Background: Shoulder injury related to vaccine administration (SIRVA) accounts for more than half of all claims received by the National Vaccine Injury Compensation Program. However, due to the difficulty of finding SIRVA cases in large health care databases, population-based studies are scarce.
Objective: The goal of the research was to develop a natural language processing (NLP) method to identify SIRVA cases from clinical notes.