Abstract: Fatigue is a latent hazard in health care, (particularly in emergency departments-ED), leading to poor judgement and increased medical errors. Fatigue-induced adverse events have negative financial and patient/occupational safety impact in EDs and other settings. Commonly used time- and task-management strategies (e.g., multitasking), are much less effective in clinicians with fatigue. Potential causes, consequences, and fatigue-induced adverse events, have been studied, however interventions to mitigate risks is limited. Currently proposed solutions to obviate fatigue (e.g., limit working hours, decreased patient load) can be helpful, but fatigue is a complex construct, making it less feasible to develop uncomplicated solutions. Decades of adaptive automation literature suggest that clinical decision support (CDS) systems that can adapt to in-the-moment variations in clinician’s fatigue, have potential to intercept fatigue-induced human errors and preclude potential adverse events. A criticism of CDS, is that it only provides decontextualized decision support when it has potential to be adapted to its users (i.e., frontline clinicians). Users with different fatigue level have different needs. When CDS support is decontextualized, it becomes part of the background that actually contribute to clinician fatigue. Clinicians not welcoming CDS prompts, develop strategies to avoid interacting with the CDS, which can lead to negative outcomes. Adaptive CDS would configure itself based on a clinician’s fatigue level to provide the right level of information, to the right user, at the right time. The primary objective of this study is to develop the foundation for adaptive CDS in EDs, that is sensitive to a user’s fatigue and adapts to the user’s fatigue level. A mixed method design will be used to achieve our objective through two aims: (1) Examine the impact of ED clinician fatigue on (a) clinical decision making and (b) the use of the CDS for antibiotic prescription; (2) Develop and evaluate CDS design and implementation guidelines for a CDS that adapts to ED clinician fatigue. The unique contribution of this study lies in (1) creating a foundation for a novel health information technology (HIT), adaptable CDS; (2) integrating cognitive decision-making theories into the CDS design; (3) developing a CDS to accommodate the prevalent negative work condition, fatigue. Three main deliverables will be disseminated comprehensively. First, we will provide a detailed description of impact of fatigue on clinical decision making. Second, we will provide a detailed description of impact of fatigue on the use of clinical decision support systems in EDs. Third, we will report on design guidelines for adaptive CDS, thereby supporting replicability by other scholars and designers. Eventually, this proposal will improve clinician’s performance under challenging work conditions, hence patient outcomes.