The Journal of mHealth Vol 2 Issue 4 (August) - Page 22

Data Driven Proactive Healthcare Data Driven Proactive Healthcare By Sébastien Deletaille, CEO, Real Impact Analytics Health organisations collect and store a lot of historic data on patients but lack the real-time data and tracking to tackle major threats to human health like large-scale epidemics or natural disasters.   When we look at the recent outbreak of Ebola in West Africa, this real-time information on the disease was typically not available making it extremely difficult for aid workers to not only treat those affected but also look at how to stop it spreading even further.   There is data available in the form of that produced on a daily basis when individuals use their phones. In extreme cases, like the Ebola outbreak, this data could be used to support humanitarian initiatives but only if how it is used doesn’t breach subscribers’ privacy. By not taking the telco data in its raw form but by aggregating the data and looking at community patterns, insights to support aid workers can be achieved without any access to personal details.   Using anonymised mobile data records, healthcare organisations can track population movements during an outbreak, enabling healthcare professionals to stay one step ahead of the illness, sending resources to where it’s expected next. People can be advised of their closest source of help, and officials can even use the data to ensure quarantine measures are being adhered to.   Real-time data has real results While historical data has its uses, there’s no substitute for realtime data. Healthcare organisations, governments and donors are used to gathering huge amounts of data on patients and populations, but there’s exceptional value in being able to track anonymised community data in real-time.   Mobile technology allows us to monitor population movements in real-time and not just by using call or phone signal data. Network counters, mobile internet searches, and even handset data, can be used to track population movements. Anonymised data can be used to predict the development of a disease outbreak without compromising privacy.   For example, if residents of an area that’s fighting an ongoing battle against an epidemic travel away from urban centres into surrounding rural communities, mobile data can show that as it happens. Scientists and healthcare professionals can use the data to predict the spread of the disease, prepare quarantine areas and divert medical aid to affected areas. Governments can use the information to establish health centres, and inform people where their nearest source of help can be found.   Providing accurate information during an emergency 20 Using real-time data alongside historic patient data, health- August 2015 care providers can work out where they need to send vaccines (based on which places are interconnected by people frequently moving between them). They can also advise individuals of their nearest points of care (based on where they currently are). For the organisation, this healthcare centre can be used as a place to collect further data on the situation as it’s unfolding. Information that they can feed back into their databases, allowing them to form a more accurate picture of the real situation, and enabling them to provide people with the vital