The interrogation of established, large-scale datasets presents great opportunities in health data science for the linkage and mining of potentially disparate resources to create new knowledge in a fast and cost-efficient manner. The number of datasets that can be queried in the field of multimorbidity is vast, ranging from national administrative and audit datasets, large clinical, technical and biological cohorts, through to more bespoke data collections made available by individual organisations and laboratories. However, with these opportunities also come technical and regulatory challenges that require an informed approach. In this review, we outline the potential benefits of using previously collected data as a vehicle for research activity. We illustrate the added value of combining potentially disparate datasets to find answers to novel questions in the field. We focus on the legal, governance and logistical considerations required to hold and analyse data acquired from disparate sources and outline some of the solutions to these challenges. We discuss the infrastructure resources required and the essential considerations in data curation and informatics management, and briefly discuss some of the analysis approaches currently used.

对已建立的大规模数据集的询问为健康数据科学提供了巨大的机会，可以连接和挖掘潜在的不同资源，从而以快速且经济高效的方式创造新知识。在多病症领域可以查询的数据集数量巨大，从国家行政和审计数据集、大型临床、技术和生物学队列，到各个组织和实验室提供的更多定制数据集。然而，伴随这些机遇而来的还有技术和监管方面的挑战，需要采取明智的方法。在这篇综述中，我们概述了使用以前收集的数据作为研究活动工具的潜在好处。我们说明了组合潜在不同的数据集以找到该领域新问题的答案的附加值。我们专注于保存和分析从不同来源获取的数据所需的法律、治理和后勤考虑因素，并概述了应对这些挑战的一些解决方案。我们讨论了所需的基础设施资源以及数据管理和信息学管理中的基本考虑因素，并简要讨论了当前使用的一些分析方法。