3Q's for QI | Q&A with Dr. Michelle Knees
May 1, 2024
Diagnostic error may result in serious harm for more than 500,000 patients and contribute to an estimated 10% of all patient deaths. Understanding diagnostic accuracy is crucial for improving patient outcomes and ensuring effective healthcare delivery. IHQSE Faculty, Drs. Michelle Knees and Katie Raffel, along with colleagues from the University of Colorado Division of Hospital Medicine, recently published an AHRQ Issue Brief aimed at furthering efforts to enhance diagnostic accuracy. The brief reviews a substantial body of literature on the impact of cognitive load on diagnostic accuracy, identifies areas for future research, and provides recommendations for integrating existing knowledge into current practice.
Tell us about your approach to this project?
Diagnostic accuracy is a critical component to clinicians’ ability to provide safe patient care, but surprisingly little has been written about the role of cognitive load on diagnostic accuracy. We aimed to synthesize existing research on cognitive load and its effects on diagnostic performance. We began by conducting an extensive literature review to gather relevant studies and data. This involved analyzing research findings to identify key themes and gaps in the current understanding of cognitive load in diagnostic settings. There is a relative dearth of high-quality research investigating the causal links between cognitive load and diagnostic accuracy, so we also wanted to focus on providing researchers with possible metrics and future studies that could be performed to further this field of research. The overarching goal was to create a practical, evidence-based Issue Brief that could guide future research and inform clinical practice improvements.
Why is this work important?
This work is vital because diagnostic errors are a significant source of patient harm. By examining how cognitive load affects diagnostic accuracy, we can identify ways to mitigate these errors. Cognitive load refers to the mental effort required to process information and make decisions. In high-stakes medical environments, excessive cognitive load can overwhelm clinicians, leading to mistakes. Understanding the factors that contribute to cognitive load, and how they impact diagnostic performance, is essential for developing interventions that enhance diagnostic accuracy. This Issue Brief not only highlights the importance of cognitive ergonomics in healthcare but also provides actionable recommendations for improving cognitive load and, subsequently, diagnostic processes. Ultimately, this work aims to foster safer, more effective patient care by addressing what we believe to be one of the root causes of diagnostic errors.
How do you think this will impact healthcare?
This work has the potential to impact healthcare by enhancing the accuracy and reliability of medical diagnoses. By identifying the sources and effects of cognitive load on diagnostic performance, healthcare institutions can develop targeted strategies to reduce cognitive overload among clinicians. This could include the implementation of decision support tools, improved clinician team structures, and system-level changes to streamline workflows. Additionally, our recommendations can inform resource allocation to support diagnostic safety initiatives. In the long term, reducing diagnostic errors through better management of cognitive load can lead to improved patient outcomes, increased clinician satisfaction, and reduced healthcare costs. This research not only contributes to the academic understanding of cognitive load in the diagnostic process but also offers practical solutions that can be readily applied in clinical settings, driving meaningful improvements in patient care.
Other IHQSE Faculty involved:
Katie Raffel, MD
Read the full AHRQ Issue Brief here, and check out some other IHQSE publications on diagnostic accuracy and error:
Achieving diagnostic excellence through prevention and teamwork (ADEPT) study protocol: A multicenter, prospective quality and safety program to improve diagnostic processes in medical inpatients - Journal of Hospital Medicine
Prevalence and Causes of Diagnostic Errors in Hospitalized Patients Under Investigation for COVID-19 - Journal of General Internal Medicine