Kenneth J. Smith et al. Table 2: Direct and indirect costs per screening test received and ranges examined in sensitivity analyses. Costs of clinic screening Direct costs Clinician cost Test cost Indirect costs Monetary (mean [SD])∗ Time (hours) (mean [SD])† Time value (per hour) Costs of home screening Direct costs Test cost, packaging, and postage Base case 28 21 25 2.97 [7.55] 3.7 [2.7] 16 Range 12–50 10–32 0–25 0.4–10.5 7–25 15–35 ∗ Parking/transportation plus babysitter/childcare. † Time oﬀ work or school, plus time donated by others so that care could be received. to be received per clinic visit. Combined direct and indirect costs per clinic visit totaled 111. Table 3 displays tests performed, testing costs, and cost- eﬀectiveness results for all study subjects and for subgroups based on recruitment site. More tests and more asymp- tomatic tests were performed among the home screening group (P < .0001), with greater diﬀerences in testing rates seen in women recruited from neighborhoods. Women re- cruited from clinics had high testing rates and a smaller diﬀerential between home and clinic-based testing. No dif- ference in STD incidence was noted between intervention groups (20.4 [home testing] versus 24.1 [clinic testing] per 100 woman-years, P = .28). Considering total costs for all subjects and all testing, and assuming equal STD detection between groups, the home testing intervention was cost saving, because fewer clinic- based tests were performed and the resulting cost savings were not completely oﬀset by the costs of increased home testing (Table 3). Total testing costs per infection found were estimated at 702 in the intervention group and 717 in the control group. However, cost savings were not noted for the neighborhood recruitment subgroup, where each additional test obtained by the intervention group compared to the con- trol group cost about 24.50, due to more frequent home- based testing and no decrease in clinic testing with the in- tervention. When only asymptomatic testing was considered in all subjects, the intervention cost was 12.51 per additional test performed, since the costs of increased home testing were not oﬀset by the relativity small decreases in clinic-based test- ing in the intervention group. In one-way sensitivity analyses, four parameter values varied individually through their listed ranges (Table 2) made the total cost per subject of all testing in the inter- vention group greater than the total cost per subject in the control group (Table 4). The model was most sensitive to changes in home testing costs, with increases in this cost of ≥5 making the home testing intervention more expensive than clinic testing; to have similar eﬀects, time spent seek- Home testing not cost saving 3 5 4 ttsse rea eohm treyp 3 ien jceb 2 sa u s re r Icn ep 1 0 0 Home testing cost saving 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Decrease in clinic tests per subject per year 1 Figure 1: Two-way sensitivity analysis on changes in testing rates resulting from a home testing intervention. The line represents points where the overall costs of a home testing program or clinic- based testing are equal when gonorrhea and chlamydia detection rates are the same with either program. Points denoting changes in home and clinic testing frequency occurring due to a home testing program that fall in the area below the line (e.g., the “X”) indicate that cost savings would occur with that program. Points above the line (e.g., the open square) denote parameter values where cost sav- ings would not occur. ing/receiving care, the cost of that time, or clinic testing cost would need to decrease by about a third. Most importantly, if infection detection frequency is not equal between groups, unlike the equal detection seen in the DAISY trial and as- sumed in this analysis, between-group diﬀerences in infec- tion costs and complication eﬀects would need to be explic- itly accounted for in the analysis. In the probabilistic sensitivity analysis, where all cost and testing parameters were varied simultaneously, the interven- tion was cost saving in 52% of model iterations when all test- ing was considered. When considering only asymptomatic testing, there was a 22% likelihood that the intervention would be cost saving. Figure 1 illustrates the relationship of changes in testing rates to cost savings with a home testing program if infec- tion detection rates are equal between groups. If per-patient clinic testing rates decrease by more than 22.5% of the in- crease seen in home testing rates due to program adoption, a home testing program will be cost saving. For example, if a home testing intervention increases home testing in a popu- lation by 1 test per patient per year and decreases yearly clinic testing by 0.4 tests per patient (denoted by the “X” in Fig- ure 1), then the intervention would be cost saving. However, with the same increase in home testing, if the clinic testing rate only decreases by 0.1 test per patient (denoted by the open square), then a home testing program is not cost sav- ing. In this analysis of a program encouraging home test- ing for chlamydia and gonorrhea in a high-risk group of young women, we found that, when all costs and all tests were considered, a home testing program was cost saving in the DAISY study, a randomized, controlled trial, while, at the same time, signiﬁcant increases in all tests and in asymptomatic tests were seen. However, whether cost savings