title: A standardized vascular disease health check in europe: a cost-effectiveness analysis.
abstract: BACKGROUND
  No clinical trials have assessed the effects or cost-effectiveness of health check strategies to detect and manage vascular disease. We used a mathematical model to estimate the cost-effectiveness of several health check strategies in six European countries.
  
  
  METHODS
  We used country-specific data from Denmark, France, Germany, Italy, Poland, and the United Kingdom to generate simulated populations of individuals aged 40-75 eligible for health checks in those countries (e.g. individuals without a previous diagnosis of diabetes, myocardial infarction, stroke, or serious chronic kidney disease). For each country, we used the Archimedes model to compare seven health check strategies consisting of assessments for diabetes, hypertension, lipids, and smoking. For patients diagnosed with vascular disease, treatment was simulated in a standard manner. We calculated the effects of each strategy on the incidence of type 2 diabetes, major adverse cardiovascular events (MACE), and microvascular complications in addition to quality of life, costs, and cost per quality-adjusted life-year (QALY).
  
  
  RESULTS
  Compared with current care, health checks reduced the incidence of MACE (6-17 events prevented per 1000 people screened) and diabetes related microvasular complications (5-11 events prevented per 1000 people screened), and increased QALYs (31-59 discounted QALYs) over 30 years, in all countries. The cost per QALY of offering a health check to all individuals in the study cohort ranged from €14903 (France) to cost saving (Poland). Pre-screening the population and offering health checks only to higher risk individuals lowered the cost per QALY. Pre-screening on the basis of obesity had a cost per QALY of €10200 (France) or less, and pre-screening with a non-invasive risk score was similar.
  
  
  CONCLUSIONS
  A vascular disease health check would likely be cost effective at 30 years in Denmark, France, Germany, Italy, Poland, and the United Kingdom.
authors.affiliation: Archimedes, Inc., San Francisco, California, USA. andy.schuetz@archimedesmodel.com
authors.forename: C Andy
authors.initials: CA
authors.lastname: Schuetz
authors.forename: Peter
authors.initials: P
authors.lastname: Alperin
authors.forename: Swathi
authors.initials: S
authors.lastname: Guda
authors.forename: Andrew
authors.initials: A
authors.lastname: van Herick
authors.forename: Bertrand
authors.initials: B
authors.lastname: Cariou
authors.forename: David
authors.initials: D
authors.lastname: Eddy
authors.forename: Janusz
authors.initials: J
authors.lastname: Gumprecht
authors.forename: Antonio
authors.initials: A
authors.lastname: Nicolucci
authors.forename: Peter
authors.initials: P
authors.lastname: Schwarz
authors.forename: Nick J
authors.initials: NJ
authors.lastname: Wareham
authors.forename: Daniel R
authors.initials: DR
authors.lastname: Witte
authors.forename: Ulf
authors.initials: U
authors.lastname: Smith
mesh_terms: D000328:Adult; D000368:Aged; D002318:Cardiovascular Diseases / Q000175:diagnosis / Q000453:epidemiology / Q000517:prevention & control*; D003362:Cost-Benefit Analysis; D003924:Diabetes Mellitus, Type 2 / Q000175:diagnosis / Q000453:epidemiology* / Q000517:prevention & control; D005060:Europe / Q000453:epidemiology; D005260:Female; D006801:Humans; D006973:Hypertension / Q000175:diagnosis / Q000453:epidemiology / Q000517:prevention & control; D015994:Incidence; D008297:Male; D008403:Mass Screening / Q000191:economics / Q000379:methods; D008875:Middle Aged; D008962:Models, Theoretical; D011788:Quality of Life; D019057:Quality-Adjusted Life Years; D013997:Time Factors; D014652:Vascular Diseases / Q000175:diagnosis* / Q000453:epidemiology / Q000517:prevention & control