Automated Translation of Clinical Parameters in Evaluating Acute Radiation Injury: Results From a Mass Casualty Exercise.

OBJECTIVE: A radiological disaster could result in a large number of patients potentially exposed to harmful levels of radiation. Currently, early triage of patients for radiation exposure relies heavily on a clinical evaluation of signs and symptoms. However, detailed clinical assessment takes significant time and requires specialized training to accurately interpret the results.

METHODS: During planning of a recent exercise, SMEs estimated that it would take up to 15 minutes per patient. Patient load would quickly overwhelm the number of qualified clinicians providing treatment. In this exercise organized by the NATO RTG HFM 222, we examined using automated translation of clinical data to facilitate clinic evaluations. We used two triage evaluation approaches; REAC/TS and METREPOL. These approaches allowed us to translate tabulated clinical data, first into categorical data for grouping patients, and then into recommendations for follow-up diagnostics and care.

RESULTS: The organizers provided clinical evaluations of 191 case studies that were estimated to require up to 50 total hours for completion. However, using our application, we were able to evaluate all cases in less than 2 minutes.

CONCLUSION: This study clearly demonstrates the need for automated tools to help translate clinical data for effective patient triage after a nuclear or radiological incident. (Disaster Med Public Health Preparedness. 2018;12:569-573).