With predictive medicine, it is possible to predict the risk of diseases based on unique data of a patient which includes factors like – their lifestyle, previous medical history, environmental and genetic data. Medical information in electronic medical records (EMRs), gives medical professionals a better view of what happened in the past based on which they can make predictions about what may happen next.
With the Internet of Things (IoT), predictive medicine is giving people a more personalised medical experience. Today devices can be connected to keep a check on health which helps in supporting predictive medicine. As data becomes more accessible and devices smarter, medical professionals are looking to connect technology with a smooth experience for the patient.
Apart from that, predictive medicine is based on a whole lot of genetic testing. Genomics help doctors determine the probability of a person developing certain diseases. The study of biomarkers helps to analyse data which is linked to certain diseases. An example of such genetic testing can be seen in a research study conducted by Sekar Kathiresan, a geneticist at Massachusetts General Hospital in Boston. Kathiseran looked at 6.6 million spots on the human genome to calculate a person’s risk of developing coronary artery disease. With the help of the data, the doctors developed a polygenic risk score that could be applied to patients based on their individual genetic markers. Despite genetic testing being the cornerstone of predictive medicine, it is not the only data used by the doctors to predict diseases. The medical researchers also make use of data like past treatment outcomes, the latest research in peer-reviewed medical journals, and hospital admission and re-admission rates.
Predictive medicine can revolutionise healthcare systems. Today many forms of testings can be considered as examples of predictive medicine. For example, screening tests of newborn babies helps to determine whether children are susceptible to any kind of diseases. Risk Testing approach of predictive medicine helps in identifying whether patients have risk factors that could exacerbate the likelihood of disease. Diseases like Cystic Fibrosis can serve as a potential paradigm for the application of predictive medicine. The breakthroughs achieved to date offer tremendous hope to many patients affected by this life-shortening condition.
Predictive medicine can also reduce healthcare costs in the long run. Predictive medicine can reduce unnecessary prescription medications, tests, and procedures which lead to extra expenditures. Predictive medicine can also assist with prevention and public health by allowing doctors to offer more early intervention strategies.
