Feasibility of Natural Language Processing-Assisted Auditing of Critical Findings in Chest Radiology.
Marta E Heilbrun, Brian E Chapman, Evan Narasimhan, Neel Patel, Danielle Mowery
Journal of the American College of Radiology | Elsevier BV | Published : 2019
OBJECTIVE: Time-sensitive communication of critical imaging findings like pneumothorax or pulmonary embolism to referring physicians is essential for patient safety. The definitive communication is the radiology free-text report. Quality assurance initiatives require that institutions audit these communications, a time-intensive manual task. We propose using a rule-based natural language processing system to improve the process for auditing critical findings communications. METHODS: We present a pilot assessment of the feasibility of using an automated critical finding identification system to assist quality assurance teams' evaluation of critical findings communication compliance. Our asses..View full abstract