title: Designing a prospective study when randomization is not feasible.
abstract: When conducting a randomized controlled trial (RCT) is unfeasible, the goal is to replicate the randomization process by creating a control group that is essentially equivalent to the treatment group on known pre-intervention characteristics and assume that the remaining unknown characteristics will not bias the results. The strategies proposed in this article are based on the thesis that since only pre-intervention characteristics are used for adjustment, a comparable control group can be established as soon as the participant group is identified. Consequently, outcomes can be observed immediately after launching the initiative rather than waiting until study completion. The benefit is that significant treatment effects can be observed as they occur, or alternatively, the initiative can be cancelled if treatment effects are not attained by a certain time point. Although these methods can never ensure the same level of validity as in an RCT, they are considered robust alternatives when randomization is impractical, and therefore a compelling study design for many commercial initiatives, such as disease management programs, benefit design changes, and pay-for-performance efforts. An obvious constraint is that treated participants must first be identified before suitable controls can be found. The preferred strategy is to enroll the entire treatment group within a narrow time frame. An alternative option is to have periodic enrollment periods with their respective treatment and control cohorts. The concept proposed in this article is intended to offer a robust alternative to the inadequate strategies currently being used in many health care settings where study findings may not be trusted, and thus decision makers remain uninformed as to whether an initiative is worth continuing or cancelled.
authors.affiliation: Linden Consulting Group, OR, USA. alinden@lindenconsulting.org
authors.forename: Ariel
authors.initials: A
authors.lastname: Linden
mesh_terms: D006801:Humans; D015999:Multivariate Analysis; D057216:Propensity Score; D011446:Prospective Studies; D011897:Random Allocation; D012107:Research Design; D018570:Risk Assessment; D015983:Selection Bias