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Big Data for Better Outcomes (BD4BO)

Principal Investigator: Elias Mossialos
Researchers: Huseyin Naci, Beth Kreling, Max Salcher, Caroline Carney, Sahan Jayawardana
Start Date: 01 February 2017
End Date: 31 January 2019
Region: Europe
Keywords: big data; health care systems; value-based health care; outcomes research, health policy, health economics

The LSE Health-led "Big Data for Better Outcomes, Policy Innovation, and Healthcare Systems Transformation" (DO-IT) consortium coordinates the BD4BO programme, identifying and addressing opportunities for data-driven health care system transformation based on input from a wide range of stakeholders.

Big Data for Better Outcomes (BD4BO) is a major research programme launched by the Innovative Medicine Initiative 2 (IMI2) to facilitate the use of "big data" to enable the transition towards value-based, outcomes-focused health care systems in Europe. The LSE Health-led "Big Data for Better Outcomes, Policy Innovation, and Healthcare Systems Transformation" (DO-IT) consortium coordinates the BD4BO programme, identifying and addressing opportunities for data-driven health care system transformation based on input from a wide range of stakeholders. DO-IT shapes the BD4BO programme strategy and provides the programme’s disease specific projects (Alzheimer’s Disease, haematological malignancies, cardiovascular diseases, prostate cancer and future topics) with support on methodological questions and policy-relevant translation of knowledge and insights generated by the programme.

DO-IT acts as the BD4BO coordination platform (Coordination and Support Action), realising synergies across disease specific projects and maximising impact on European healthcare systems. More specifically, DO-IT aims to:

  • act as a knowledge broker by aggregating learnings and disseminating findings from BD4BO projects;
  • provide BD4BO projects with support on methods for selecting and measuring outcomes in real world settings;
  • develop minimum data privacy standards for the collection, use, storage and transfer of clinical and biological data;
  • engage with key stakeholders to understand value and limitations of data-driven approaches for value-based health care, and to ensure real world impact for the BD4BO programme;
  • recommend areas for future collaborative research to address gaps in standards, methodologies, tools, and available data required for a meaningful impact of big data on European healthcare systems.

LSE Health coordinates 35 organisations in the public-private DO-IT consortium with a total budget of 7.2 million Euros. As the leading academic partner, LSE Health plays a prominent role in developing the programme strategy. LSE researchers are working to provide methodological guidance on collection and analysis of real world data to ensure quality and consistency of individual projects, in line with the BD4BO programme objective. The methodological research focus is highly policy focussed: robust methodological criteria need to be identified if routinely collected data are to be used to promote high-value health care. Questions around the selection of relevant outcomes in different disease areas, their measurement, and the analysis of observational data as foundation for decision-making need to be considered carefully to realise the potential of big data in health care. LSE Health will contribute to the development of a "roadmap" that charts the methodological steps required from identification and measurement of meaningful outcomes to their use in value-based health care systems.

Consortium Members

London School of Economics and Political Science (Project Coordinator), Novartis (Project Lead), National Institute for Health and Care Excellence, Swedish Dental and Pharmaceutical Benefits Agency, European Cancer Patient Coalition, European Multiple Sclerosis Platform, Semmelweis University, Imperial College London, Swedish Institute for Health Economics, Centre for Research in Healthcare Management at Università Bocconi, Norwegian Institute of Public Health, Norwegian Medicines Agency, Technology, Methods and Infrastructure for Networked Medical Research (TMF), Inserm Toulouse, The Association of the British Pharmaceutical Industry, Amgen, Bayer, Boehringer Ingelheim, Celgene, European Federation of Pharmaceutical Industries and Associations (EFPIA), Farmaindustria, GlaxoSmithKline, Health iQ, InterSystems, Janssen Pharmaceutica, Eli Lilly and Company, Merck Group, MSD Sharp & Dohme, Novo Nordisk, Pfizer, Roche, Sanofi, Servier, UCB, Association of Research-Based Pharmaceutical Companies (VfA).

Outputs

Outcomes Selection

Collecting the same outcomes across a range of sources has many advantages including enabling the pooling of outcome data across a wider population.
DO-IT looked at how to identify, select and measure core outcomes sets, focusing on how we create transparency in how outcomes are selected and involving a wide range perspectives including patient representatives so that outcomes are meaningful for all stakeholders.

  • BD4BOToolkit
  • Webinar on outcomes selection

Enabling effective big data use

Overview: an overall aim of the BD4BO project is to facilitate the wider use of big data and real world data. Realising the potential of big data and real world data requires the correct tools for credible and acceptable evidence and conditions that enable data sharing. DO-IT has engaged with HTA bodies to understand their perspective on real work evidence and has produced a review of econometric methods for real world data analysis and undertake a case study review of core outcome sets with consideration of their availability in real world data.

  • Cost Studies
  • Methods Review

Knowledge Management

Overview: DO-IT as the CSA serves to support and amplify the work of the range of DSPs sitting under the BD4BO banner. The project has increased the visibility and ease of access to BD4BO outputs by creating a central portal for accessing outputs produced across the programme. Outputs from BD4BO projects cross a range of disease areas but share similarities in the methodological, data and privacy issues, the BD4BO Knowledge Hub enables BD4BO projects and other parties in big data analysis to learn from each other's work.

Data privacy

Overview: ensuring consent, confidentiality and patient privacy is protected is a prerequisite for building trust in big data and real world evidence. Sharing data across different legal systems is a challenge for big data research. DO-IT has produced an informed consent form and other outputs to encourage data sharing with the potection of privacy.

  • Empirical investigation ofcurrent informed consent practices
  • Review of patientperspectives on RWE

Advocacy and engagement

Overview: Something on advocating the use of big data and creating spaces for engagement and collaboration

Outreach events

  1. UK outreach event
  2. TLV outreach discussion in Jan 2017
  3. Germany outreach activities
  4. Spain outreach activities
  5. DIA Europe conference
  6. Eyeforpharma conference
  7. BD4BO Symposium
  8. Nordic Conference on RWE
  9. CEE Webinar
  10. TLV Webinar on acceptability of evidence
  11. Brussels GA outreach event on AI/future of big data

Future challenges and opportunities for big data

Overview: Big data research involves new challenges beyond those of traditional research projects. There is also great potential for the use of big data and real world evidence, DO-IT have produced a road map outlining the challenges and opportunities for big data and a review of unmet big data needs.

For more information, see the BD4BO website.