J Korean Acad Nurs.  2011 Dec;41(6):750-757. 10.4040/jkan.2011.41.6.750.

Comparison of Benefit Estimation Models in Cost-Benefit Analysis: A Case of Chronic Hypertension Management Programs

Affiliations
  • 1Department of Nursing, Inha University, Incheon, Korea. lim20712@inha.ac.kr
  • 2College of Nursing, University of Illinois at Chicago, Chicago, U.S.A.
  • 3Women's Policy Division, Incheon Metropolitan City Hall, Incheon, Korea.

Abstract

PURPOSE
Cost-benefit analysis is one of the most commonly used economic evaluation methods, which helps to inform the economic value of a program to decision makers. However, the selection of a correct benefit estimation method remains critical for accurate cost-benefit analysis. This paper compared benefit estimations among three different benefit estimation models.
METHODS
Data from community-based chronic hypertension management programs in a city in South Korea were used. Three different benefit estimation methods were compared. The first was a standard deterministic estimation model; second, a repeated-measures deterministic estimation model; and third, a transitional probability estimation model.
RESULTS
The estimated net benefit of the three different methods were $1,273.01, $-3,749.42, and $-5,122.55 respectively.
CONCLUSION
The transitional probability estimation model showed the most correct and realistic benefit estimation, as it traced possible paths of changing status between time points and it accounted for both positive and negative benefits.

Keyword

Cost-benefit analysis; Evaluation methodology; Hypertension; Probability; Nursing services

MeSH Terms

Adult
Aged
Blood Pressure
Chronic Disease
Cost-Benefit Analysis/*methods
Databases, Factual
Female
Humans
Hypertension/economics/*therapy
Male
Middle Aged
*Models, Statistical
Program Evaluation

Figure

  • Figure 1 Three different benefit estimation models. •Hypertension; ▪Mild; ▴Moderate; ♦Severe; ○Standard deterministic estimation model; □Repeated-measures deterministic estimation model; ▵Transitional probability estimation model.


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