Adams KT, Pruitt Z, Kazi S, et al. J Patient Saf. 2021;17:e988-e994.
It is important to consider unintended consequences when implementing new tools, such as health information technology (HIT). This study reviewed 2,700 patient safety event reports to identify the type of medication error, the stage in the process in which the error occurred, and how HIT usability issues contributed to the errors. Errors in dosing were the most frequent type, and occurred during ordering or reviewing. Most errors described usability issues which should be considered and addressed to improve medication safety.
Choudhury A, Asan O. JMIR Med Inform. 2020;8:e18599.
This systematic review explored how artificial intelligence (AI) based on machine learning algorithms and natural language processing is used to address and report patient safety outcomes. The review suggests that AI-enabled decision support systems can improve error detection, patient stratification, and drug management, but that additional evidence is needed to understand how well AI can predict safety outcomes.
Scott IA, Pillans PI, Barras M, et al. Ther Adv Drug Saf. 2018;9:559-573.
The prescribing of potentially inappropriate medications is a quality and safety concern. This narrative review found that information technologies equipped with decision support tools were modestly effective in reducing inappropriate prescribing of medications, more so in the hospital than the ambulatory environment.
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