1. FP7-ICT-2009.5.1 – Support Action
Directions for ICT Research in Disease Prevention
This project is partially funded under the 7th Framework Programme by the European Commission
The Citizen as Co-producer of Health &
Conceptual Framework for Chronic Disease
Management
Niels Boye
University of Aarhus, Denmark
2. www.preve-eu.org
Client Centred Approach
Patient Centred Medicine
Ambient Assisted Living
Health Service Delivery
Maturity of ICT
Citizen as object
User as Operator
Expert Systems
Corporate Centred
User as User
Layman Systems
Individual Centred
Citizen as co-Producer of Health
Contemporary
State of the Art
in ICT and
Empowerment
Model &
Concepts
Citizen as proactive subject
Disease prevention
Disease compensation
(Disease cure)
Assisted living
The Citizen as Co-producer of Health –
enabled by ICT
5. www.preve-eu.org
Personal Guidance Services (PGS)
Conceptual Aims of “the Citizen as
Co-producer of Health Model"
• Information and patients as resources
• Nature, Nurture, and collaboration with institutionalized
health care
• Personalized management of prevention (and care of
chronic diseases) – in a citizen context
• Multilevel ICT-modeling of health and disease
encapsulated in to personal devices –
From: “Background document for the Consultation meeting
on potential European Large scale Action (ELSA) on eHealth”
European Commission “ICT for Health Unit, H1, 28.08.2009
9. www.preve-eu.org
Decision support (information flows)
EHR
Quality
Assurance
HMO/
Region
Clinical
encounter
Healthcare
Co-production
Health-PGS
PHR and
digital avatar
Research Patient-NGO
Research/
Pharmaceutical Co
Hospital
Data- and
Information
flow
10. www.preve-eu.org
Decision Support
Present service model
• Contemporary service model (provider push) of
prevention:
• Non-specific lifestyle modifications
• Primary prevention (e.g. immunisations)
• Secondary prevention – (e.g. screening programs)
• Tertiary prevention of complications to disease
11. www.preve-eu.org
Prevention in the Co-Producer Model
context
• From the citizen and co-production of health point of view
there is no distinction between primary, secondary and
tertiary prevention
• It is behaviour planning and execution on the basis of
personal-context, evidence-, and knowledge-driven ICT-
augmented decisions
12. www.preve-eu.org
Evidence Based Associations between Risk
Factors and Conditions
Type 2-diabetes
Preventable cancer
Cardiovascular disease
Osteoporosis
Musculoskeletal disorders
Hypersensitivity disorders
Mental disorders
Chronic obstructive pulmonary disease
Tobacco smoking
Alcohol consumption
Diet
Physical activity
Obesity
Accidents
Working environment
Environmental factors
Diseases and Disorders Risk Factors
13. www.preve-eu.org
Reduction i CVD
disease risk (%)
(95% CI)
Reference
Wine
(150 ml/day)
32 ( 23-41) Circulation 2002;105:2836-44
Fish
(114 gr 4x/week)
14 (8-19) Am J Cardiol 2004;93:1119-23
Dark chocolate
(100g/day)
21 (14-27) JAMA 2003;290:1029-30
Fruit and vegetables
(400 g/day)
21 (14-27) Lancet 2002;359:1969-74
Garlic
(2.7 g/day)
25 (21-27) Arch Intern Med 2001;161:813-24
Almonds
(68 g/day)
13 (11-14) Circulation 2002;106:1327-32
Am J Clin Nutr 2003;77:1379-84
Combined effect 76 (63-84)
Franco OH et al. BMJ 2004;329:1447-50.
CVD=Cardiovascular Disease,
CI = Confidence interval
A “polymeal” of the above would cost 21.60 Great British Pounds per week (2004)
and give an average increase in life expectancy of 6.6 years for men and 4.8 years for women
And give men 9.0 years more life without heart disease for women (8.1 years).
Decision support – in prevention
Example: Evidence of food having impact in Cardio Vascular Disease
14. www.preve-eu.org
Citizen Modifiable Risk Factors
Co-production of Disease Prevention
Connections between Risk Factors and Conditions
Type 2-diabetes
Preventable cancer
Cardiovascular disease
Osteoporosis
Musculoskeletal disorders
Hypersensitivity disorders
Mental disorders
Chronic obstructive
pulmonary disease
ConditionsTobacco smoking
Alcohol consumption
Diet
Physical inactivity
Obesity
Accidents
Working environment
Environmental factors
Citizen Modifiable Risk Factors
Non-Modifiable Risk Factors
Family history and gender