The diversity of diseases in rheumatology and variability in disease prevalence necessitates greater data parity in disease presentation, treatment responses including adverse events to drugs and various comorbidities. Randomized controlled trials are the gold standard for drug development and performance evaluation. However, when the drug is applied outside the controlled environment, the outcomes may differ in patient populations. In this context, the need to understand the macro and micro changes involved in disease evolution and progression becomes important and so is the need for harvesting and harnessing the real-world data from various resources to use them in generating real-world evidence. Digital tools with potential relevance to rheumatology can potentially be leveraged to obtain greater patient insights, greater information on disease progression and disease micro processes and even in the early diagnosis of diseases. Since the patients spend only a minuscule portion of their time in hospital or in a clinic, using modern digital tools to generate realistic, bias-proof, real-world data in a non-invasive patient-friendly manner becomes critical. In this review we have appraised different digital mediums and mechanisms for collecting real-world data and proposed digital care models for generating real-world evidence in rheumatology.

中文翻译：

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使用数字工具利用真实世界数据和真实世界证据：风湿病实践中的实用模型和潜在模型

风湿病疾病的多样性和疾病患病率的可变性需要在疾病表现、治疗反应（包括药物不良事件和各种合并症）方面进行更大的数据均等性。随机对照试验是药物开发和性能评估的黄金标准。然而，当药物在受控环境之外应用时，患者群体的结果可能会有所不同。在这种情况下，了解疾病演变和进展所涉及的宏观和微观变化的需求变得很重要，因此需要从各种资源中收集和利用真实世界的数据以使用它们来生成真实世界的证据。可以利用与风湿病学潜在相关的数字工具来获得更深入的患者见解，更多关于疾病进展和疾病微过程的信息，甚至在疾病的早期诊断中。由于患者只在医院或诊所度过极少部分时间，因此使用现代数字工具以对患者友好的非侵入性方式生成真实、无偏见的真实数据变得至关重要。在这篇综述中，我们评估了用于收集真实世界数据的不同数字媒体和机制，并提出了用于在风湿病学中生成真实世界证据的数字护理模型。