The COVID-19 pandemic has exacerbated existing challenges associated with diagnostic error. This study used natural language processing to identify and categorize diagnostic errors occurring during the pandemic. The study compared a review of all patient safety reports explicitly mentioning COVID-19, and using natural language processing, identified additional safety reports involving COVID-19 diagnostic errors and delays. This innovative approach may be useful for organizations wanting to identify emerging risks, including safety concerns related to COVID-19.