Modelling and Simulation in Health Technology – from Development via Implementation to Assessment F. Breitenecker, N. Popper, S. Wassertheurer EUROSIM

Modelling and Simulation in Health Technology – from Development via Implementation to Assessment

F. Breitenecker, N. Popper, S. Wassertheurer EUROSIM 2010, Prague

MMS

Modelling and Simulation in Health Technology – from Development via

Implementation to AssessmentF. Breitenecker, Vienna Univ. of Technology

Niki Popper, dwh Simulation Sevices

Siegfried Wassertheurer, Austrian Inst. of Technology



MMS

Modelling and Simulation – M & S

• Modelling and Simulation – Technique since 1970

• 3rd Pillar of Science

Problem Simulation Solution

Abstraktion der

Realität

Theory

Experiment



MMS




• Problem SolutionProblem Simulation Solution

Theory

Experiment



MMS




• Problem Solution

• Aim and Goal ?


Theory

Experiment



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• Aim and Goal ?


Theory

Experiment

Simulation is the process of designing a model of a real system and conducting experiments with this

model for the purpose either of understanding the behavior of the system and its underlying causes or

of evaluating various designs of an artificial system or strategies for the operation of the system.



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• Aim and Goal

• Level of Application / Use


Theory

Experiment



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• Aim and Goal

• Level of Application / Use

DEVELOPMENT - IMPLEMENTATION - DIFFUSION


Theory

Experiment



MMS



of a Product / Technique / Strategy (PTS)

PTS PTS

PTS

PTS

PTS

PTS

PTS

PTS

PTS

PTS

PTS



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PTS PTS

PTS

PTS

PTS

PTS

PTS

PTS

PTS

PTS

PTS

M & S



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PTSPTS

PTS

PTS

PTS

PTS

PTS

PTS

PTS

PTS

PTS

M & S

M & S



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PTSPTS

PTS

PTS

PTS

PTS

PTS

PTS

PTS

PTS

PTS

M & S

M & S

M & S



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M & S M & S



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Mechatronic M&S M & S

Em-bedded

M&S



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Mechatronic M&S M & S ?

Em-bedded

M&S



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DIFFUSION

– Assessment at Free Market

M & S



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DIFFUSION


M & S



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DIFFUSION


M & S



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DIFFUSION




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DIFFUSION

– Assessment at Free Market Market M & S



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DEVELOPMENT - IMPLEMENTATION -


Mechatronic M&S Market M & S

Em-bedded

M&S

MECHATRONICS

ASSESSMENT

DIFFUSION



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Mechatronic M&S Market M & S

Em-bedded

M&S

MECHATRONICS

ASSESSMENT

DIFFUSION



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M&S M & SHEALTH TECHNOLOGY

ASSESSMENT

DIFFUSION

Embedded M&S

Embedded M&S



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M & S

HEALTH TECHNOLOGY

DIFFUSION - ASSESSMENT

Limited Market

Controlled Market (Laws)

Health Care Systems

Use depends on Assessment

ASSESSMENT - > DIFFUSION



MMS



M&S with Markov – ODE – PDE - CA - AB - NN

HEALTH TECHNOLOGY

ASSESSMENT

DIFFUSION

Embedded M&S

Embedded M&S



MMS

Cardiovascular Risk Stratification and Therapy

Optimization in Epidemiology using Simulation




MMS

Arcus Ao.Ao. abdom inalis

A . fem oralis

A . peronaea

The arterial system in (technical) terms

• Single source (heart)• Branched elasitc tubes for

blood transport (arteries)• Various sinks (organs)• Unsteady pressure gradients

drive the system• Arterial pressures

(systolic/diastolic) are actually the most important inidactors in prevention/treatment



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Pathology (Hypertension)

Prevalence of Hypertension over age and sex (USA 1988-94)



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Costs

Source: Austrian Social Insurance (1999-2004)



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Outcome

• Only 10-15 % of treated patients reach their therapy goals within OECD countries! (Source: WHO, AHA)

• Vienna Study– 7100 Probands– 50 % Hypertensives– 1110 in treatment– 185 (16%) well treated!



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1 Paradox – 2 Answers

Only 50 % CHD are related to Hypertension?!



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Circadian Blood Pressure

• 24 h Blood pressure profile

• White coat hypertension

• Masked hypertension

Blood Pressure is time dependent!



MMS



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Explanation

Blood pressure depends on the arterial site!



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How to handle? Dynamics!

Womersley Solution for Navier-Stokes Eq.



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Generalized Transfer Function (GTF)

This approach allows for the first time widespread epidemiological use!



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Ambulatory Pulse Wave Analysis



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Validation



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Example 1: Physiological Case



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Example 2:Non-Dipper



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Example 3:Raiser



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META – LEVEL: „SIMULATION ON THE MARKET“

– Health Technology




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HEALTH TECHNOLOGY ASSESSMENT

– Using Simulation - Competitor

DT MC CA SD DE PM AB DEVsNN



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DIFFERENT (EASIER) APPLICATION



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DEMANDS: EASY TO USE



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Σ



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– Using Simulation - Competitors

DT MC CA SD DE PM AB DEVs NN



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– Using Simulation - Competitors

DT MC CA SD DE PM AB DEVs NN



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Evaluation = Evidence Based Decision Making

For Effective and Efficient Use of Ressources

YES: Do not things without Benefit – “Make it Rational”

NO: Deprive things with Benefit – “Rationalise”



MMS

Dissociation of Prooved Benefit of Costs for Medical Care

Pharmaceutical Application Discovery Costs € (Patient/Year)

Effects (Survival)

Insulin Typ 1 Diabetes 1920 500 Decades

Statins Cardiology 1990 5.000 Years

Monoclonal Antibodies Onkology 2000 50.000 Month/Weeks

Encyme Alternation Metabolism 2010 500.000 ???



MMS


M&S IN HEALTH TECHNOLOGY ASSESSMENT

Problem 1: Goal Function - LYG, QLYG, ...



MMS



Decision

Course of Disease.

Therap. Eff.

Therap. Probl.

Life Expectance

Life Quality

Costs

Problem 2: Data Diversity and Data Quality

„What to Do?“



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Top Down Heterogeneous PopulationM&S IN HEALTH TECHNOLOGY ASSESSMENT


Point of View: Bottom Up



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Population

Top Down Heterogeneous PopulationM&S IN HEALTH TECHNOLOGY ASSESSMENT




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Female Male

Top Down Heterogeneous Population

Top Down: POSSIBLE





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Children (f) Children (m)

Adults (f) Adults (m)

Retired (f) Retired (m)


Top Down: COMPLEX





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female,adult

< PS

female,adult

PS

female, adult

Secondary

female, adult

Master

male, adult

< PS

male, adult

PS

male, adult

Secondary

male, adult

Master

Children

Adults

Retired


Top Down: MORE COMPLEX





MMS

Rich

Poor

Children

Adults

Retired


Top Down: COMPLEX INCOME





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Y N Y N Y N Y N Y N Y N Y N Y N

Rich

Poor

Children

Adults

Retired


Top Down: DISEASE CLUSTERING





MMS



Decision

Course of Disease.

Therap. Eff.

Therap. Probl.

Life Expectance

Life Quality

Costs

Problem 3: „The Point of View“

„What to Do?“

Ethics

Politics

Customer

Dealer



MMS

“The Point of View....”



MMS

Top Down Heterogeneous PopulationModelling and Simulation – M & S

Problem 4: Diversity of Problems




MMS

Decision

Course of Disease

Therap. Eff.

Therap. Probl.

Life Expectance

Life Quality

Costs

„Decisions have to be made….“

„What to Do?“

Ethics

Politics

Customer

Dealer





MMS

Advanced Structure - Vaccination

Markovian Model

- Decision Tree - Statistics

Real System

ODE (Population & Dynamics)

ODE (definite Population)AB (definite Population)

AB (Population & Dynamics)


Solutions – Part 1: Technology



MMS

• Flexible structures for scenarios (Vaccination, Quarantine, etc…)

• Long term population dynamics

• Start-up phase simulation

• Model Generated Herd immunity effects

• White Box Modeling

• Parallelization

• Reusability

Advanced StructureM&S IN HEALTH TECHNOLOGY ASSESSMENT




MMS

Feedback to data structure

internal data

(HVB, clinical

trials, …)

external

data

Pool of

Methods

- AB

- SD, ODEs

- couplings

- …

Hybrid

decom-

position

model

com-

parison

Evaluation

Insigths for data structure

external evaluation

Feedback to model pool

Problem

class

definition

economical

point of view

model

demand

Feedback to data structure

Goal

EV

ALU

AT

ION

OF

DIF

FE

RE

NT

MO

DE

LIN

G

TE

CH

NIQ

UE

S F

OR

SIM

UL

AT

ION

OF

EP

IDE

MIC

S





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Solutions – Part 2: Data

New Possib.

New Solutions

New Problems

New Respons.



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Analysing Individual Patient Careers and Pathways

Analyse Health Care Sector from a Patients Perspective

Show Impact of Policy Changes on Individuals

Increase Transparency of Changes in Individual Behavior

-> Reduced but Sufficient Information

New Data allows…


Solutions – Part 2: Data



MMS

EU Joint Action

(2006-2008/2009+, 2010-2012 www.eunethta.net

35 Organisations

27 European Countries (NICE/ GB, IQWIG/ DE, …)

-> Well defined Rules and Standards for Assessment

SOME DAY INCLUDING M&S

EUnetHTA


Solutions – Part 3: Strategy



MMS

Decision

„Decisions have to be made….“

„What to Do?“

Dealer

HTA-Exp.

Customer

Results


Solutions – Part 4: Organisation

Ethics Politics

Data Statistics M&S

Documents

Modelling and Simulation in Health Technology – from Development via Implementation to Assessment F. Breitenecker, N. Popper, S. Wassertheurer EUROSIM