The incredible amount of data created by connected devices, health records and smartphone apps is laying the foundation for big data as a concept: unique, large and complex data sets that require specific techniques to analyse (data analytics).
Gaining insights from big data
Big Data includes data sets with sizes beyond the capability of commonly used software tools to capture, curate, manage and process data with a tolerable elapsed time. More often other concepts like AI- and deep learning platforms are usde to help gain insights form this data pool. Chronic diseases are medical conditions which consistently could create medically-relevant data from multiple sources, such as the electronic health record, the smart glucose meter, the food tracking application and the activity tracking wearable and companion app. Superficially, these data sources, are indirectly related and the role of Big Data is to bring all of these sources together.
How to deal with massive data stream
So, how do we deal with this massive data stream, multiplying roughly every 18 months? The answer according to HIMMS is found in collaborative working environments where doctors, patients, healthcare professionals, user interface and web designers, software developers and data scientists working under one roof designing highly specific solutions for the patients and healthcare providers. Some chronic conditions are especially difficult to treat due to their highly variable symptoms, complications and treatment responses. Big Data combined with concepts and technologies such as Internet of Things (IoT) Devices, Electronic Health Records and Machine Learning could create groundbreaking efforts to deal with chronic conditions.
For example, a team of experts at the National Science Foundation in collaboration with John Hopkins University have created statistical algorithms that enable computers to analyse large volumes of medical records and identify subgroups of patients with similar patterns of disease progression.
What is EU doing with big data in healthcare
What is the European Union doing with regards to Big Data in Healthcare, blog poster Stefan Buttigieg, Specialist Trainee in Public Health Medicine, Malta, asks. The latest study on Big Data in Public Health, Telemedicine and Healthcare released in December 2016 offers 10 main policy recommendations which intrinsically have a relation with Chronic Disease management such as Education and Training, Data Sources and Analysis.
More than ever we need three main things, Buttigieg states, to make big data in healthcare succesful in Europe:
- Data Governance
- Legal Framework
‘What’s amazing is that most of the technology to enable this is already there, but the last two step which are data governance and legal framework will have the opportunity to be fully clarified in the upcoming Estonian EU Presidency.’ Buttigieg hopes that during eHealth Tallinn taking place in Tallinn, Estonia between 16 and 18th October 2017, more steps can be taken towards succes for big data in EU healthcare.
Future of ehealth: more collaboration needed
In a 20 July informal meeting in the Estonian capital of Tallinn, EU health ministers discussed the future of digital solutions in health in a broader perspective. The main outcome was the need for further collaboration between EU member states and action at EU levels to overcome the main challenges of data-driven digital innovation in health, such as better alignment of regulation en building common data platforms.
The ministers identified three areas for closer collaboration among member states and possible actions at the EU level to overcome the main challenges of data-driven digital innovation in health:
- Better alignment of regulatory and data governance approaches when implementing the new EU data protection regulation.
- Extending the cross-border health data exchange.
- Building common data platforms to facilitate the reuse of data for research and innovation.`
A digital Europe and the free movement of data is one of the overall priorities of the Estonian Presidency in the second half of 2017. With the spread of digital technologies, large amounts of data are produced in the health sector, which could be used for advanced data analytics to support the prevention and treatment of diseases and to contribute to research and innovation.