OBJECTIVES: To improve research productivity in an economic environment with limited resources, researchers may need to consider investigator-initiated approaches to design cost-efficient studies. A cost function was developed to guide decisions about trade-offs to be made in clinical trial design with the objective of minimizing cost while achieving a given level of power to detect differences in patient-reported outcomes. METHODS: The design and conduct of a clinical study was treated as a constrained optimization problem. A cost function was developed, a Lagrangian function was constructed, and first-order partial derivatives were taken with respect to each choice variable (e.g., number of recruitment sites, number of follow-up visits, and study duration). Comparative statics analysis was used to examine the changes in the choice variables as a result of changes in the exogenous variables. RESULTS: A necessary condition to minimize cost while achieving a given power is the equivalence of the ratios of the marginal cost associated with increasing each choice variable and the marginal change in power associated with each choice variable; in other words the same cost per unit of output created by each input at the margin. For second-order condition, we made the reasonable assumption that increasing the number of participants recruited leads to a decrease in the marginal rate of change in the Type II error which holds. Comparative statics analysis showed that the increase or decrease in the rate of recruitment, expected percent loss to follow-up, and the cost of interventions lead to different trade-offs between the marginal cost of conducting the clinical trial and the marginal change in the probability of committing a Type II error. CONCLUSIONS: In light of funding challenges, researchers could consider the trade-offs required to achieve a cost-efficient study for a given level of power using methods from economics and optimization.