Technology is driving medicine towards a new era where new devices and large amounts of data come together to play an important role on diagnosis and treatments. The deployment of Electronic Medical Records (EMR) has been a significant improvement on healthcare as it unifies clinical data. However, new data sets may increment and deepen the understanding of patient’s clinical condition as never before. Smart and wearable devices are good examples of new technologies that enable new data sets such as monitoring steps, sleep patterns, heart rates, etc. Another example is the improvement on omics data that could provide a much more specific understanding on certain conditions on the genomic level. Environmental data such as air pollution, for example, can also be monitored and used to provide context to individuals lives.
Precision medicine is a new approach to health care that takes into account this holistic understanding of individual variability in genes, environment, and lifestyle. Although promising, big challenges poses to address this approach.
Many issues related to the data are yet to be addressed regarding policy making, data security and privacy but there is also another important perspective to be considered: data analysis and visualization.
The objective of this research is to design an ontological database of data visualization for precision medicine. Therefore, a complete and dynamic library of different data and information visualization types will be aggregated with meaning in the context of precision medicine. Technology constraints and human-factors will be taken into consideration. The ontological database will be designed by 1) the identification of data visualization types used currently in precision medicine literature; 2) understanding of clinicians mental models for decision making; and 3) aggregating technology and human-factors needs and constraints.
Last updated: March 11, 2020