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An E-triage tool developed in the US is improving detection of patients with critical outcomes and is being used in place of human assessment.

Nurses and doctors typically use the emergency severity index (ESI) during triage to assign a score from Level 1 for patients who are the most critically sick to Level 5 for patients who are the least sick. A patient鈥檚 ESI level determines in which area of the emergency department that patient will be seen, places the patient in a queue and influences provider decision-making throughout the patient鈥檚 care process.

However, the algorithm can be completely subjective, said Dr Scott Levin, PhD, Associate Professor of Emergency Medicine at the .聽鈥淣urses and physicians make a quick assessment on whether the patient can wait solely based on their clinical judgment.鈥� In most cases, researchers say patients are assigned to a Level 3 and not entirely differentiated. 鈥淲e thought that Level 3 patient group included a large mix of patients who are pretty sick and others who weren鈥檛, and our goal was to determine whether these patients could be sorted out,鈥� he said.

To help differentiate patient triage levels, Levin and a team developed an electronic triage tool. In a recently published聽paper in the聽, the E-triage tool showed equal or improved identification of patient outcomes compared to ESI based on a multisite retrospective study of nearly 173,000 emergency department visits. The study showed significant differences in patient priority levels using E-triage and ESI.

For example, out of the more than 65% of visits triaged to ESI Level 3, E-triage identified about 10%, or more than 14,000, ESI Level 3 patients who may have benefited from being up-triaged to a more critical priority level, such as Level 1 or 2. These patients were at least five times more likely to experience a critical outcome, such as death, admission to the ICU or emergency surgery, and two times more likely to be admitted to the hospital. The E-triage tool was also able to increase the number of patients down-triaged to a lower priority level, such as Level 4 or 5, to help minimise low-acuity patients from waiting and overusing scarce resources.

The E-triage tool uses an algorithm to predict patient outcomes based on a systems engineering approach and advanced machine learning methods to identify relationships between predictive data and patient outcomes. 鈥淲hen a patient comes in, and we collect the patient鈥檚 information, the E-triage tool is comparing that patient to hundreds of other like patients to make a prediction on the patient鈥檚 outcome,鈥� Levin said.

These methods are common in other industries, such as defence, transportation and finance, but rarely, if ever, are implemented in health care. 鈥淢achine-based learning takes full advantage of electronic health records and allows a precision of outcomes not previously realisable,鈥� said Dr Gabor Kelen, director of the Department of Emergency Medicine and Professor of Emergency Medicine at the Johns Hopkins University School of Medicine. 鈥淚t is the wave of future health care, although some providers may be hesitant. Decision aids that take advantage of machine learning are also highly customisable to meet the needs of an emergency department鈥檚 patient population and local healthcare delivery systems.鈥�

The E-triage tool is also designed to be a decision support tool to help clinicians make better care decisions about their patients. 鈥淭he theory behind this tool, and all clinical decision support tools, is that the tool paired with the clinician can make better predictions or better prognostics tasks like this than the tool alone or the clinician alone,鈥� Levin said.

Better differentiating patients鈥� priority levels can, in turn, help patients get the appropriate care they need. 鈥淭he ultimate objective is patients should be waiting less in the emergency department,鈥� Levin said. 鈥淔or patients at risk of having a critical care need, this technology is designed to detect them better and make sure they are seen quicker. For patients who are less sick, E-triage should detect those patients and put them on an expedited track, so they don鈥檛 need to wait as long.鈥�

E-triage is currently being used at The Johns Hopkins 黑料吃瓜群网 and Howard County General 黑料吃瓜群网, both member hospitals of Johns Hopkins Medicine. The tool is continuing to be prospectively evaluated with preliminary results that suggest improvement in detection of patients with critical outcomes and other measures relating to emergency department crowding, according to researchers.

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