By Amy Koroba

With the development of technology, AI has penetrated nearly every industry, optimising roles previously performed by humans in the workplace. The medical industry is no different. One way AI is used in healthcare is through patient triage. While it has been shown to improve efficiency and accuracy, AI is a support tool, not a complete replacement. 

What is Patient Triage?

Patient triage is the sorting and allocation of treatments to patients, especially disaster victims, according to a system of priorities designed to maximise the number of survivors and utilise available resources. [3] These factors include vital signs, urgency of the conditions and other indicators that help determine whether a patient requires urgent care. 

The Problem with Manual Patient Triage

Patient triage decisions are important for patients and medical staff. However, the traditional process has limitations. The manual process of patient triage can be laborious, considering the time constraints, mental pressure and the large number of patients waiting to receive treatment. Under these conditions, patients may be underexamined, particularly in understaffed hospitals. In addition, a study on triage nurses found that as nurses gain experience, triage decisions become more holistic and intuitive [1], which may lead to biased or incorrect assessments.

AI in Patient Triage

In recent years, AI has emerged as a tool for optimising patient triage. It processes patient data through objective and standardised criteria, helping hospitals make more informed decisions about resource allocation while minimising human error. A review of AI patient triage during hospital emergencies showed that it improves triage efficiency. More specifically, it predicts hospital admissions, identifies critical conditions, and alleviates overflow of the emergency department. [4] For instance, Mass General Brigham, an integrated healthcare system based in Boston, uses AI to support clinical decision-making. [2]

Why Human Efforts are Still Important

Despite the efficiency of AI and the benefits of its use in the industry, human thought and analysis remain crucial to triage and human care. For instance, AI may lack the ability to make judgments in scenarios that lack precedents. AI works by analysing data on previous clinical assessments and makes new decisions based on observed patterns. It cannot process underrepresented cases. This is when humans need to step in to make decisions. Furthermore, AI cannot be accountable for the decisions it makes. Therefore, human review and approval are still necessary before using the decisions and judgments AI makes.

AI has become a valuable tool by improving efficiency and optimising resource allocation in high-pressure medical environments. Through its ability to process large amounts of data, it can assist medical staff in managing patient flow and case analysis. However, AI cannot completely replace human judgment. Therefore, the most effective approach is for AI to support professional decision-making by minimising human error.

References

  1. Gorick, H., McGee, M., & Smith, T. O. (2025). Assessments Under Pressure: Interviews With Triage Nurses in Emergency Departments: An Exploratory Descriptive Qualitative Study. Journal of Advanced Nursing. https://doi.org/10.1111/jan.70283
  2. IntuitionLabs. (2025, August 16). AI Adoption in U.S. Hospitals: Trends and Use Cases. IntuitionLabs. https://intuitionlabs.ai/articles/ai-adoption-us-hospitals-trends
  3. Merriam-Webster. (2019). Definition of TRIAGE. Merriam-Webster.com. https://www.merriam-webster.com/dictionary/triage
  4. Tyler, S., Olis, M., Aust, N., Patel, L., Simon, L., Triantafyllidis, C., Patel, V., Lee, D. W., Ginsberg, B., Ahmad, H., & Jacobs, R. J. (2024). Use of Artificial Intelligence in Triage in Hospital Emergency Departments: A Scoping Review. Cureus, 16(5). https://doi.org/10.7759/cureus.59906