Department of Neuroscience, Central Clinical School, Faculty of Medicine, Nursing and Health Science, Monash University, Melbourne, VIC, Australia.
Department of Neurology, Alfred Hospital, Melbourne, VIC, Australia.
Eye (Lond). 2024 Aug;38(12):2448-2456. doi: 10.1038/s41433-024-03160-8. Epub 2024 Jun 6.
Real-world data (RWD) can be defined as all data generated during routine clinical care. This includes electronic health records, disease-specific registries, imaging databanks, and data linkage to administrative databases. In the field of neuro-ophthalmology, the intersection of RWD and clinical practice offers unprecedented opportunities to understand and treat rare diseases. However, translating RWD into real-world evidence (RWE) poses several challenges, including data quality, legal and ethical considerations, and sustainability of data sources. This review explores existing RWD sources in neuro-ophthalmology, such as patient registries and electronic health records, and discusses the challenges of data collection and standardisation. We focus on research questions that need to be answered in neuro-ophthalmology and provide an update on RWE generated from various RWD sources. We review and propose solutions to some of the key barriers that can limit translation of a collection of data into impactful clinical evidence. Careful data selection, management, analysis, and interpretation are critical to generate meaningful conclusions.
真实世界数据（RWD）可定义为在常规临床护理过程中生成的所有数据。这包括电子健康记录、特定疾病的登记处、成像数据库以及与行政数据库的数据链接。在神经眼科学领域，RWD 与临床实践的交叉为理解和治疗罕见疾病提供了前所未有的机会。然而，将 RWD 转化为真实世界证据（RWE）面临着一些挑战，包括数据质量、法律和伦理考虑以及数据源的可持续性。本综述探讨了神经眼科学中现有的 RWD 来源，如患者登记处和电子健康记录，并讨论了数据收集和标准化的挑战。我们重点关注神经眼科学中需要回答的研究问题，并提供了来自各种 RWD 来源生成的 RWE 的最新信息。我们审查并提出了解决一些可能限制将数据集合转化为有影响力的临床证据的关键障碍的方法。仔细的数据选择、管理、分析和解释对于得出有意义的结论至关重要。
