3187.0: Monday, November 13, 2000 - Board 2

Abstract #5122

Linear programming as a tool for the efficient allocation of resources for the prevention of cardiovascular disease and cancer in South Carolina

David M. Ward, PhD1, James Zoller, PhD2, Marc D. Silverstein, MD2, Paul J Nietert, PhD2, Francis W. Lee, DBA1, Nikki Robertson, MHA1, and Karen Wager, DBA1. (1) Department of Health Administration and Policy, Medical University of South Carolina, 19 Hagood Avenue, 408 Harborview Tower, P.O. Box 250807, Charleston, SC 29425, (843)792-2119, wardd@musc.edu, (2) Center for HEalth Care Research, Medical University of South Carolina, 135 Rutledge Avenue, PO Box 250550, Charleston, SC 29425

Linear programming was combined with cost effectiveness studies, county demographics and epidemiologic data related to CVD and three cancers (Breast, Cervical, and Colorectal) to identify the most efficient allocation of prevention resources in South Carolina. The model distributes resources across county, age, gender, race, risk factors and interventions. The algorithms maximize the life years gained as a result of additional resources.

Findings from a model limited to CVD yielded the following:

Table 1:  
 
Population Served
Life Years Gained
Cost Per Life Year Gained
Full Funding - $606,825,000
1,397,260
25,484
$23,812
50% - $303,412,500
719,745
22,578
$13,438
5% - $30,000,000
88,165
5,932
$5,057

Additional constraints change the distribution of resources and the efficiency of the dollar allocation. Table 2 shows the efficiency loss associated with the different constraints when allocating $30,000,000.

Table 2:  
 
Population Served
Life Years Gained
Cost Per Life Year Gained
Unconstrained 
88,165
5,932
$5,057
Proportional by County
87,763
5,922
$5,066
Proportional by Race
91,341
5,868
$5,112
Proportional by Gender
93,499
5,667
$5,294
Equal by Gender
93,499
5,627
$5,331
Equal by County
89,851
5,535
$5,420

The allocation model developed in this study can provide policy makers with the ability to assess the impact of different resource allocation mechanisms. In addition, the model can be used to assess the value – in life years – of different decisions or constraints on the allocation of additional resources.

Learning Objectives: At the conclusion of the session, the participant (learner) in this session will: 1.Understand the use of linear programming as an extension of cost effectiveness analysis. 2.Assess the efficieny and distributional effects of distributing funds for the prevention of cardiovascular disease and cancer

Keywords: Economic Analysis, Methodology

Presenting author's disclosure statement:
Organization/institution whose products or services will be discussed: None
I do not have any significant financial interest/arrangement or affiliation with any organization/institution whose products or services are being discussed in this session.

The 128th Annual Meeting of APHA