Biomedical Standards and Open Health Data

Abstract

Recent movements such as open data, crowdhealth, participatory surveillance, quantified self, or individuals becoming “data donors” have the potential to generate new findings about diseases, to improve diagnostics and deliver healthcare and treatment. This chapter provides insights into the topic of open data concerning healthcare. Examples will be given on open health data that are available. Analysis of open health data can help to identify causes of diseases, effects of treatments, or even correlations between environmental factors and disease progression. However, there are also major concerns on privacy, confidentiality and control of data about individuals once data become open. These concerns will be highlighted. Ensuring usefulness of open health data requires high data quality, enrichment with metadata and the development of standards and best practices to guide the way data are presented and organized. This ensures that data are not only accessible, but also readable, comprehensible and utilizable by various users and algorithms. Biomedical standards, classification systems, and ontologies as well as communication protocols for health data have already been available for clinical practice for years and should be considered when opening health data. We will provide an overview on relevant biomedical standards to guide toward standardized representations in the context of open health data.