Center of Clinical Neuroscience, Department of Neurology, Faculty of Medicine and University Hospital Carl Gustav Carus, TU Dresden, Dresden, Germany.
Center of Clinical Neuroscience, Department of Neurology, Faculty of Medicine and University Hospital Carl Gustav Carus, TU Dresden, Dresden, Germany.
Autoimmun Rev. 2023 Aug;22(8):103358. doi: 10.1016/j.autrev.2023.103358. Epub 2023 May 12.
Multiple sclerosis (MS) has a longitudinal and heterogeneous course, with an increasing number of therapy options and associated risk profiles, leading to a constant increase in the number of parameters to be monitored. Even though important clinical and subclinical data are being generated, treating neurologists may not always be able to use them adequately for MS management. In contrast to the monitoring of other diseases in different medical fields, no target-based approach for a standardized monitoring in MS has been established yet. Therefore, there is an urgent need for a standardized and structured monitoring as part of MS management that is adaptive, individualized, agile, and multimodal-integrative. We discuss the development of an MS monitoring matrix which can help facilitate data collection over time from different dimensions and perspectives to optimize the treatment of people with MS (pwMS). In doing so, we show how different measurement tools can combined to enhance MS treatment. We propose to apply the concept of patient pathways to disease and intervention monitoring, not losing track of their interrelation. We also discuss the use of artificial intelligence (AI) to improve the quality of processes, outcomes, and patient safety, as well as personalized and patient-centered care. Patient pathways allow us to track the patient's journey over time and can always change (e.g., when there is a switch in therapy). They therefore may assist us in the continuous improvement of monitoring in an iterative process. Improving the monitoring process means improving the care of pwMS.
多发性硬化症（MS）具有纵向和异质性的病程，治疗选择和相关风险概况不断增加，导致需要监测的参数数量不断增加。尽管正在产生重要的临床和亚临床数据，但治疗神经科医生可能并不总是能够充分利用这些数据来管理 MS。与其他医学领域监测其他疾病不同，尚未为 MS 建立基于目标的标准化监测方法。因此，迫切需要一种标准化和结构化的监测方法，作为 MS 管理的一部分，这种监测方法具有适应性、个体化、灵活性和多模式综合的特点。我们讨论了开发 MS 监测矩阵的问题，该矩阵可以帮助从不同维度和角度随时间收集数据，从而优化多发性硬化症患者的治疗。在这样做的过程中，我们展示了如何将不同的测量工具结合起来，以增强多发性硬化症的治疗效果。我们建议将患者路径的概念应用于疾病和干预监测，而不会忽略它们之间的相互关系。我们还讨论了使用人工智能（AI）来提高流程、结果和患者安全的质量，以及个性化和以患者为中心的护理。患者路径使我们能够随着时间的推移跟踪患者的治疗过程，并且可以随时改变（例如，当治疗发生变化时）。因此，它们可以帮助我们在迭代过程中不断改进监测。改进监测过程意味着改善多发性硬化症患者的护理。
