سامانه همایش های دانشگاه آزاد اسلامی واحد نجف آباد

صفحه اصلی / اولین همایش بین المللی تحول خدمات سلامت: تلفیق مراقبت، درمان، بازتوانی و امیدبخشی

The Role of Artificial Intelligence in Optimizing Pharmacotherapy and Preventing Medication Errors in Clinical Settings: A Systematic Review

نویسندگان :

Amin Mahdi Majidi¹ Fatemeh Ahmadi² Mohammad Hesam Esmaili³

1- Bachelor of Nursing Student, Student Research and Technology Committee, School of Nursing and Midwifery, Bam University of Medical Sciences, 2- Bachelor of Nursing Student, Student Research and Technology Committee, School of Nursing and Midwifery, Bam University of Medical Sciences, 3- Bachelor of Nursing Student, Student Research and Technology Committee, School of Nursing and Midwifery, Bam University of Medical Sciences,

کلمات کلیدی :

Artificial intelligence،Clinical decision support،Machine learning،Medication errors،Medication safety،; Pharmacotherapy

چکیده :

Abstract Background: Medication errors and adverse drug events are major challenges to patient safety. The complexity of medication regimens and increasing clinical data make the identification and prevention of medication-related risks difficult. Artificial intelligence (AI) and machine learning can analyze health data and support clinical decision-making, potentially improving medication safety. This study aimed to examine the role of AI in optimizing pharmacotherapy and preventing medication errors. Methods: This systematic review was conducted according to the PRISMA framework. PubMed, Scopus, Web of Science, Embase, and Cochrane Library were searched for studies published between 2020 and 2025. Studies investigating AI or machine learning for predicting adverse drug events, identifying medication errors, or supporting medication-related decision-making were included. Data on technology type, clinical applications, and safety outcomes were extracted and descriptively analyzed. Results: The evidence indicated that machine learning methods have considerable potential for predicting adverse drug events. One systematic review and meta-analysis evaluated 59 studies and reported promising model performance. In addition, a review of AI applications for optimizing medication alerts identified 10 studies and reported improved detection of inappropriate prescriptions and reduced alert burden. Conclusion: AI can serve as a complementary tool for improving medication safety, reducing medication errors, and supporting clinical decision-making. Prospective and multicenter studies are needed to evaluate its effectiveness in real-world clinical settings..