oncology, The University of Texas

MD Anderson Cancer Center, Houston, Texas, USA

33

Identify Patients with a Certain Condition

PatientCohort Identification

and Selection

34

Head & Neck CancerMetformin Diabetic

34

PatientCohort Identification

and Selection

35

0 in metadata Forms in notes

Partially in metadataForms in notes

All in metadata

35

Head & Neck CancerMetformin Diabetic

PatientCohort Identification

and Selection

36

Identify Patients with a Certain Condition

36

PatientCohort Identification

and Selection

37

Identify Patients with a Certain ConditionPatient

Cohort Identificationand Selection

Predicting Patients at Risk

Shift from reactive to pro-active medicine.

Need predictive models based on all the data.

39

Driving Actions with Real World Predictive Models

Early Detection of

Hepatitis C

Isolation

Sepsis

Deleria

Readmission in

psychiatric care

PredictingPatientsat Risk

40

Early Detection of IsolationPredictingPatientsat Risk

41

1. Crisis center

2. IBS

3. Consultation

4. Medication

5. Examination

6. Kcap

7. Suicide Risk

Early Detection to Prevent Isolation

8. Assessment

9. Bad

10. Not possible

11. Voluntary admission

12. Drugs

13. appointments

PredictingPatientsat Risk

• Injecting Drug User (IDU)

• HIV

• Country of origin: HCV prevalence > 2%

• High ethnic mix area

• LFT: ALT more the

• Transfusion before 1992

• Piercing

• Acupuncture

• Tattoo

• Men having sex with men (MSM)

• Household & sex partners of Hep carriers

• Prison stay

Identifying Hepatitis C “At Risk” Patients

HCV Risk Group Drivers

• Alert and outcome “score”

• Clinical support

– Guidance on additional questions

– Testing recommendation

• Links to knowledge base

Positive Risk Alert

Algorithm CriteriaPatient Database Risk Indicator Flag Hep C Test

42

PredictingPatientsat Risk

43

Healthcare Journey

Prevention of

Hepatitis C

Isolation

Sepsis

Delerium

Personalized Medicine

Cancer therapy

Reactive Proactive

PredictingPatientsat Risk

Population Screening

Too many records to sort through manually

Gaps in structured data

Risk of missing an at-risk patient

45

iknow at Cancer RegistriesPopulationScreening

46

Faster time-to-market

Accurate test patients

Less manual work

And more

Conclusion:The Value of iKnow for Clinical Practice and Medical Research

Conclusions

• All care providers have a very important asset: clinical data

• All pharmaceutical companies need this clinical data to do their research work.

• We offer rapid & simple integration, normalization, aggregation, and analysis of structured & unstructured data. Data becomes high quality information.

• Better clinical data will have a direct impact on the outcome of clinical trials

• Better outcome of the patient selection phase will have a direct impact on the duration

of the clinical trial.

• Better outcome of clinical trials and shorter clinical trials will have a direct impact on

the cost of research...

• and even more importantly, on the time-to-market of the medicine, thus providing a

competitive advantage.

Herman Roelandts

Country Sales Manager Benelux

Herman.roelandts@intersystems.com

+32 478 20 60 61