Biological Models to Better Understanding of Diseases

31
ICT for a global infrastructure for health research Dr Octavian Purcarea Global Industry Manager

description

Biological Models to Better Understanding of Diseases. Purcarea O, Frangi A, Hernandez V. eHealth week 2010 (Barcelona: CCIB Convention Centre; 2010)

Transcript of Biological Models to Better Understanding of Diseases

Page 1: Biological Models to Better Understanding of Diseases

ICT for a global

infrastructure for health

research

Dr Octavian Purcarea

Global Industry Manager

Page 2: Biological Models to Better Understanding of Diseases

Challenges for eHealth implementation

• Usability

• Trust

• Sustainability (economic model)

• Implication of different actors (empowerment)

• Bringing closer the clinical practice and clinical research

Page 3: Biological Models to Better Understanding of Diseases

Challenges for clinical research

• Only 7% of eligible patients enrol in a clinical trial.

• Only 3% of eligible cancer patients enrol.

• 86% of all trials fail to enrol on time.

• 85%-95% study days beyond original study timetable

are due to not recruiting subjects on time.

• Women, minorities, children and special populations are

underrepresented.

• Only 3% board-certified physicians participate in clinical

trials.

• The number of clinical investigators dropped 11%

between 2001 and 2003.

Michael G. Kahn MD, PhD University of Colorado The Children’s Hospital, Denver

Page 4: Biological Models to Better Understanding of Diseases

USE OF DATA FROM THE PRIMARY CARE EPR - RESISTANCES AND SOLUTIONS Prof Dr Marc VANMEERBEEK DUMG 2004

Analysis of the database records of the EPR in 8 Medical Homes, 3 years, 133.0000 contacts

Belgian Study

EPR usability

EPR Usability in the daily practice of the GPs

« 6, 7% of the contacts were recorded in the database »

« exasperation of the user »

« It seems illusory to continue an IT program

without a rapid response to the numerous improvement demands »

Page 5: Biological Models to Better Understanding of Diseases

QUALITY IMPROVEMENT IN THE PRIMARY CARE BASED ON DATA COLLECTION OF DIABETES AND HYPERTENSION RELATED CONSULTATIONS Vandenberghe H., Bastiaens H., Jonckheer P., Orban T., Declercq E.,Lafontaine M.-F.,Van Casteren V.Service d’Epidémiologie Institut Scientifique de la Santé Publique, 2003, Bruxelles

Exploration of the feasibility of data collection for quality improvement interventions .Two groups: paper based data collection and EPR based data collection

Conclusion

“40% of the physicians from the EPR based group finally didn’t send the data”

« The quality indicators are strongly divergent for the 2 methods”

EPR Usability in public health and quality management

Belgian Study

EPR usability

Page 6: Biological Models to Better Understanding of Diseases

Conclusions

- only 20% of care networks have electronically data exchange

- only 9% have enough structured data

- only 3% can document the care processes electronically

German Study

PRAXISNETZ STUDIE 2006 MANAGEMENT -PROZESSE –INFORMATIONSTECHNOLOGIEGünter Schicker und Oliver Kohlbauer , Wirtschaftsinformatik II Universität Erlangen-Nürnberg

Analysis of the practice mangement and IT situation of GP Associations in Germany and Switzerland ; ( 72 deutsche Praxisnetze und 18 Schweizer)

EPR Usability for GPs

EPR usability

Page 7: Biological Models to Better Understanding of Diseases

Clinical Software for USABILITY

1. Software behavior should reflect the work process of the user (workflow )

2. Software objects should reflect the mental model (concepts) of the user (terminology )

Usability threshold

Terminology+ ---------------------------------------------------->

Clinical Process Models

Page 8: Biological Models to Better Understanding of Diseases

Trends : the Expansion of Networks:

Numbers of Connected Devices

• ‘60s

• ‘70s

• ‘80s

• ‘90s

• ‘00s

• ‘10s

• ‘20s

10s

100s

1,000s

1,000,000s

1,000,000,000s

1,000,000,000,000s

1,000,000,000,000,000s

Page 9: Biological Models to Better Understanding of Diseases

Personal

Cloud

Platforms, not technologies,

Create Economic Value

• Consistent APIs

• Standards for

interoperability

• Available at scale

• Compelling business

model LAN

Web

Page 10: Biological Models to Better Understanding of Diseases

Why Cloud changes the rules

• Instant global scale service creation: Creates

major opportunity for startups

• Adds value to all existing platforms: Software +

Services

• Interoperability based on open standards:

Broadest device, client and data accessibility

Page 11: Biological Models to Better Understanding of Diseases

Single Touch

EnhancedGUI

Handwriting

Voice

NUI

Page 12: Biological Models to Better Understanding of Diseases

Data Input

Page 13: Biological Models to Better Understanding of Diseases

Innovative interfaces

Page 14: Biological Models to Better Understanding of Diseases

10 Year View:

An Algorithmic* Transformation

• Automation of the routine

• Network Embedding of specialized knowledge and processes

• Massive expansion of networkedservice value chains

• Value creation moves from specialized to generalized skills

Moore’sLaw

Cloud

NUI

UbiquitousNetworking

+

+

+

*Prof. John Zysman, BRIE – UC. Berkeley

Page 15: Biological Models to Better Understanding of Diseases

Implications:

Healthcare Providers

• Will need to add semantic interoperability to

automated processes and knowledge networks

• The role of the GP will change dramatically as

patients become increasingly educated, networked

• Real-time monitoring and sensor based

diagnostics will transform working practices

• Massively increased competition in health services

provision

Page 16: Biological Models to Better Understanding of Diseases

Implications:

Patients

• Move towards ‘end to end’ health and wellness

management strategies

• Increased choice as providers compete with

monitoring and diagnostic services

• Much higher expectations from service providers

• Increased concern about privacy as health

services and data go online

Page 17: Biological Models to Better Understanding of Diseases

Implications:

Research

Integrating Electronic Health Records (EHR) with

Electronic Data Capture (EDC) systems used in

clinical trials:

• avoid duplicated data entry

• assist in automatic identification of patients for

clinical trials

• enable early detection of potential patient safety

issues.

• Take into account multiple parameters

(environmental, physical, genetical)

Page 18: Biological Models to Better Understanding of Diseases

A Fundamental Change is Underway

- World Health

Organization

Page 19: Biological Models to Better Understanding of Diseases

HealthVault = Health Application

Platform

Page 20: Biological Models to Better Understanding of Diseases

Physicians

Laboratories

Hospitals

Pharmacies& PBMs

Application Providers

Health & Fitness Device

Manufacturers

Health Plans

Employers

Schools

Healthcare Associations

Patients can:

•store health information

from many sources

•access a range of health

and fitness apps

•upload data from health

and fitness devices

•share health information

with those they trust.

Personal Health & Wellness

Page 21: Biological Models to Better Understanding of Diseases

Environmental

Data

Phenomic data

Integrated Health Records

Biosensors

Genomic data

Biochips

Future plansTowards full picture of individual’s health status

Page 22: Biological Models to Better Understanding of Diseases

Infr

astr

uctu

re &

Pla

tform

Offerings

Connected Health Platform

Connected Health Platform

Application Platform for Health

Business Productivity Infrastructure for Health

Core Infrastructure for Health

Connected Health Framework – Architecture and Design Blueprint

www.microsoft.com/healthICTResources available at:

Page 23: Biological Models to Better Understanding of Diseases

Microsoft Connected Health Framework

Knowledge Driven Health Create a Technology

Foundation

Page 24: Biological Models to Better Understanding of Diseases

Seamless Integration of External

Services: EPR side

Exchange of key patient

data

Seamless integration at

user interface

Page 25: Biological Models to Better Understanding of Diseases
Page 26: Biological Models to Better Understanding of Diseases

Integration of the HIS side: Microsoft Amalga Unified

Intelligence System

Page 27: Biological Models to Better Understanding of Diseases

Specialty Care Case Manager

Care Manager

Social WorkerPrimary Care Provider

ED Physician

Healthcare Providers

Inte

gra

tion

Sys

tem

Data

Contributors

PH

R A

pp

lica

tion

s

Citizens

Personal Health

Record System

Interoperability Tools

Aggregation &

Insight System

Health Domain

Page 28: Biological Models to Better Understanding of Diseases

Specialty Care Case Manager

Care Manager

Social WorkerPrimary Care Provider

ED Physician

Healthcare Providers

Connected Health Platform &

Partner Interoperability Tools

Hea

lthV

au

ltA

pp

lica

tion

s -

Pa

rtne

rs

Citizens

Connected Health

Biz

Ta

lk S

erv

er

Data

Contributors

Page 29: Biological Models to Better Understanding of Diseases

What We Need to Make It Happen?

• Support (fund) semantic interoperability including human resources.

• Involve, empower the individuals in management of their own Health,

involve from the beginning in your projects the Health Professionals;

• designing an organisational architecture that bolsters the interest of

health professional, promoting the early assessment of new

therapies for their inclusion among the reimbursable treatments,

fostering the validation of clinical trials protocols based on Evidence

Based Medicine and additionally, on Evidence Based Management.

• validating new reimbursement schemas, assessing the need for

incentives for health professionals and patients involved in clinical

trials, and devising new adherence strategies with patients and

health professionals.

• Think in terms of pay per performance, quality related indicators,

incentives, trust and usability.

Page 30: Biological Models to Better Understanding of Diseases

For More Information about Microsoft Health

• Health Web site: www.microsoft.com/healthcare

• Health Blog: www.blogs/msdn.com/healthblog

• EMEA Health Blog: http://blogs.msdn.com/ms_emea_health_blog/default.aspx

• Information on Amalga and Health Vault can be found at: http://www.microsoft.com/hsg/

• You can find information on the Common User Interface and the design guides at: www.mscui.com

• Here is the link to the CHF (Connected Health Framework) material: http://msdn2.microsoft.com/en-us/architecture/bb525069.aspx

• For MedStory (now called Live Search – Health) go to https://ssl.search.live.com/health/default.aspx or www.medstory.com.

E-mail: [email protected]

Page 31: Biological Models to Better Understanding of Diseases

© 2010 Microsoft Corporation. All rights reserved. Microsoft, Windows, Windows Vista and other product names are or may be registered trademarks and/or

trademarks in the U.S. and/or other countries.The information herein is for informational purposes only and represents the current view of Microsoft Corporation as

of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of

Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation.

MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.