Receiving accurate care in the Emergency Department (ED) is essential because diagnostic errors can have life-threatening consequences. Let’s first examine the role of care within the Emergency Room. In emergency medicine, time is of the essence, and the focus is often on ensuring patient safety, providing follow-up care, and ruling out immediate harm. However, miscommunication and unmanaged expectations can occur when the patient’s understanding of the role of treatment and diagnostic information is unclear. This scenario can lead to patients feeling unheard and potentially leaving the ED with undiagnosed conditions.
Unfortunately, diagnostic errors still occur when they might have been avoidable. According to the Agency for Healthcare Research and Quality (AHRQ), 68% of diagnostic errors associated with high-severity harm are attributed to 15 clinical conditions, primarily within vascular events, infection, and cancer categories. This data suggests the need for a more tractable and systems-based approach to improve these diagnostic outcomes.
Adopting a systems approach would allow clinicians to identify potential gaps in their diagnostic thinking, consider the likelihood of missed diagnoses, and determine appropriate diagnostic testing. Clinicians must acknowledge their fallibility and embrace a humanistic approach that encourages the use of tools and algorithms to enhance diagnostic capabilities. However, top-down enforcement of these tools may lead to resistance, highlighting the need to balance heroism and humanism.
Additionally, ED overcrowding poses a cognitive constraint on clinicians and limits their ability to incorporate additional tools for improved diagnostic outcomes. Under such conditions, cognitive biases can increase the rate of errors. Addressing ED overcrowding requires a focus on minimizing unnecessary ED visits and managing patient expectations effectively.
The availability of proven and beneficial tools is crucial for enhancing diagnostic accuracy. However, gathering outcomes data before implementing these tools to support their use is also essential. Introducing AI and machine learning algorithms into the market necessitates a systematic approach to managing the situation’s complexity rather than searching for a singular best answer.
Improving diagnostic accuracy in the ED requires a multifaceted approach. Clear communication, a systems perspective, humanistic thinking, addressing ED overcrowding, and implementing proven tools, are all vital steps to enhancing diagnostic outcomes. By recognizing the complexities involved and adopting a comprehensive approach, clinicians can strive for improved patient care and diagnostic accuracy in emergency medicine.