ABSTRACT
Electronic health records (EHRs) began as an aggregate of discrete data accumulated from various sources which were integrated into a seamless narrative that documented a patient’s journey through the healthcare system. The newer generation of EHRs incorporate real-time dynamic data from mobile sensors, telehealth, external and implanted sensors. Prototype watches and medical sensors woven into clothing began to appear in 2013 and are becoming more mainstream and this data will begin to be incorporated into EHRs. System analysis techniques utilized in other engineering disciplines will add to the dynamic predictive analysis in medical records providing probabilities of potential acute conditions such as a stroke or heart attack and possible immune responses that may be affected by stress and pollution in the environment. The field of epigenomics will also benefit from the additional data provided from dynamic medical data, where external factors can affect gene expression and regulation, i.e., the probability of developing a specific cancer. Inheriting a trait from DNA is only one of many factors that determine susceptibility to developing serious diseases. We are on the cusp of a revolution that will bring healthcare parity with other engineering advances by creating a systems approach to healthcare (Figure 3.1).
