BACKGROUND: Models commonly used for the economic assessment of chlamydial screening programs do not consider population effects. GOAL: To develop a novel dynamic approach for the economic evaluation of chlamydial prevention measures and to determine the cost-effectiveness of a general practitioner-based screening program. STUDY DESIGN: The dynamic approach was used to estimate the cost-effectiveness of a screening program for the first 10 years of screening in The Netherlands. Screening involved a ligase chain reaction test on urine followed by standardized therapies and partner referral. Eligible persons were sexually active, 15 to 24 years, visited a general practitioner, and had no symptoms of sexually transmitted diseases. The heterosexual model population, which consisted of persons 15 to 64 years, had a total chlamydial prevalence of 4.1% before screening. Screening effects on chlamydial incidence were computed by using a population-based stochastic simulation model. Incidence data were connected with a decision analysis model to determine the health effects of the program. The net costs of the program were calculated (investment costs minus averted costs, in 1997 US$) from a societal perspective and expressed per major outcome averted (symptomatic pelvic inflammatory disease, chronic pelvic pain, ectopic pregnancy, infertility, neonatal pneumonia). RESULTS: Unlike the standard static approach, our model adequately addresses dynamic processes such as chlamydial transmission and the impact of screening programs on chlamydial incidence in the population. During the first 10 years of screening, the investigated program yields savings of US $492 or US $1,086 per major outcome averted, excluding or including indirect costs, respectively. These results depend on chlamydial prevalence and partner referral. CONCLUSIONS: The cost-effectiveness of chlamydial screening programs seems best to be determined by using dynamic modeling on a population basis. In addition to preventing negative health outcomes, the investigated screening program may save costs.
BACKGROUND: Models commonly used for the economic assessment of chlamydial screening programs do not consider population effects. GOAL: To develop a novel dynamic approach for the economic evaluation of chlamydial prevention measures and to determine the cost-effectiveness of a general practitioner-based screening program. STUDY DESIGN: The dynamic approach was used to estimate the cost-effectiveness of a screening program for the first 10 years of screening in The Netherlands. Screening involved a ligase chain reaction test on urine followed by standardized therapies and partner referral. Eligible persons were sexually active, 15 to 24 years, visited a general practitioner, and had no symptoms of sexually transmitted diseases. The heterosexual model population, which consisted of persons 15 to 64 years, had a total chlamydial prevalence of 4.1% before screening. Screening effects on chlamydial incidence were computed by using a population-based stochastic simulation model. Incidence data were connected with a decision analysis model to determine the health effects of the program. The net costs of the program were calculated (investment costs minus averted costs, in 1997 US$) from a societal perspective and expressed per major outcome averted (symptomatic pelvic inflammatory disease, chronic pelvic pain, ectopic pregnancy, infertility, neonatal pneumonia). RESULTS: Unlike the standard static approach, our model adequately addresses dynamic processes such as chlamydial transmission and the impact of screening programs on chlamydial incidence in the population. During the first 10 years of screening, the investigated program yields savings of US $492 or US $1,086 per major outcome averted, excluding or including indirect costs, respectively. These results depend on chlamydial prevalence and partner referral. CONCLUSIONS: The cost-effectiveness of chlamydial screening programs seems best to be determined by using dynamic modeling on a population basis. In addition to preventing negative health outcomes, the investigated screening program may save costs.
Authors: E Honey; C Augood; A Templeton; I Russell; J Paavonen; P-A Mårdh; A Stary; B Stray-Pedersen Journal: Sex Transm Infect Date: 2002-12 Impact factor: 3.519
Authors: Jarir Atthobari; Jasper M Bos; Cornelis Boersma; Jacobus R B J Brouwers; Lolkje T W de Jong-van den Berg; Maarten J Postma Journal: Pharm World Sci Date: 2005-10
Authors: Ingrid V F van den Broek; Christian J P A Hoebe; Jan E A M van Bergen; Elfi E H G Brouwers; Eva M de Feijter; Johannes S A Fennema; Hannelore M Götz; Rik H Koekenbier; Sander M van Ravesteijn; Eline L M Op de Coul Journal: BMC Infect Dis Date: 2010-04-07 Impact factor: 3.090