Big Data for Public Health Policy-Making: Policy Empowerment

L. Mählmann*, M. Reumann, N. Evangelatos, A. Brand

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


Digitization is considered to radically transform healthcare. As such, with seemingly unlimited opportunities to collect data, it will play an important role in the public health policymaking process. In this context, health data cooperatives (HDC) are a key component and core element for public health policy-making and for exploiting the potential of all the existing and rapidly emerging data sources. Being able to leverage all the data requires overcoming the computational, algorithmic, and technological challenges that characterize today's highly heterogeneous data landscape, as well as a host of diverse regulatory, normative, governance, and policy constraints. The full potential of big data can only be realized if data are being made accessible and shared. Treating research data as a public good, creating HDC to empower citizens through citizen-owned health data, and allowing data access for research and the development of new diagnostics, therapies, and public health policies will yield the transformative impact of digital health. The HDC model for data governance is an arrangement, based on moral codes, that encourages citizens to participate in the improvement of their own health. This then enables public health institutions and policymakers to monitor policy changes and evaluate their impact and risk on a population level. (c) 2018 S. Karger AG, Basel

Original languageEnglish
Pages (from-to)312-320
Number of pages9
JournalPublic Health Genomics
Issue number6
Publication statusPublished - 2017

JEL classifications

  • i18 - "Health: Government Policy; Regulation; Public Health"
  • i19 - Health: Other
  • c80 - "Data Collection and Data Estimation Methodology; Computer Programs: General"
  • c81 - "Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access"


  • Big data analytics
  • Cross-border healthcare
  • Data linkage
  • E-health
  • Ethical and regulatory frameworks
  • Health data cooperatives
  • Prevention
  • Public health policies
  • Secondary use of data
  • CARE

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