1. What is meant by big data in health?

Big data in health have often been defined with reference to the “three Vs” of data: volume (a large amount of data), variety (different types of data), and velocity (data arriving at high speed). However, the notion of big data goes beyond the characteristics of data itself and includes how data are used, as is captured in the following definition from a recent European Commission funded study:
“Big Data in Health refers to largely routinely or automatically collected datasets, which are electronically captured and stored. It is reusable in the sense of multipurpose data and compromises the fusion and connection of existing databases for the purpose of improving health and health system performance. It does not refer to data collected for a specific study.”
(European Commission, Study on Big Data in Public Health, Telemedicine and Healthcare. 2016.)


2. How is big data in healthcare collected and analysed?

Health care systems routinely collect large amounts of data as patients use various health care services. For example, information on the fact that a patient has visited the GP, as well as medicines prescribed would be included in the patient’s record. This information is required to provide the patient with optimal care, but also plays an important role in ensuring health care providers are reimbursed for their services. Beyond the “one-dimensional” collection of data, computer programs help to combine and enrich data from different sources, thus generating an added value compared to the originally isolated datasets.
In broader terms, the analytic methods applied are to support all stages of the health technology life cycle from basic research (such as genomics, proteomics and metabolomics data)) to reimbursement decisions (such as economic modelling methods) and subgroup identification (such as imaging data).


3. Who can use big data in healthcare and how?

The better use of healthcare data is expected to make healthcare systems more efficient, accessible and resilient, and can also contribute to research and development, as well as policy making. Big data can be used especially by healthcare services, the academia, policy makers, and the industry. A few examples on the use of big data in healthcare are the following:
• achieving better health outcomes
• improving the effectiveness of treatments and increase patient safety
• monitoring healthcare services
• detection of population-level effects
• more efficient recruitment and selection of patients for clinical trial


4. What are the benefits of utilising big data for patients?

Big data has been attributed as having “transformative potential” in healthcare systems, with benefits across the entire pathway of care delivery for all stakeholders. Linkage of previously separated data sets and their analysis using appropriate “big data” analytics offer new ways to accelerate research and to identify the right treatment for individual patients. Access to large data sets gives a more comprehensive picture of patients, allows patient-related outcomes to be measured more accurately, and supports decision-makers in shaping healthcare systems.


5. What are health outcomes?

According to an explanation given by the International Consortium for Outcomes Measurement in 2016:
“Outcomes are the results of treatment that patients care about most. Outcomes are not ‘outputs’; they are not lab results; they are not technical details. They’re real-world results, like physical functioning or level of pain or Quality of Life”.


6. Why is value-based and outcomes-focused healthcare important?

One of the primary goals of healthcare is improving the overall health of the population. Efficiently allocating funds for purchasing care is a key factor, and it is crucial that scarce resources are spent wisely on interventions that offer the most benefits to patients, that is, better outcomes. Therefore, a value-based approach to healthcare would ensure that the health system receives the greatest benefit from investment of public funds when deciding between alternatives for health interventions.


7. What is the Big Data for Better Outcomes Programme (BD4BO)? Where is its place within IMI?

Big Data for Better Outcomes (BD4BO) is part of the public-private Innovative Medicines Initiative 2 (IMI-2). BD4BO is a research programme aiming to promote the development of value-based and outcomes-focused healthcare systems in Europe through the use of big data. The Programme consists of research in disease-specific areas. Projects in Alzheimer’s disease, haematological malignancies and heart diseases are already ongoing and new projects in more disease areas are already being set up. These projects will lead the way in using real world evidence to complement evidence obtained from clinical trials. Real world evidence means using sources such as registries and electronic health records but potentially also more novel sources of data such as from wearable technology like fit bits or smart phones.


8. What are the goal and objectives of the BD4BO Programme?

The goal of BD4BO, as defined by the Innovative Medicines Initiative 2 (IMI2) funding the programme, is to “support the evolution towards patient outcomes focused and sustainable healthcare systems, exploiting the opportunities offered by large data sets from variable sources”.
Its overall objective is to maximise the potential of big data in European healthcare, and to promote innovative methods for harmonising, accessing, and analysing data.
Eventually, BD4BO and its projects should be the “go-to” source for pan-European outcomes data and a trusted partner for patients, researchers, healthcare professionals, and decision-makers alike.


9. Which projects does the BD4BO Programme consist of? What future topics are considered?

The BD4BO Programme is composed of several projects including projects in disease specific areas as listed below. These disease specific projects are supported by the Big Data for Better Outcomes, Policy Innovation and Healthcare Systems Transformation (DO->IT) Consortium, and the European Health Data Network (EHDN) project which will be a federated network of relevant and high quality data sources.

The disease-specific projects are:

ROADMAP – Real World Outcomes Across the Spectrum for Better Care
The project aims to create the conditions for an open collaboration among stakeholders that yields consensual and efficient uses of Real World Evidence for the benefit of Alzheimer’s Disease patients and their caregivers. (www.roadmap-alzheimer.org)

HARMONY – Healthcare Alliance for Resourceful Medicines Offensive against Neoplasm in Hematology
The Big Data platform developed by HARMONY, a European Network of Excellence for Big Data in hematology, is aimed at accelerating access to novel therapies and improving outcomes of patients with haematological malignancies. (www.harmony-alliance.eu)

BigData@Heart – Big Data for Better Hearts
BigData@Heart’s goal is to develop a Big Data-driven translational research platform of unparalleled scale and phenotypic resolution to deliver clinically relevant disease phenotypes, scalable insights from real-world evidence and insights driving drug development and personalised medicine through advanced analytics. (www.bigdata-heart.eu)

PROSTATE CANCER – upcoming project to be launched in 2018.

MULTI-MORBID PATIENTS – TBC


10. How can patient data contribute to the improvements, and what will be the benefit for patients?

Active participation of patients is needed to achieve the ambitious objective of the BD4BO Programme: to develop an approach within existing data systems to efficiently enable initiation, maintenance, and evaluation of the right treatment to the right patient at the right time in health care systems.
The Programme plans to unlock a wealth of patient reported outcome measures based on digital data mining with the aim of developing preventative and personalised approaches to care for the benefit of patients.


11. How is patient data protected in the BD4BO project?

The Programme will provide a structure for empowering patients as data owners and partners in research. Recognising the ultimate right of patients to their personal data, inclusive the right to be forgotten, it will ensure that the informed consent templates and data privacy standards strike a balance between protecting individual privacy and promoting innovation. A toolkit will be developed that includes best practices and training materials for collaborating with patients, and informing them about data privacy in research.


12. How can I find information on the implementation of the BD4BO Programme?

The outcomes and results of the Programme, as well as relevant news, information on conferences and other events, our newsletters, publications and press releases will be communicated on our website: bd4bo.eu

 

Home