The Journal of mHealth Vol 1 Issue 3 (June 2014) - Page 32

Conference News Continued from page 29 ance companies, employers and healthcare providers can view a comprehensive picture of an individual and a population's health – one that is more accurate and trustworthy than a first-person narrative. This increase in predictive ability should be a force for good, but human reactions may be unpredictable. Prognosis could provoke change, equally it could provoke over- or underestimation of the risk, or – if the prognosis is not positive – to ignore it altogether. We already know that humans have a tendency to drift towards hyperbolic discounting. The risk of a terrorist attack, which statistics tell us is highly unlikely, is seen by most respondents as being far higher than diabetes – which statistics suggest is a much likelier fate. Moreover, most people have an inability to imagine how they will age and how their preferences and personalities will change. The most effective way for humans to take on and realise information is through feedback loops. The first stage is evidence, the actual data; then comes the prognosis based on the data; the relevance of the prognosis has to be realised in its social and physical context; the consequences of the prognosis are understood; and the individual finally acts according to the previous four steps. The circle is started again. These stages can be identified within the use of fitness armbands that record physical movement. Evidence (steps) leads to prognosis (expected gains in fitness); leads to relevance (frequently in a gaming context, which encourages participation); leads to consequences (feel better, weight loss); and finally action (take more steps in a day). This does not mean there are not questions about predictive technology. Human happiness is not a universally defined quantity. Some may feel uncomfortable in the knowledge that our future is already defined. Moreover, it is difficult to know what to do with prognoses that may not be beneficial; such as a predisposition to criminal behaviour or a degenerative condition. Predictions can be self-fulfilling. As W.I. Thomas and D.S. Thomas suggested in 1928, “If 30 June 2014 men define their situations as real, they are real in their consequence.” Reducing the burden of chronic disease through remote monitoring and management (Laurence Jacobs, Senior Research Scientist, University of Zurich Medical School) The traditional approach to the management of chronic diseases is not optimal from a medical perspective, and it is extremely expensive. Moreover, the worldwide growth in cases of chronic disease continues to increase at a very fast pace. Reasonable cost estimates place the total financial burden caused by chronic disease in the several hundreds of billions of dollars annually. This situation is untenable in the long run. Left unattended, this problem is such that in the not too distant future, no society will be able to afford the cost of caring for its ailing population. The traditional approach to this problem simply does not scale well. Fortunately, there are alternatives to the traditional approach. These alternatives, at present mostly in the development or testing phases, are not only much cheaper, but they have the potential of being better for the patient from a medical perspective. The current opportunity was born not only of necessity, though that has played an important role, but also from the confluence of the general population's interest in health. Companies have developed small, accurate and inexpensive biosensors. These have led to a growing availability of good quality data that can be used to derive accurate models that can generate alerts, or even trigger devices to react to critical changes in the one or more parameters being monitored. Diabetes is a prominent example. As far as growth, it is estimated that there will be around 250 million sufferers worldwide by 2030, more than double the amount estimated in 2005. A key component of the process of managing dia- betes is to measure the level of glucose in the blood several times a day. With the technology of a few years ago, this process is painful , expensive and cumbersome, requiring the extraction of blood and the use of portable meters. However, current technology already allows for a reasonably practical way to measure glucose continuously using a sensor that is implanted subcutaneously. Even better, several start-ups are announcing systems to measure glucose continuously without the need to extract any blood at all. These sensors, several using light, or estimating the levels of blood glucose by analysing tears or saliva, will soon become commercially viable. These systems will not only be simpler and cheaper, but they will also lead to better methods of treatment. There are currently many clinical trials underway that aim to test integrated platforms, running smartphones, that measure, analyse, and report on multiple continuous measurements of a potentially large number of important biometrics that promise to optimise the treatment of several chronic diseases. Patients and their doctors can be informed in real time on effective treatment change, and alert on critical risk factors. This would have been imposs