The Digital Patient: Advancing Healthcare, Research, and Education
Understanding in detail and with certainty what is going on within one’s own body has been an elusive quest. Partial glimpses and general understanding are the best we have been able to do with the data we have at our disposal and with the limitations of population‐normed theories of what the data mean for diagnosis and treatment of individuals. In the not‐too‐distant future, however, that will change as the Digital Patient platform is developed. The capacity to measure one’s personal physiological and social metrics, compare those metrics with the metrics of millions of other humans, personalize needed therapeutic interventions, and measure the resulting changes will realize the vision of personalized medicine. Incorporating all of this rich data in simulations will have significant impacts on medical research, education, and healthcare systems around the world, as more interventions are simulated and assessed in silico prior to their use in therapy.
So, what exactly is the Digital Patient? The most commonly referenced definition of the Digital Patient is that provided through the European Union’s DISCIPULUS project: a technological framework that, once fully developed, will make it possible to create a computer representation of the health status of each citizen that is descriptive, interpretive, integrative and predictive. Not explicitly stated, but implied, is that this framework will include behavioral, social, temporal, and spatial dimensions.
Major technological advancements in recent years have paved the way for more systematic approaches to modeling, simulation, and visualization of biological and social processes that make the realization of the Digital Patient possible. Modeling now encompasses high degrees of complexity and holistic methods of data representation. Various levels of simulation capability allow for improved outputs and analysis of discrete and continuous events. Simulation complements both natural language and mathematical and statistical analysis by introducing new ways of thinking. Simulation also provides tools to build understanding and generate insight into complex biological systems and processes, thus allowing much more comprehensive human models.