Recent trends in Veterans Affairs chronic condition spending

Popul Health Manag. 2011 Dec;14(6):293-8. doi: 10.1089/pop.2010.0079. Epub 2011 Nov 1.

Abstract

The change in prevalence and total Veterans Affairs (VA) spending were estimated for 16 chronic condition categories between 2000 and 2008. The drivers of changes in spending also were examined. Chronic conditions were identified through diagnoses in encounter records, and treatment costs per patient were estimated using VA cost data and regression models. The estimated differences in total VA spending between 2000 and 2008 and the contributions of population increase, differences in prevalence, and differences in treatment costs were evaluated. Most of the spending increases during the study period were driven by the increase in the VA patient population from 3.3 million in 2000 to 4.9 million in 2008. Spending on renal failure increased the most, by more than $1.5 billion, primarily because of higher prevalence. Higher treatment costs did not contribute much to higher spending; lower costs per patient for several conditions may have helped to slow spending for diabetes, chronic obstructive pulmonary disease, heart conditions, renal failure, dementia, and stroke. Lowering treatment costs per patient for common conditions can help slow spending for chronic conditions, but most of the increase in spending in the study period was the result of more patients seeking care from VA providers and the higher prevalence of conditions among patients. As the VA patient population continues to age and to develop more co-morbidities, and as returning veterans seek care for service-related problems, higher spending on chronic conditions will become a more prominent issue for the VA health care system.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Adult
  • Aged
  • Chronic Disease / economics*
  • Female
  • Health Expenditures / trends*
  • Humans
  • Male
  • Medical Records
  • Middle Aged
  • Pharmaceutical Services / statistics & numerical data
  • Regression Analysis
  • United States
  • United States Department of Veterans Affairs*
  • Veterans*