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 (personalized medicine). 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.

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The opportunities offered by Big Data will only materialize when healthcare systems move beyond the mere collection of large amounts of data. 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 that paint a more comprehensive picture of patients allows patient-relevant outcomes to be measured more accurately. If they are of enough quality and/or supported by other findings such as lab data, they can support decision-makers in shaping patient focused healthcare systems.

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1.

What is meant by Big Data in healthcare?

Big Data in healthcare has 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.)

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2.

How is Big Data in healthcare collected and analyzed?

Healthcare systems routinely collect large amounts of data as patients use various healthcare services. For example, information on the fact that a patient has visited the doctor, 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 healthcare 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).

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3.

Who can use Big Data in healthcare and how?

The smarter use of healthcare data is expected to improve healthcare outcomes and make healthcare systems more efficient, accessible and resilient. It can also contribute to improved research and development, and lead to more effective 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 increasing patient safety; monitoring healthcare services; detection of population-level effects; more efficient recruitment and selection of patients for clinical trials; 

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4.

What are the benefits of using 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 (personalised medicine). 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.

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Source: BD4BO, Big Data for Better Outcomes, a comprehensive European research programme aiming to develop key enablers to support health care system transformation through the use of big data. The Innovative Medicines Initiative (IMI) launched BD4BO in 2016 as an umbrella programme with the overall objective of realising the potential of Big Data in the context of European healthcare; for promoting innovative methods through harmonising, accessing and analysing data. BD4BO comprises the following projects: ROADMAP (Big Data & Altzheimer, HARMONY (Big Data & hematology), BigData@Heart (Big Data & cardiovascular diseases), PIONEER (Big Data & prostate cancer) and the European Health Data Networkand Evidence Network (EHDEN) project. Read more >>

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