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Trends in Chronic Care (R)Evolution

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Levay Akos

on 6 June 2010

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Transcript of Trends in Chronic Care (R)Evolution

Systems biomedicine Personalization Patient in the focus Care space evolution Biological individualization Holistic personalization Monitoring
Physiological state determination
Physiological modelling Health culture development Personal expectations to be taken into account

Personality development depending on the personal psychological, mental and socio-economic stratus

Personalized communication Information supply Shared decision making Concordance Biomedical
scientific results Reactive care Proactive care Individualized patient models Risk modelling Patient Medical team 90 - 95 % Information space Activity space Technological innovations Guidelines, cases, EPR ICT Innovations Information sharing
distributed systems Clinical practice results


Evidence based guidelines Systems biomedicine Agilely organized on demand Highly specialized members Intelligent agents Physicians and non-physicians New types of organization

Reshaped roles Self management:
(in outpatient care) Multimodel userinterfaces New care models Personalized support Intelligent support for problem solving and decision making

A care model defines the main participants and their relationships in a structured framework Requirements Outpatient care Inpatient care Individualised state determination

State monitoring

Individiualised state management

Risk management

Personalised information

Outpatient care model REACTION Scenarios

Use cases
Inpatient care model Complex physiological model


Complex Physiological state parameter management (e.g. glucose managemenet)

Therapy risk assessment
(short term)

Information concerning the actual acute status and suggested treatments

Psychophysiological model

Telemonitoring sensors

State parameter management (e.g. glucose management)

Personalised care plan
(long term)

patient education, personal health culture development

Characteristics ICT E-Health Telemedicine
Telecare Intelligent systems Decision support systems
Knowledge management systems
Partner systems Networked systems Distributed systems
Service oriented architectures
EPR, EHR connectivity, standards Trends in Chronic Care (R)Evolution Care at the Crossroads Exploring Solutions for Chronic Care Management, Intel Corporation, 2007

Diagnostics 2009: Moving towards personalized medicine, What will you do? PricewaterhouseCoopers 2009, Available at www.pwc.com/healthcare

Georgeff, M. E-Health and the Transformation of Healthcare, Australian Centre For Health Research Limited, 2007

Healthcare 2015: Win-win or lose-lose? IBM Global Business Services, 2006

Healthcare 2015 and care delivery, IBM Global Business Services, 2008

HealthCast: The customization of diagnosis, care and cure, PricewaterhouseCoopers 2010, Available at www.pwc.com/healthcare

HealthCast 2020: Creating a Sustainable Future, PricewaterhouseCoopers 2010, Available at www.pwc.com/healthcare

Thomas H. Lee, M.D. James J. Mongan, M.D., Chaos and Organization in Health Care, The MIT Press, 2009, Cambridge, Massachusetts, London, England

Matthew A. Hein,Telemedicine: An Important Force in the Transformation of Healthcare, U.S. Department of Commerce, 2009

The new science of personalized medicine, PricewaterhouseCoopers 2009 Available at www.pwc.com

High Quality Care For All, NHS Next Stage Review Final Report, 2008
New monitoring and testing solutions (e.g. POCT) Shared decision making
concordance Applied Logic Laboratory
Tamas Gergely Biomed R&D Clinical R&D Socio-ecnomic environment Financial incentives Attitude Organization Technology Developments Personalized Medicine - personalisation of the care and its person centric realisation

Patients’ participation and empowerment in self-care

Coordinated, integrated and proactive care in a networked model, where each participant is supported
Outpatient workflows

Inpatient workflows
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