Babel Aditi, Taneja Richi, Mondello Malvestiti Franco, Monaco Alessandro, Donde Shaantanu
Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom.
Medical Product Evaluation, Pfizer Ltd, Mumbai, India.
Front Digit Health. 2021 Jun 29;3:669869. doi: 10.3389/fdgth.2021.669869. eCollection 2021.
Artificial intelligence (AI) tools are increasingly being used within healthcare for various purposes, including helping patients to adhere to drug regimens. The aim of this narrative review was to describe: (1) studies on AI tools that can be used to measure and increase medication adherence in patients with non-communicable diseases (NCDs); (2) the benefits of using AI for these purposes; (3) challenges of the use of AI in healthcare; and (4) priorities for future research. We discuss the current AI technologies, including mobile phone applications, reminder systems, tools for patient empowerment, instruments that can be used in integrated care, and machine learning. The use of AI may be key to understanding the complex interplay of factors that underly medication non-adherence in NCD patients. AI-assisted interventions aiming to improve communication between patients and physicians, monitor drug consumption, empower patients, and ultimately, increase adherence levels may lead to better clinical outcomes and increase the quality of life of NCD patients. However, the use of AI in healthcare is challenged by numerous factors; the characteristics of users can impact the effectiveness of an AI tool, which may lead to further inequalities in healthcare, and there may be concerns that it could depersonalize medicine. The success and widespread use of AI technologies will depend on data storage capacity, processing power, and other infrastructure capacities within healthcare systems. Research is needed to evaluate the effectiveness of AI solutions in different patient groups and establish the barriers to widespread adoption, especially in light of the COVID-19 pandemic, which has led to a rapid increase in the use and development of digital health technologies.
人工智能（AI）工具在医疗保健领域正越来越多地被用于各种目的，包括帮助患者坚持药物治疗方案。本叙述性综述的目的是描述：（1）关于可用于测量和提高非传染性疾病（NCD）患者药物依从性的人工智能工具的研究；（2）为此目的使用人工智能的好处；（3）在医疗保健中使用人工智能的挑战；以及（4）未来研究的重点。我们讨论了当前的人工智能技术，包括手机应用程序、提醒系统、增强患者能力的工具、可用于综合护理的仪器以及机器学习。使用人工智能可能是理解非传染性疾病患者药物不依从背后复杂因素相互作用的关键。旨在改善患者与医生之间的沟通、监测药物消费、增强患者能力并最终提高依从性水平的人工智能辅助干预措施可能会带来更好的临床结果，并提高非传染性疾病患者的生活质量。然而，在医疗保健中使用人工智能受到众多因素的挑战；用户的特征可能会影响人工智能工具的有效性，这可能会导致医疗保健领域进一步的不平等，并且可能有人担心它会使医疗失去人性化。人工智能技术的成功和广泛应用将取决于医疗保健系统内的数据存储能力、处理能力和其他基础设施能力。需要进行研究以评估人工智能解决方案在不同患者群体中的有效性，并确定广泛采用的障碍，特别是鉴于新冠疫情导致数字健康技术的使用和发展迅速增加。
