How Technology Can Reduce Biases When Assigning Triage Acuity

Many types of bias can impact triage decision-making and negatively impact patient outcomes. Often, these biases from nurses are unconscious, which makes education about them even more essential for health care professionals and their patients.

Sheri Dungan, BSN, RN, MICN, SANE-A, SANE-P, CEN
Sheri Dungan, BSN, RN, MICN, SANE-A, SANE-P, CEN

Adventist Health ED Clinical Practice Specialist Sheri Dungan, BSN, RN, MICN, SANE-A, SANE-P, CEN, will present “Three Blind Mice … Volume, Gender, and Race Bias in Assigning Triage Acuity: Using Technology to See More Clearly” from 3:30-4:15 p.m. Pacific time on Sept. 22 at Emergency Nursing 2023.

“Biases are like mental shortcuts, which nurses need because they’re often asked to make quick decisions based on the information available to them,” Dungan explained. “However, these mental shortcuts are influenced by our culture, gender, age and other factors. If we’re not willing to examine and challenge our biases, we could end up making some bad decisions for our patients.”   

She will share data with attendees that illustrates how factors like gender, race and volume in the emergency department can influence a provider’s decision-making while assigning triage acuity.

“To address our biases, it’s important to keep them top of mind because when we’re experiencing a particularly stressful period at work, we tend to default to our old, practiced behaviors,” Dungan said. “We need to be able to challenge ourselves and question the assumptions we make to provide the best care for patients.” 

In addition to recognizing biases and their causes, Dungan will explore technological tools that can reduce biases from the triaging process. 

One such system, KATE, uses real-time artificial intelligence to notify triage nurses of anomalies in care that merit a second look. KATE combines clinical expertise and learnings informed by more than 10 billion data points to predict the acuity of emergency triage patients. KATE operates within existing workflows and with any electronic health record. Dungan will also share strategies to successfully implement this technology in the clinical setting to ensure it is used ethically and effectively.

“Standardized tools can help reduce biases from the intake process. KATE doesn’t have to worry about factors like stress, fatigue or other unconscious biases affecting its decision-making,” she explained.

Those interested in learning more about KATE may do so here.

Health systems that don’t have these technological capabilities can still use standardized guidelines that account for biases, such as the Emergency Severity Index (ESI) endorsed by ENA. Dungan will also review the ESI scale and how it should be implemented into the triage process.

“The first and most important step in combating biases is to prioritize self-awareness,” she said. “Once people become aware of the problem, we can help them identify the tools available to avoid it.”