Practical Implications of Differential Discounting in Cost-Effectiveness Analyses with Varying Numbers of Cohorts

• Published in: Value in health 2011-06, Vol.14 (4), p.438-442
• Main Authors: O'Mahony, James F., MA, de Kok, Inge M.C.M., PhD, van Rosmalen, Joost, PhD, Habbema, J. Dik F., PhD, Brouwer, Werner, PhD, van Ballegooijen, Marjolein, PhD
• Format: Article
• Language: English
• Subjects: Adolescent; Adult; Age Factors; Aged; Child; Cohort Effect; cohort models; Cost-Benefit Analysis - economics; Cost-Benefit Analysis - methods; cost-effectiveness analysis; differential discounting; Female; Humans; Internal Medicine; Middle Aged; Models, Statistical; Papillomavirus Vaccines - economics; Papillomavirus Vaccines - therapeutic use; population models; study comparability; Uterine Cervical Neoplasms - economics; Uterine Cervical Neoplasms - epidemiology; Uterine Cervical Neoplasms - prevention & control; Young Adult
• ISSN: 1098-3015; 1524-4733
• DOI: 10.1016/j.jval.2010.09.009

Abstract Objective To call attention to the influence of the number of birth-cohorts used in cost-effectiveness analysis (CEA) models on incremental cost-effectiveness ratios (ICERs) under differential discounting. Methods The consequences of increasing the number of birth-cohorts are demonstrated using a CEA of cervical cancer prevention as an example. The cost-effectiveness of vaccinating 12-year-old girls against the human papillomavirus is estimated with the MISCAN microsimulation screening analysis model for 1, 10, 20, and 30 birth-cohorts. Costs and health effects are discounted with equal rates of 4% and alternatively with differential rates of 4% and 1.5% respectively. The effects of increasing the number of cohorts are shown by comparing the ICERs under equal and differential discounting. Results The ICER decreases as the number of cohorts increases under differential discounting, but not under equal discounting. Conclusions The variation of ICERs with the number of cohorts under differential discounting prompts questions regarding the appropriate specification of CEA models and interpretation of their results. In particular, it raises concerns that arbitrary variation in study specification leads to arbitrary variation in results. Such variations could lead to erroneous policy decisions. These findings are relevant to CEA guidance authorities, CEA practitioners, and decision makers. Our results do not imply a problem with differential discounting per se, yet they highlight the need for practical guidance for its use.