During Phase I, we propose to develop an Automated Multi-Language Emergency Triage Assister (AMLETA), an internet-based, software prototype to assist triage nurses rapidly identify underlying symptoms of patients presenting to an emergency department to better prioritize those patients when they are unable to speak English. AMLETA will be designed for use by patients who are conscious, which typically represents over 95% of patients arriving to the emergency department (Levels 2-5 of the Emergency Severity Index - see below), and are physically able to interact with a computer system. The system will quickly elicit the most critical information about a patient's condition and then summarize those findings, in real time, to the triage nurse who can then prioritize patients based on his/her training and the resources available within the department at the time. Although many emergency departments have live interpreters to help communicate with patients who cannot speak English, those interpreters may not be available immediately to assist as soon as a patient arrives in the emergency department. In areas of the country where multiple languages are spoken, the hospital may not have interpreter in all needed languages. The ability to quickly understand the patient's chief complaint and prioritize care is the objective of triaging in the emergency department. Having a tool to assist in identifying the patient's presenting symptoms in any language can have a major beneficial impact on the delivery of care, particularly in overcrowded hospitals serving diverse populations, and during times of disasters. During Phase I, we will explore the challenges of creating a decision tree to quickly identify critical information necessary for prioritizing patients. Because our system is intended to be used by patients in a foreign language, designing an intuitive interface with graphical elements and audio narratives to accommodate potential low reading and health literacy will be a challenge. If successful, our system could dramatically improve timely access to emergency service for all our limited English proficient population.
Diminishing number of emergency departments, greater utilization of emergency departments for non-emergent care, and growing diversity of language and culture have created a critical breaking point for many hospitals in our health care system. Overcrowded emergency department are struggling to provide safe, effective care for patients and they are finding it even harder to provide service to those who are unable to speak effectively in English. To reach toward the Institute of Medicine's goal to eliminate health disparities, we propose to develop a software based tool to help triage nurses provide timely medical care by better understanding each patient's presenting complaints and symptoms when those patients are unable to speak English.
