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Health Serv Res. 2009 Feb;44(1):303-20. doi: 10.1111/j.1475-6773.2008.00909.x.

Comparing cost-of-illness estimates from alternative approaches: an application to diabetes.

Author information

1
RTI International and RTI-UNC Center of Excellence in Health Promotion Economics, 118 Beaufain Street, Charleston, SC 29401, USA. honeycutt@rti.org

Abstract

OBJECTIVE:

To compare disease cost estimates from two commonly used approaches.

DATA SOURCE:

Pooled Medical Expenditure Panel Survey (MEPS) data for 1998-2003.

STUDY DESIGN:

We compared regression-based (RB) and attributable fraction (AF) approaches for estimating disease-attributable costs with an application to diabetes. The RB approach used results from econometric models of disease costs, while the AF approach used epidemiologic formulas for diabetes-attributable fractions combined with the total costs for seven conditions that result from diabetes.

DATA EXTRACTION:

We used SAS version 9.1 to create a dataset that combined data from six consecutive years of MEPS.

PRINCIPAL FINDINGS:

The RB approach produced higher estimates of diabetes-attributable medical spending ($52.9 billion in 2004 dollars) than the AF approach ($37.1 billion in 2004 dollars). RB model estimates may in part be higher because of the challenges of implementing the two approaches in a similar manner, but may also be higher because they capture the costs of increased treatment intensity for those with the disease.

CONCLUSIONS:

We recommend using the RB approach for estimating disease costs whenever individual-level data on health care spending are available and when the presence of the disease affects treatment costs for other conditions, as in the case of diabetes.

PMID:
19146569
PMCID:
PMC2669634
DOI:
10.1111/j.1475-6773.2008.00909.x
[Indexed for MEDLINE]
Free PMC Article

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