Programmatic economic analyses can provide important information on the relative costs and benefits of an intervention, program, or policy. Such information is often demanded by decision makers to help assess the relative value between a set of alternative options. Types of economic analyses include programmatic cost estimation, cost-of-illness studies, cost-effectiveness analyses, benefit-cost analyses, and return on investment analyses, and several others.
NORC is a leader in the development of practical guidelines for government policy makers in the use of economic analyses within the Department of Health and Human Services. On behalf of the Assistant Secretary for Planning and Evaluation of Health and Human Services, NORC developed concrete guidance on how to understand and use decision-analytic modeling information to inform governmental decision-making. This report (which can be accessed at
) provides an in depth discussion of the approaches to economic evaluation, the valuation of health benefits, modelling methodology and differences between study designs, and best practices for sound economic modelling, and information regarding sensitivity analyses.(1) In a subsequent and forthcoming document, NORC partnered with researchers from Harvard University and the research firm Industrial Economics, Inc. to develop guidance on the evaluation of potential cost of illness estimates for use in federal regulatory benefit-cost analysis. Finally, NORC has conducted advisory work for the Patient Centered Outcomes Research institute (PCORI) on the use of value of information approaches (an advanced extension of cost-effectiveness analyses) to set research priorities.(2)
NORC also offers hands on experience in the application of cost-effectiveness and benefit-cost analyses to inform public health policy. In the area of cost-effectiveness, NORC developed the cost-effectiveness evidence in support of CDC’s ‘Baby Boomer’ hepatitis C testing recommendation. This work was featured as an early release in Annals of Internal Medicine, and led directly to a change in CDC testing guidelines for hepatitis C.(3) NORC researchers have utilized state of the art cost-effectiveness methods such as probabilistic sensitivity analyses, cost-effectiveness acceptability curves, incremental net benefit outcomes, cost-effectiveness estimates by payer, and expected value of perfect information calculations.(4)
1. Miller W, Rein DB, O'Grady M, Yeung JE, Eichner J, McMahon M.
A Review and Analysis of Economic Models of Prevention Benefits. Office of the Assitant Secretary for Planning and Evaluation, 2013.
2. Rein DB.
Value of Information and Research Prioritization. Patient Centered Outcomes Research institute 2012.
3. Rein DB, Smith BD, Wittenborn JS, Lesesne SB, Wagner LD, Roblin DW, et al. The Cost-Effectiveness of Birth-Cohort Screening for Hepatitis C Antibody in U.S. Primary Care Settings.
Ann Intern Med. 2011.
4. Rein DB, Wittenborn JS, Zhang X, Allaire BA, Song MS, Klein R, et al. The cost-effectiveness of three screening alternatives for people with diabetes with no or early diabetic retinopathy.
Health Serv Res. 2011;46(5):1534-61.