Decision making in health care is complex, and substantial uncertainty can be involved. Structured, systematic approaches to the integration of available evidence, assessment of uncertainty, and determination of choice are of significant benefit in an era of "value-based care." This is especially true for otolaryngology-head and neck surgery, where technological advancements are frequent and applicable to an array of subspecialties. Decision analysis aims to achieve these goals through various modeling techniques, including (1) decision trees, (2) Markov process, (3) microsimulation, and (4) discrete event simulation. While decision models have been used for decades, many clinicians and researchers continue to have difficulty deciphering them. In this review, we present an overview of various decision analysis modeling techniques, their purposes, how they can be interpreted, and commonly used syntax to promote understanding and use of these approaches. Throughout, we provide a sample research question to facilitate discussion of the advantages and disadvantages of each technique.
Keywords: Markov model; decision analysis; decision modeling; discrete event simulation; economic evaluation; evidence-based medicine; microsimulation model.