Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Centre for Statistics in Medicine, University of Oxford, Oxford, UK.
Department of Psychiatry, University of Oxford, Oxford, UK.
Transl Psychiatry. 2024 Jun 1;14(1):232. doi: 10.1038/s41398-024-02911-1.
The explosion and abundance of digital data could facilitate large-scale research for psychiatry and mental health. Research using so-called "real world data"-such as electronic medical/health records-can be resource-efficient, facilitate rapid hypothesis generation and testing, complement existing evidence (e.g. from trials and evidence-synthesis) and may enable a route to translate evidence into clinically effective, outcomes-driven care for patient populations that may be under-represented. However, the interpretation and processing of real-world data sources is complex because the clinically important 'signal' is often contained in both structured and unstructured (narrative or "free-text") data. Techniques for extracting meaningful information (signal) from unstructured text exist and have advanced the re-use of routinely collected clinical data, but these techniques require cautious evaluation. In this paper, we survey the opportunities, risks and progress made in the use of electronic medical record (real-world) data for psychiatric research.
数字数据的爆炸式增长和丰富性可以促进精神病学和心理健康领域的大规模研究。利用所谓的“真实世界数据”（如电子医疗/健康记录）进行研究具有资源效率高、能够快速生成和检验假设、补充现有证据（例如来自试验和证据综合）的特点，并且可能为将证据转化为针对可能代表性不足的患者群体的临床有效、以结果为导向的护理提供了一条途径。然而，由于临床重要的“信号”通常包含在结构化和非结构化（叙述性或“自由文本”）数据中，因此对真实世界数据源的解释和处理非常复杂。从非结构化文本中提取有意义信息（信号）的技术已经存在，并推进了常规收集的临床数据的再利用，但这些技术需要谨慎评估。在本文中，我们调查了在使用电子病历（真实世界）数据进行精神科研究方面的机会、风险和进展。
