The way that people are being diagnosed and treated for medical conditions is changing every day, with new techniques and new cures being found all the time.
Traditionally this has been done through extensive lab work, theoretical work is then needed to be proven through trials and data.
This is changing though, and this data that medical personnel are trying to find is now acting as the catalyst for future innovations.
This has all become possible through the use of Big Data and analytics in the medical process, from creating huge databases to an individual tracking themselves through wearable devices. It is all amalgamating to create an environment where healthcare may be undertaking its biggest revolution in living memory.
With society’s capacity for data gathering it has become possible for databases containing millions or even billions of case studies outlining every possible scenario or treatment to be created. It allows for predictive modelling, where treatment success can be established based on insight from previous cases, so if a person fits a specific profile (e.g 51 year old, ex-smoker, caucasian, regular exercise) it becomes possible to see what their best course of treatment would be. Predictive modelling can create a better insight into what could be achieved from this and any side effects that this could create.
This kind of modelling also helps to find new and unexpected cures, such as an anti-depressant helping to treat some forms of lung cancer. If a patient deviates from the modelled path, it is possible to identify the outlying choices they have made in order to establish what has caused the positive or negative anomaly. This creates new opportunities for finding cures or potential side effects within treatments.
Data is not everything in medicine though, as regardless of how many choices there are within treatments they need to be effectively trialled before they can be used on the general public.
Data can help in creating the most comprehensive possible studies and will bring together the best test subjects. This helps in creating a study that incorporates as much vital testing information as possible, from looking at as many backgrounds and medical histories as possible, through to the interference it may have with other drugs being used.
It goes further than simply treating diseases too, it is helping to both prevent them in individuals and also stop their spread during epidemics.
We have seen with the use of wearable technologies, that it becomes possible to track the routines of people, track their calorie intake and then process this with recommendations about making people healthier and therefore less likely to contract diseases. As this moves forward in the coming years, we are going to see this concept become even more important as we develop technologies that allow us to track even more data.
With the spread of disease, data can also be used to track how it is spreading and this information can then be used to stop this spread. This was attempted during the recent spread of ebola in Africa. Due to the severity of the situation, mobile providers made their data available, so that the movement of people and the spread of the disease could be evaluated and tracked to make decisions in order to minimize the spread moving forwards.
Big Data is already having a massive impact on the way that we are looking at healthcare and medicine, moving forward this is only going to increase. The implications of a wider adoption of this is also profound, as the more we collect data in this way, the more use it could have in society.