Forecasting the impact of heart failure in the United States: a policy statement from the American Heart Association

Circ Heart Fail. 2013 May;6(3):606-19. doi: 10.1161/HHF.0b013e318291329a. Epub 2013 Apr 24.

Abstract

Background: Heart failure (HF) is an important contributor to both the burden and cost of national healthcare expenditures, with more older Americans hospitalized for HF than for any other medical condition. With the aging of the population, the impact of HF is expected to increase substantially.

Methods and results: We estimated future costs of HF by adapting a methodology developed by the American Heart Association to project the epidemiology and future costs of HF from 2012 to 2030 without double counting the costs attributed to comorbid conditions. The model assumes that HF prevalence will remain constant by age, sex, and race/ethnicity and that rising costs and technological innovation will continue at the same rate. By 2030, >8 million people in the United States (1 in every 33) will have HF. Between 2012 and 2030, real (2010$) total direct medical costs of HF are projected to increase from $21 billion to $53 billion. Total costs, including indirect costs for HF, are estimated to increase from $31 billion in 2012 to $70 billion in 2030. If one assumes all costs of cardiac care for HF patients are attributable to HF (no cost attribution to comorbid conditions), the 2030 projected cost estimates of treating patients with HF will be 3-fold higher ($160 billion in direct costs).

Conclusions: The estimated prevalence and cost of care for HF will increase markedly because of aging of the population. Strategies to prevent HF and improve the efficiency of care are needed.

Keywords: AHA Scientific Statements; heart failure.

MeSH terms

  • Adult
  • American Heart Association
  • Comorbidity
  • Cost of Illness*
  • Female
  • Forecasting
  • Heart Failure / classification
  • Heart Failure / economics*
  • Heart Failure / epidemiology*
  • Heart Failure / mortality
  • Hospitalization / statistics & numerical data
  • Humans
  • Income
  • Male
  • Patient Care Team / organization & administration
  • Prevalence
  • Risk Factors
  • Terminal Care
  • United States / epidemiology