Verman Snehil, Anjankar Ashish
Department of Community Medicine, Jawaharlal Nehru Medical College, Datta Meghe Institute of Medical Sciences, Wardha, IND.
Department of Biochemistry, Jawaharlal Nehru Medical College, Datta Meghe Institute of Medical Sciences, Wardha, IND.
Cureus. 2022 Sep 14;14(9):e29162. doi: 10.7759/cureus.29162. eCollection 2022 Sep.
An adverse event is any abnormal clinical finding associated with the use of a therapy. Adverse events are classified by reporting an event's seriousness, expectedness, and relatedness. Monitoring patient safety is of utmost importance as more and more data becomes available. In reality, very low numbers of adverse events are reported via the official path. Chart review, voluntary reporting, computerized surveillance, and direct observation can detect adverse drug events. Medication errors are commonly seen in hospitals and need provider and system-based interventions to prevent them. The need of the hour in India is to develop and implement medication safety best practices to avoid adverse events. The utility of artificial intelligence techniques in adverse event detection remains unexplored, and their accuracy and precision need to be studied in a controlled setting. There is a need to develop predictive models to assess the likelihood of adverse reactions while testing novel pharmaceutical drugs.
不良事件是指与某种治疗方法的使用相关的任何异常临床发现。不良事件通过报告事件的严重程度、预期性和相关性进行分类。随着越来越多的数据可用，监测患者安全至关重要。实际上，通过官方途径报告的不良事件数量非常少。病历审查、自愿报告、计算机化监测和直接观察可以检测到药物不良事件。用药错误在医院中很常见，需要基于医疗服务提供者和系统的干预措施来预防。印度当前需要制定和实施药物安全最佳实践以避免不良事件。人工智能技术在不良事件检测中的效用仍未得到探索，需要在可控环境中研究其准确性和精确性。在测试新型药物时，有必要开发预测模型来评估不良反应的可能性。
