Keynote 2: Big data: hype or help?

Linked to EAHP Statements: Section 1: introductory statements and governance

ACPE UAN: 0475-0000-17-002-L04-P. A knowledge based activity.

Abstract

Health systems are forced to move in one direction: to create more value in healthcare. This means that population health should be managed more efficiently, that patient care will significantly improve and that preventive care is delivered in an efficient way. More than that cost pressure is the environment of every healthcare system worldwide making evidence-based medicine a condition sine qua non in our daily work as healthcare professionals. In the last years advances in genetics, biomedics and computing technology changed our healthcare environment and gives us the feeling that there are possibilities to fulfil the challenges to create a better healthcare system by using those data. In a SAS White Paper Big Data is defined as follows: “Big Data is a relative term describing a situation where the volume, velocity and variety of data exceed an organisation’s storage or compute capacity for accurate and timely decision making”.

So what is the role of Big Data in the healthcare system? To say this in first place: Big Data is not just to collect all possible data of single patients to put it together in big databases. Big Data also means that one can use those data with big data tools (meaning IT platforms) giving us the opportunity to e.g. identify at-risk patients (e.g. those who will develop a sepsis, calculated on the basis of patient history, age, gender, family history, genetic markers, drug therapy and other personalised factors), to track clinical outcomes (e.g. cancer therapy and again connected to the unique factors of patients), to measure performance and management of healthcare interventions and, perhaps most important for us, to make the right clinical decisions at the point of care on the basis of this Big Data. To get to this point the databases have to be filled with all the OMICS data, such as genomics, proteomics or metabolomics, of individual persons, have to be linked to phenotype data from clinical observations as well as data from environment, nutrition, food, drugs and also new data from e.g. gut microbiome. We can easily realise that this is still a big challenge for biostatistical analyses.

With the rise of Big Data we also face new challenges like data privacy, ownership and security, which are not yet discussed in-depth.

The keynote lecture will give an overview on the Big Data approach in healthcare systems, the possibilities, the challenges, the problems and the needs to work with.

And the goal of using Big Data in healthcare is clear: it shall improve quality and costs of health care to simple save lives.

Learning objectives

After the keynote, the participant should be able to:
• discuss the advantages of Big Data in decision making processes;
• avoid getting lost in the jungle of Big Data;
• classify the different outcomes of the use of Big Data in patient management.

Keywords: Big Data, personalized data, decision making

* No conflict of interest has been declared.