Wearable devices, electronic health records and big data analytics will combine to transforming healthcare, enabling new insights and promising fast and immediate personalized care for all.
connected everything
New breeds of connected wearable – such as fitness bands - are gathering huge chunks of useful personal health and activity data, even while the evolution of analytics engines and deep learning intelligence is making it possible to crunch more and more of this information to produce actionable insights and intelligence.
That’s certainly understood by IBM, which recently launched Watson Health Cloud. This will be a secure open source platform where care providers and researchers can share and analyze health data to find the insights they need to improve individual and overall patient outcomes. Based on IBM’s Watson supercomputer, information within the system will be de-identified so partners can analyse it using Wilson’s data-mining and predictive analytics capabilities.
“As healthcare providers, health plans and life sciences companies face a deluge of data, they need a secure, reliable and dynamic way to share that data for new insight to deliver quality, effective healthcare for the individual,” Mike Rhodin, senior vice president, IBM Watson explained.
health central
IBM’s initial partners include Apple, Johnson & Johnson and medical device manufacturer Medtronic, while the company also acquired Phytel and Explorys which means it already has health data of over 50 million people for analysis.
These partners encompass every element of the connected health data revolution. Apple, for example, will connect its HealthKit and ResearchKit solutions to Watson so that iOS users can contribute to health studies by sharing the information gathered by their devices. In terms of implementing insights identified by analysis of these stacks of information, Medtronic will use Watson Health Cloud to develop and deliver highly personalized care plans for diabetes sufferers while Johnson & Johnson is developing intelligent health coaching systems for pre- and post-operation patients with limb problems.
Such partnerships make it clear that big data has implications across the spectrum, from personal health to institutional care; from social health schemes to tracking disease. Data is both a management and a clinical tool, and data collection combined with remote analysis will enable new breeds of remote healthcare monitoring services, as well as more effective preventative services.
huge potential
The transformative health potential of big data analysis applied to data from mobile devices may not be immediately obvious. For example, media researchers at the Politecnico di Milano and Stanford University are using anonymized call data from Senagalese operator Sonatel to determine the impact of human mobility on water-based parasitic worm infection, schistosomiasis.
Also in Senegal, Orange contributed anonymised voice and text data from 150,000 phones with Flowminder so that it could draw up detailed maps of population movements in the region to help authorities deploy treatment centres and restrict travel to contain the Ebola outbreak. In its fight against Ebola, the US Center for Disease Control and Prevention (CDC) collects mobile phone mast activity data from mobile operators to map where calls to helplines are mostly coming from.
It is also important to understand how big data analysis for public health can take information from seemingly unrelated sources in order to find useful insights.
In the US, the Hedonometer project monitors Twitter to gauge levels of happiness and health. This yields interesting insights such as that cities with higher populations of obese people more commonly tweet the words ‘heartburn’ and ‘starving’. This kind of information can help guide wellness programs, prepare medical centers for likely problems and provide a better picture of a population’s current and future health needs. In combination with the kind of information IBM gains with its Apple partnership or research data gathered by health researchers, such data mining of social feeds can potentially yield incredibly useful insights, identifying trends and patterns that may never have been realized before today.
Read our White Paper that explains what businesses can do to harness the potential of big data, and take a look at Orange Healthcare to find out even more about big data in healthcare.
Jon Evans is a highly experienced technology journalist and editor. He has been writing for a living since 1994. These days you might read his daily regular Computerworld AppleHolic and opinion columns. Jon is also technology editor for men's interest magazine, Calibre Quarterly, and news editor for MacFormat magazine, which is the biggest UK Mac title. He's really interested in the impact of technology on the creative spark at the heart of the human experience. In 2010 he won an American Society of Business Publication Editors (Azbee) Award for his work at Computerworld.