title: The comparative effectiveness of heart disease prevention and treatment strategies.
abstract: BACKGROUND
  Policymakers must be able to calculate the comparative effectiveness of interventions to control heart disease if they are to optimize the population impact of programmatic initiatives.
  
  
  METHODS
  A model was created to calculate the number of deaths that would be prevented or postponed if perfect care for heart disease prevention and treatment were achieved--that is, the elimination of risk factors and the prescription of all effective medications before and between acute events, and the delivery of all effective therapies to individuals suffering an acute heart disease event. The impact of perfect care was calculated for a hypothetic population aged 30-84 years with risk-factor levels, event rates, current patterns of behavior, levels of treatment, and mortality rates resembling those of the U.S. The analysis was performed in 2007 and 2008.
  
  
  RESULTS
  In this population, 44% of all deaths were due to heart disease. Perfect care before the first heart disease event would prevent or postpone 33% of all deaths. Perfect care between acute events would prevent or postpone 23% of all deaths. Perfect care during acute events would prevent or postpone 8% of all deaths.
  
  
  CONCLUSIONS
  This direct comparison of heart disease prevention and treatment strategies indicates that nearly 90% of the impact from perfect care for heart disease would accrue from interventions before and between acute events. The impact of risk-factor interventions before or between events is amplified by the fact that these interventions also reduce the risk of death from other chronic diseases.
authors.affiliation: HealthPartners Research Foundation, Minneapolis, Minnesota 55440-1524, USA. thomas.e.kottke@healthpartners.com.
authors.forename: Thomas E
authors.initials: TE
authors.lastname: Kottke
authors.forename: Dennis A
authors.initials: DA
authors.lastname: Faith
authors.forename: Courtney O
authors.initials: CO
authors.lastname: Jordan
authors.forename: Nicolaas P
authors.initials: NP
authors.lastname: Pronk
authors.forename: Randal J
authors.initials: RJ
authors.lastname: Thomas
authors.forename: Simon
authors.initials: S
authors.lastname: Capewell
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D003198:Computer Simulation; D019317:Evidence-Based Medicine; D005260:Female; D006331:Heart Diseases / Q000401:mortality / Q000517:prevention & control / Q000628:therapy*; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D012307:Risk Factors; D016019:Survival Analysis; D014481:United States / Q000453:epidemiology