For medical tests that have a central role in clinical decision-making, current guidelines advocate analytical performance specifications. Given that empirical (clinical trial-style) analyses are often impractical or unfeasible in this context, the ability to set such specifications is expected to rely on indirect studies to calculate the impact of test measurement uncertainty on downstream clinical, operational, and economic outcomes. Currently, however, a lack of awareness and guidance concerning available alternative indirect methods is limiting the production of outcome-based specifications. Therefore, our aim was to review available indirect methods and present an analytical framework to inform future outcome-based performance goals.A methodology review consisting of database searches and extensive citation tracking was conducted to identify studies using indirect methods to incorporate or evaluate the impact of test measurement uncertainty on downstream outcomes (including clinical accuracy, clinical utility, and/or costs). Eighty-two studies were identified, most of which evaluated the impact of imprecision and/or bias on clinical accuracy. A common analytical framework underpinning the various methods was identified, consisting of 3 key steps: () calculation of "" test values; () calculation of test values (incorporating uncertainty); and () calculation of the of discrepancies between () and () on specified outcomes. A summary of the methods adopted is provided, and key considerations are discussed.Various approaches are available for conducting indirect assessments to inform outcome-based performance specifications. This study provides an overview of methods and key considerations to inform future studies and research in this area.