Background: Soil-transmitted helminth (STH) control programs currently lack evidence-based recommendations for cost-efficient survey designs for monitoring and evaluation. Here, we present a framework to provide evidence-based recommendations, using a case study of therapeutic drug efficacy monitoring based on the examination of helminth eggs in stool. Methods: We performed an in-depth analysis of the operational costs to process one stool sample for three diagnostic methods (Kato-Katz, Mini-FLOTAC and FECPAKG2). Next, we performed simulations to determine the probability of detecting a truly reduced therapeutic efficacy for different scenarios of STH species (Ascaris lumbricoides, Trichuris trichiura and hookworms), pre-treatment infection levels, survey design (screen and select (SS); screen, select and retest (SSR) and no selection (NS)) and number of subjects enrolled (100-5,000). Finally, we integrated the outcome of the cost assessment into the simulation study to estimate the total survey costs and determined the most cost-efficient survey design. Principal findings: Kato-Katz allowed for both the highest sample throughput and the lowest cost per test, while FECPAKG2 required both the most laboratory time and was the most expensive. Counting of eggs accounted for 23% (FECPAKG2) or ≥80% (Kato-Katz and Mini-FLOTAC) of the total time-to-result. NS survey designs in combination with Kato-Katz were the most cost-efficient to assess therapeutic drug efficacy in all scenarios of STH species and endemicity. Conclusions/significance: We confirm that Kato-Katz is the fecal egg counting method of choice for monitoring therapeutic drug efficacy, but that the survey design currently recommended by WHO (SS) should be updated. Our generic framework, which captures laboratory time and material costs, can be used to further support cost-efficient choices for other important surveys informing STH control programs. In addition, it can be used to explore the value of alternative diagnostic techniques, like automated egg counting, which may further reduce operational costs.