Quality, Accuracy, and Bias in ChatGPT-Based Summarization of Medical Abstracts.

Purpose: Worldwide clinical knowledge is expanding rapidly, but physicians have sparse time to review scientific literature. Large language models (eg, Chat Generative Pretrained Transformer [ChatGPT]), might help summarize and prioritize research articles to review. However, large language models sometimes "hallucinate" incorrect information.

Assessing the Immunization Information System and electronic health record interface accuracy for COVID-19 vaccinations.

Objective: Our objective is to assess the accuracy of the COVID-19 vaccination status within the electronic health record (EHR) for a panel of patients in a primary care practice when manual queries of the state immunization databases are required to access outside immunization records.

Materials And Methods: This study evaluated COVID-19 vaccination status of adult primary care patients within a university-based health system EHR by manually querying the Kansas and Missouri Immunization Information Systems.

Results: A manual query of the local Immunization Information Systems for 4114 adult patients with "unknown" vaccination status showed 44% of the patients were previously vaccinated.