DZone

Over the years, people have been generating an increasing volume of health-related data. Traditionally, this data type is produced in citizen-centered health systems where information about patients is collected. Some common sources are patient’s health status record, video/audio exams, known diseases, regular use medicines, etc. Every time a person goes through medical services either elective appointments or urgency/emergency events it produces more data improving the accuracy of tracking each patient’s health. A straightforward advantage of this model is the construction of individualized knowledge that gives support for a diversity of preventive front lines related to diagnosis, treatment, and rehabilitation of the population. On the other hand, a critical drawback is the intrinsic dependency of people’s presence in health centers. If a person does not get in touch with those services, no consistent data is generated.

The expansion in the use of wearable devices represents a new perspective for people’s health monitoring. The telemedicine broadening scope is also contributing to this scenario especially with the adoption of the ‘continuity of care’ concept. The introduction of those technological solutions into medical preventive actions has been causing an even more explosion in the data collected volume. This is the reason big data fundamentals are being explored in that context. Considering the usability of wearable devices, Lymberis explains that,

Source: DZone