BACKGROUND: The purpose of this article was to describe methods that sexually transmitted disease (STD) programs can use to estimate the potential effects of changes in their budgets in terms of disease burden and direct medical costs. METHODS: We proposed 2 distinct approaches to estimate the potential effect of changes in funding on subsequent STD burden, one based on an analysis of state-level STD prevention funding and gonorrhea case rates and one based on analyses of the effect of Disease Intervention Specialist (DIS) activities on gonorrhea case rates. We also illustrated how programs can estimate the impact of budget changes on intermediate outcomes, such as partner services. Finally, we provided an example of the application of these methods for a hypothetical state STD prevention program. RESULTS: The methods we proposed can provide general approximations of how a change in STD prevention funding might affect the level of STD prevention services provided, STD incidence rates, and the direct medical cost burden of STDs. In applying these methods to a hypothetical state, a reduction in annual funding of US $200,000 was estimated to lead to subsequent increases in STDs of 1.6% to 3.6%. Over 10 years, the reduction in funding totaled US $2.0 million, whereas the cumulative, additional direct medical costs of the increase in STDs totaled US $3.7 to US $8.4 million. CONCLUSIONS: The methods we proposed, though subject to important limitations, can allow STD prevention personnel to calculate evidence-based estimates of the effects of changes in their budget.
BACKGROUND: The purpose of this article was to describe methods that sexually transmitted disease (STD) programs can use to estimate the potential effects of changes in their budgets in terms of disease burden and direct medical costs. METHODS: We proposed 2 distinct approaches to estimate the potential effect of changes in funding on subsequent STD burden, one based on an analysis of state-level STD prevention funding and gonorrhea case rates and one based on analyses of the effect of Disease Intervention Specialist (DIS) activities on gonorrhea case rates. We also illustrated how programs can estimate the impact of budget changes on intermediate outcomes, such as partner services. Finally, we provided an example of the application of these methods for a hypothetical state STD prevention program. RESULTS: The methods we proposed can provide general approximations of how a change in STD prevention funding might affect the level of STD prevention services provided, STD incidence rates, and the direct medical cost burden of STDs. In applying these methods to a hypothetical state, a reduction in annual funding of US $200,000 was estimated to lead to subsequent increases in STDs of 1.6% to 3.6%. Over 10 years, the reduction in funding totaled US $2.0 million, whereas the cumulative, additional direct medical costs of the increase in STDs totaled US $3.7 to US $8.4 million. CONCLUSIONS: The methods we proposed, though subject to important limitations, can allow STD prevention personnel to calculate evidence-based estimates of the effects of changes in their budget.
Authors: Paul G Farnham; David R Holtgrave; Chaitra Gopalappa; Angela B Hutchinson; Stephanie L Sansom Journal: J Acquir Immune Defic Syndr Date: 2013-10-01 Impact factor: 3.731
Authors: Matthew R Golden; Matthew Hogben; H Hunter Handsfield; Janet S St Lawrence; John J Potterat; King K Holmes Journal: Sex Transm Dis Date: 2003-06 Impact factor: 2.830
Authors: Kwame Owusu-Edusei; Harrell W Chesson; Thomas L Gift; Guoyu Tao; Reena Mahajan; Marie Cheryl Bañez Ocfemia; Charlotte K Kent Journal: Sex Transm Dis Date: 2013-03 Impact factor: 2.830