Healthcare by Big Data
The healthcare system and medicine are currently being gripped by the “Big Data” revolution: the explosively increasing availability of huge amounts of data. Every doctor’s visit, every prescription, every hospital stay leaves a digital fingerprint which in sum provides a snapshot of all medical services and the health of all patients in a country – in Austria, for example, about two million hospital stays a year and 100 million contacts with 20,000 different health care providers, from the family doctor to the specialized physician or the laboratory visit. With a new generation of mathematical and computational models such data sets can be used to generate new knowledge, which is made available to science, health care providers and the interested public.
At the Complexity Science Hub Vienna, the world’s first model of a nationwide health care system is developed. Every patient, doctor, pharmacy and hospital is represented by an anonymous avatar. Changes in the health of the patient’s avatars, medical contacts or hospital stays are formulated on the basis of concrete observations in a large data set of medical billing data and subsequently modeled.
The goal of such “agent based” simulations is to identify weaknesses and to make the health care system as a whole more efficient and sustainable.
In particular we can ask questions: How do new treatment guidelines affect the health of the population? What effects does the pooling of hospitals and specific medical practices effect the health care status in a particular region? How accessible are medical services in a country? How far are we away from systemic bottlenecks and even crashes?
The full-scale simulator will make it possible to develop personal strategies for chronic diseases that pose the most urgent challenges of today’s medicine: the pandemic of chronic diseases such as diabetes, cardiovascular diseases, and cancer. Personalized strategies for the targeted prevention of chronic diseases could be identified, and by a better coordination of different medical service providers the number of preventable hospital stays could be reduced.
To implement this vision and to generate meaningful knowledge from Big medical Data, new mathematical and statistical methods are needed. At the Complexity Science Hub Vienna, we are working on new ways of interpreting medicine into a science of dynamic, co-evolving, generalized networks.