Abstract
Results from clinical studies are often subject to the risk of bias (deviation from the truth, systematic error). Therefore, a critical appraisal of studies provides auseful strategy in evidence-based healthcare to safeguard against wrong decisions and resulting in overtreatment or undertreatment. This article explains the frequently encountered types of bias, differentiates between them and provides strategies for avoidance of systematic errors. In addition, the two established Cochrane tools with which the risk of bias can be assessed in randomized and non-randomized studies are presented. To highlight the most important components of these tools for bias assessment, examples of randomization, confounding, blinding, completeness of data and selective reporting are provided. Finally, it is shown that bias should not be confused with other study limitations, such as external validity and imprecision.
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