ibm involvement in adoption of ehr, health data standards and epsos - matej adam

© 2012 IBM Corporation

IBM involvement in adoption of EHR, health data standards and epSOS

Matej Adam

Healthcare Leader EMEA

[email protected]

mailto:[email protected]

mailto:[email protected]


Let’s build a smarter planet: Healthcare

1

Agenda

1.IBM in healthcare

2.Health data standards

3.epSOS

4.EHR adoption and value creation



2

IBM Healthcare & Life Sciences Team

4,000+ employees worldwide

– Services, Systems, Software,

Research, & Financing, Sales

– Large Clinical Consulting Staff

Clients include:

– Hospitals: 14 of the top 14 hospitals

– Healthcare Insurance: 12 of top 13

companies

– Government: significant projects in

Canada, Singapore, Denmark,

Germany, Ireland, Spain, Italy, China,

India and US

– Pharmaceutical: 30 of the top 30

companies

– Biotech: 18 of top 20 companies

– Also, medical research in

Almaden/Watson, Haifa, Zurich, Japan



3

IBM Involvement in European eHealth

Large Scale EU Projects

– epSOS – engaged in 3 working groups

– Renewing Health – Supporting Smart Personal Health action (via Continua)

European Trade Associations

– COCIR – 3 resources on HIT and Telemedicine Focus Groups

– Continua Health Alliance – 1 resource on Policy/Strategy Work Group

– EHTEL- ETSI- CEN/CENELEC- EuroRec

Other European ‘Centres of Excellence’

– Norway – Tromso Telemedicine Centre

– N Ireland – European Centre for Connected Health

Major European Conferences and Exhibitions

– eHealth Week - World of Health IT (7-9 May 2012, Copenhagen)

– HIMSS CIO Summit (18-20 November 2012, Mallorca)

– eHealth Week - World of Health IT (13-15 May 2013, Dublin)



4

Semantic interoperability

Functional interoperability

e.g., HL7 mission: “To provide standards for the exchange,

management and integration of data that supports clinical

patient care and the management, delivery and evaluation

of healthcare services.”

interoperability

: ability of two or more systems or components to

exchange information and to use the information that has

been exchanged.

Source: IEEE Standard Computer Dictionary: A Compilation of

IEEE Standard Computer Glossaries, IEEE, 1990]

New Generation of Standards aim at ‘True’ Interoperability



5

Interface

Engine

Reference

Database

Enabling interoperability: Metadata, Ontologies, Standards… ?

Enterprise

Data

Metadata

Enterprise

Data

Metadata

Enterprise

Data

Metadata

Enterprise

Data

Metadata

Public

Ontology

(Inter) nationally

Accredited

Standards

Inter-

operability? Metadata

Registry



6

IBM HCLS Standards Program

An IBM “Standards Team” with experts on each key* SDO**

Develop innovative standards

Promote adoption of standards within IBM and outside

Implement HCLS standards over open technology standards

Foster a continuum/convergence of healthcare and life sciences standards

Use model-driven approach, enabling customization through constraining

Push industry to reduce overlaps where possible

Show how standards fit together and support interoperable EHR

Examples of innovative standards development led by or with IBM:

• HL7 Clinical Genomics & Family History : lead

• HL7 Clinical Document Architecture (CDA): co-editor

• HL7 Continuity of Care Document (CCD): co-editor

• IHE XCA, XCPD, XDS-SD, XD-Lab: lead

* key = accredited, appointed, dominant or emerging SDOs

** SDOs = Standard Developing/Profiling Organizations



7

Medical Imaging Management

CMO, VNA Cross-facility intelligent archive

Clinical Genomics

CG / BII / BioMIMS / Cli-G

Interoperability and PHREHR

HIE&Initiate / MECIDS / uHealth

Health Standards Practice

HL7 / IHE / CEN / DICOM / HIPAA

Admin

Server

SME

TSM

ManagementConsol

RMI/IIOP

DICOMInterface

Agent

Raid Drive (local cache)

CM API

Tape Tape Tape

HL7Interface

Agent

CM API

CM

CM API

User specificInterfaceAgent

CM API

Offering Education & Services

HL7 involvement:

• Co-chair and facilitator of

Clinical Genomics Group

• Co-editor of the Pedigree spec

• Co-editor of CDA Release Two

(clinical document) & CCD IG

• Co-chair of RIMBAA (RIM-based

Application Architecture)

• Regional and national

EHR initiatives

• Public health

information exchange

• Patient Empowerment

through connecting EHR

and PHR systems

Data mining analysis

of massive amount of

operational clinical-

genomic data yielding

decision support

components

• Medical home and

collaborative care

CMO = Content management Offering

BioMIMS = Biomedical Imaging Management

BII = Biomedical Information Infrastructure

HIE = Health Information Exchange

MECIDS = Middle East Consortium on Infectious Disease Surveillance

uHealth = Smart PHR and social-medical networks for the patient

Hypergenes – exploring

the genetic background

of hypertension

EuResist – fine-tuning

the AIDS drug cocktail by

the viral genome

IBM Research Lab in Haifa - Activities with Standards Implementations

http://srv-rimon.haifa.il.ibm.com:8080/rimon_web/



8

epSOS - Goals & Challenges

Goal for the epSOS eHealth Project:

–“to develop a practical eHealth framework and ICT infrastructure [based on existing national infrastructures] that will enable secure access to patient health information, particularly with respect to a basic patient summary and ePrescription, between European health care systems”

Challenges to get there (based on the EIF (European Interoperability Framework)):

–Legal Interoperability

–Organisational Interoperability

–Semantic Interoperability

–Technical Interoperability



9

Why is epSOS important?

eHealth Governance Initiative and the adoption of the Directive 2011/24/EU on the application of patient's rights in cross-border healthcare

Deploy Telemedicine solutions for Chronic Disease Management

Identifies 5 political goals for this digital agenda: –Patient Safety (evidence based healthcare, reduced risk of patient

harm)

–Quality of Care (patient satisfaction, effectiveness of care service provision)

–Availability (equal access, reduced waiting times and better utilisation of resources)

–Empowerment (patient-centricity and direct involvement in the patient’s own care)

–Continuity of Care (coordination of activities & information sharing w/ caregivers)



10

From Strategies to Services

Provide concrete cross border services that ensure safe, secure and efficient medical treatment for citizens when travelling across Europe

Focus on services close to the patient:

–Patient Summary for EU Citizens

Occasional Visit

Regular Visit –ePrescribing for EU Citizens

Medication ePrescription

Medication eDispensation

Build on existing National eHealth Projects and use experiences and

knowledge from all Member States



11

epSOS – European Patients Smart Open Services

Country ACountry B

POC

(Hospital)

POC

(General Practioner)

NCP B

POC

(Pharmacy)

POC

(Hospital)

POC

(General Practioner)

POC

(Pharmacy)

NCP A

epSOS

Circle of Trust

National Circle of Trust National Circle of Trust

Source: epSOS project documentation

IHE & CDA are

key standards!



12

The epSOS participating nations 20 EU Member States

3 Non EU Member States



13

The epSOS Industry Team

3M Agfa HealthCare Alert Life Sciences

Computing

Apollo Information

Technologies

Boston Life Labs CareCom Cisco

Conet AG

dbMotion

Dedalus Healthcare

Systems Group

Engineering S.p.A

GE Healthcare

Gnomon Informatics IBM IHE Europe* Indra

Insiel S.p.A. Intel Corporation Mawell MediCognos

Microsoft

Netsmart Oracle Posam

RISE

Steria Tiani-Spirit TrebleM

T-Systems

UBM Medica

X-tention

Industry Team Steering Group members are underlined

as per 15.05.2013

*Industry Team Coordinator,

no member of Industry Team



14

IBM involvement in epSOS project

IBM joined the project in January 2010

We have one representative in the Steering Group of the Industry Vendor team

We've been active in a number of Work Packages during the Analysis & Technical Specification phases, sharing our experience and promoting eHealth standards that have proven their value in some of IBM projects.

We're in contact with several Member States to help them build and run their epSOS pilot

We're in contact with epSOS to provide additional security/privacy services


EHR Adoption – Risks and Opportunities



16

EHR adoption improvements – why it is important



17

It is NOT about Information Technology!



18

Project Risks in Healthcare IT

20% 80%



19

Change Management is key driver of Successful Healthcare implementations

The key success factors for transformation are

organizational rather than technical

Sponsoring of senior management 82%

Fairness with staff 82%

Involvement of staff in change programs 75%

Honest communications 70%

Good training programs 68%

Usage of performance management 65%

Usage of super users 60%

Availability of resources for program 48%

Sponsoring of senior management 82%

Fairness with staff 82%

Involvement of staff in change programs 75%

Honest communications 70%

Good training programs 68%

Usage of performance management 65%

Usage of super users 60%

Availability of resources for program 48%

Software functionality 44%

System performance 35%

Realistic program planning 31%

Source: IBM Institute for Business Value

Software functionality 44%

System performance 35%

Realistic program planning 31%

Source: IBM Institute for Business Value

Change Management is a key driver of success



20

Need Help? Being a Physician is Only Getting More Difficult. No

One Individual Can Do Everything that’s Needed or Expected.



21

On the way for clinical value and meaningfulness

Importance of defining the Clinical Value of the EHR around:

Improving Quality of Care

Increasing Access to Services

Increasing Patient Safety

Managing Costs

Providing Proactive rather than Reactive Health Care

Chronic Disease Prevention Management

Patient Self Management



22

Functionality

Generation 4 The Colleague

Generation 2 The Documentor

Generation 3 The Helper

Generation 5 The Mentor

Time

Generation 1 The Collector

Predictive / Watson

DiaLog Shared Care

(Denmark)

Health Portal Basic

Shared

Repository

22

Generations of EHR capabilities



23

HIMSS Europe adoption model



24

HIMSS adoption 2012 status - Poland

Source: HIMSS Analytics Europe 2012



25 25

Focus on a how to leverage datacollection base for more value add

clinical and operational functions on the way to patient centric

Deliver collaborative care

for prevention and wellness

Achieve better quality and

outcomes

Improve operational

effectiveness EMRs, Images, Records, Forms

Lifecycle Management, Clinical Trials, Safety

Information compliance,

availability and security

Retrospective to Prospective to

Predictive Care Management

Personalized

Healthcare Value

Integration /

Interoperability

Collaboration and Automation

IBM Health Integration Framework



26

Patient Age: 65

Gender: Male

Race: White

Diagnosi

s

Melanoma

Stage: 2

Social Marital status: single

Labs AJCC: T2

Risk of

metastasi

s

47%

IBM Content Analytics IBM Content and Predictive Analytics

Recommended

Add’l

Treatment

DTIC

IBM Similarity Analytics

IBM Care Manager

100’s or 1000’s of patients

100’s or 1000’s of patients

One Patient

Goals Avoid remission

Activities Avoid UV radiation

Regular screening

Transportation

assistance

A 65-year old white male has been diagnosed with stage 2 melanoma. He is widowed and lives alone.

AJCC: T2

Raw Information (e.g. EMR and Claims)

10’s of thousands of patients

26

IBM Patient Care and Insights Capture, Analyze, Activate



27

The Data We Thought Would Be Useful … Wasn’t

• 113 candidate predictors from structured and unstructured data sources

• Structured data was less reliable then unstructured data – increased the reliance on unstructured data

New Insights Uncovered by Combining Content and Predictive Analytics

• LVEF and Smoking are significant indicators of CHF but not readmissions

• Assisted Living and Drug and Alcohol Abuse emerged as key predictors (only found in unstructured data)

• Many predictors are found in “History” notations and observations

Predictor Analysis % Encounters Structured Data

% Encounters Unstructured

Data

Ejection Fraction (LVEF) 2% 74%

Smoking Indicator 35% (65% Accurate)

81% (95% Accurate)

Living Arrangements <1% 73% (100% Accurate)

Drug and Alcohol Abuse

16% 81%

Assisted Living 0% 13%

27

Case Study: What Really Caused Readmissions at Seton

18. Jugular Venous Distention Indicator

17. Paid by Medicaid Indicator

16. Immunity Disorder Disease Indicator

15. Cardiac Rehab Admit Diagnosis with CHF Indicator

14. Lack of Emotion Support Indicator

13. Self COPD Moderate Limit Health History Indicator

12. With Genitourinary System and Endocrine Disorders

11. Heart Failure History

10. High BNP Indicator

9. Low Hemoglobin Indicator

8. Low Sodium Level Indicator

7. Assisted Living (from ICA Extract)

6. High Cholesterol History

5. Presence of Blood Diseases in Diagnosis History

4. High Blood Pressure Health History

3. Self Alcohol / Drug Use Indicator (Cerner + ICA)

2. Heart Attack History

1. Heart Disease History

Top 18 Indicators



28

Create personalised profile based on longitudinal data, determine risk factors

Find the most similar patients (or dynamic cohort) from entire population

Analyze the attributes and outcomes for this cohort (across 30,000+ dimensions)

Predict the probability of the desired outcome for patient in question

Suggest a personalized care plan based on the unique needs of this patient

Desired Outcomes

Historical Observation Window Prediction Window

This Patient’s Longitudinal Data Predicted Outcome For This Patient

Dynamic Cohort Longitudinal Data with Outcomes

How Similarity Analytics Work



32

IBM Competency in Health IT

IBM delivers e-health

in Denmark for 15 years

IBM delivers e-health

in Canada for 10 years

IBM building Smart Healthcare

in US, UK, Spain, Germany,

Norway, Sweden, Ireland, Italy,

CEE, Middle East, SA, Asia ...

IBM Institue for Business Value

Healthcare Industry Practice

IBM Center for Applied Insights

ROI for Healthcare

Many years of experience Structured and formalised method

for benefits of our clients

ROI driven healthcare program

management

Health Integration Framework

and Smarter Health solutions

ROI data from IBM own

projects and combined

industry expertise

E-health adoption framework

IBM expert team helping

clients to define national and

regional e-health strategies

based on ROI



33 10 January 2013

Econometric Model

• Analyze business model, sources of value, economic impact, competitive alternatives

• Identify value and ROI delivered to Healthcare Providers

IBM Center of Applied Insights Healthcare ROI Econometric Model

Value of the

Collaborative Care Econometric Model

Holistic: Takes a holistic perspective

unlike other studies

Financial impacts: Quantifies clinical

and business impacts as costs or

revenues

Research: Leverages academic and

industry research and results of

interviews with healthcare leaders

Outlook: Accounts for transition path

and steady state benefits

Flexible: Can accommodate alternative

technology functionalities and

implementation scenarios

Vendor neutral: Takes a functional,

rather than vendor-driven approach

Academic and industry studies meta analysis

• >200 peer-reviewed articles • Journals include New

England Journal of Medicine, Health Affairs, JAMA

Subject matter expert interviews

• 35 healthcare analysts and thought leaders, including notable authors and speakers

Business leader interviews •27 interviews representing:

•Titles: CMIO, CIO •Sizes: range from 60 to 1000 beds

•Locations: 5 countries

Source: IBM Market Insights

Improving patient safety and care quality while improving the bottom line >> Achieving quality, safety, cost, and revenue improvements



37

Summary - Ingredients for success in EHR adoption

Learn from the past and other countries – best practices

Design a rock solid Governance process

– Direction

– Project oversight

– Stakeholder buy-in

– Manage the Change

– Allocate 20 to 25% of project budgets on Change Management

– Build in motivation criteria

Focus on clinical meaningfulness

– Improvements in quality, safety, costs of care

– Decisionmaking support

– Proactive rather than Reactive Health Care

Use Standards and methods across the program

– Project management

– Common project phases & gates

– Alignment with a national E-Health Architecture using a Design Authority

Value Measurement

– Define outcomes

– Establish Benefits Realization mechanism

– KPIs



38

... and please don‘t forget

Technology is just a tool ...

... how much value we

create is up to us all!


Thank you [email protected]

ibm involvement in adoption of ehr, health data standards and epsos - matej adam

Health & Medicine