title: The rise of big clinical databases.
abstract: BACKGROUND
  The routine collection of large amounts of clinical data, 'big data', is becoming more common, as are research studies that make use of these data source. The aim of this paper is to provide an overview of the uses of data from large multi-institution clinical databases for research.
  
  
  METHODS
  This article considers the potential benefits, the types of data source, and the use to which the data is put. Additionally, the main challenges associated with using these data sources for research purposes are considered.
  
  
  RESULTS
  Common uses of the data include: providing population characteristics; identifying risk factors and developing prediction (diagnostic or prognostic) models; observational studies comparing different interventions; exploring variation between healthcare providers; and as a supplementary source of data for another study. The main advantages of using such big data sources are their comprehensive nature, the relatively large number of patients they comprise, and the ability to compare healthcare providers. The main challenges are demonstrating data quality and confidently applying a causal interpretation to the study findings.
  
  
  CONCLUSIONS
  Large clinical database research studies are becoming ubiquitous and offer a number of potential benefits. However, the limitations of such data sources must not be overlooked; each research study needs to be considered carefully in its own right, together with the justification for using the data for that specific purpose.
authors: Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Botnar Research Centre, Nuffield Orthopaedic Centre, Windmill Road, Oxford OX3 7LD, UK.
authors: J A
authors: JA
authors: Cook
authors: G S
authors: GS
authors: Collins
mesh_terms: D035843:Biomedical Research / Q000379:methods; D003625:Data Collection / Q000379:methods; D003627:Data Interpretation, Statistical; D016208:Databases, Factual / Q000592:standards / Q000706:statistics & numerical data*; D003695:Delivery of Health Care / Q000592:standards; D006801:Humans; D033181:Information Dissemination / Q000379:methods; D064887:Observational Studies as Topic / Q000379:methods; D063868:Patient Outcome Assessment; D012107:Research Design; D018570:Risk Assessment / Q000379:methods