Chair and Department of Pharmaceutical Technology, Poznań University of Medical Sciences, Poznań, Poland.
Department of Biopharmacy, Medical University of Łódź, Łódź, Poland.
Med Sci Monit. 2024 Jul 16;30:e944605. doi: 10.12659/MSM.944605.
Medication non-adherence is a problem that affects up to 50% of patients with chronic diseases. The result is a failure to achieve therapeutic goals and an increased burden on the healthcare system. It is, therefore, highly appropriate to develop models to assess patient adherence to prescribed therapy. To date, there are many methods for doing this. However, several tools have been developed that subjectively or objectively, directly or indirectly, assess the level of patient adherence. Electronic medication packaging devices are among the most rapidly evolving methods of measuring adherence. Other emerging technologies include the use of artificial intelligence algorithms and ingestible biosensors. The former is being used to create applications for mobile phones and laptops. The latter appears to be the least susceptible to the risk of overestimating adherence but remains very expensive. Here, we present recent developments in measuring patient adherence, and provide details of achievements in objective methods for assessing adherence, such as electronic monitoring devices, video-observed therapy, and ingestible biosensors. A dedicated section on using artificial intelligence and machine learning in adherence measurement and reviewing questionnaires and scales used in specific diseases is also included. Methods are discussed along with their advantages and potential limitations. This article aimed to review current measures and future initiatives to improve patient medication adherence.
药物依从性差是影响高达 50%慢性病患者的一个问题。其结果是无法实现治疗目标,增加了医疗系统的负担。因此,开发评估患者对规定治疗依从性的模型是非常合适的。迄今为止,有许多这样做的方法。然而,已经开发出了几种工具,它们可以主观或客观、直接或间接地评估患者依从性的水平。电子药物包装设备是衡量依从性的最快速发展的方法之一。其他新兴技术包括使用人工智能算法和可摄入生物传感器。前者用于为手机和笔记本电脑创建应用程序。后者似乎最不容易高估依从性的风险,但仍然非常昂贵。在这里,我们介绍了测量患者依从性的最新进展,并详细介绍了电子监测设备、视频观察治疗和可摄入生物传感器等评估依从性的客观方法的成就。还专门讨论了在依从性测量中使用人工智能和机器学习以及审查特定疾病中使用的问卷和量表的问题。本文讨论了这些方法的优缺点和潜在局限性。这篇文章旨在回顾当前的措施和未来的举措,以提高患者的药物依从性。