Department of Psychiatry, University of Oxford, Oxford, UK
Oxford Health NHS Foundation Trust, Oxford, UK.
Evid Based Ment Health. 2020 Feb;23(1):39-44. doi: 10.1136/ebmental-2019-300140.
Over the last decade dramatic advances have been made in both the technology and data available to better understand the multifactorial influences on child and adolescent health and development. This paper seeks to clarify methods that can be used to link information from health, education, social care and research datasets. Linking these different types of data can facilitate epidemiological research that investigates mental health from the population to the patient; enabling advanced analytics to better identify, conceptualise and address child and adolescent needs. The majority of adolescent mental health research is not able to maximise the full potential of data linkage, primarily due to four key challenges: confidentiality, sampling, matching and scalability. By presenting five existing and proposed models for linking adolescent data in relation to these challenges, this paper aims to facilitate the clinical benefits that will be derived from effective integration of available data in understanding, preventing and treating mental disorders.
在过去的十年中，在技术和数据方面都取得了巨大的进展，这些技术和数据有助于更好地理解影响儿童和青少年健康和发展的多种因素。本文旨在阐明可用于链接健康、教育、社会关怀和研究数据集信息的方法。链接这些不同类型的数据可以促进从人群到患者的心理健康的流行病学研究，使高级分析能够更好地识别、概念化和满足儿童和青少年的需求。大多数青少年心理健康研究都无法充分发挥数据链接的全部潜力，主要是由于四个关键挑战：保密性、抽样、匹配和可扩展性。本文通过介绍五个现有的和拟议的模型，以解决这些挑战来链接青少年数据，旨在促进将现有数据有效整合到理解、预防和治疗精神障碍中所带来的临床效益。
