Few innovative technologies promise to upend the healthcare industry as much as big data, which is rapidly ingraining itself into hospitals, medical research facilities and other hubs of healthcare around the country. Despite the growing importance of big data for delivering more positive patient outcomes than ever before, however, many up and coming medical professionals are still unfamiliar with the way that these dizzying analytics programs are going to achieve their full potential in the healthcare industry.
Hospitals are supercharging themselves with big data
Anyone who has visited or worked in a hospital knows what a hectic and chaotic environment they can be when things go wrong. Patients are being admitted every moment and healthcare crises can spring up like wildfires on different floors, demanding the limited time, attention and resources of medical experts who are overworked, overstressed and underpaid. In order to prevent themselves from becoming overcome by rising patient demand, hospitals are supercharging themselves with big data to handle a greater sum of needy patients than ever before.
For example, the New Jersey Hospital Association (NJHA) has launched a new facility which intends to harness the power of big data to identify healthcare gaps for patients across the state. The NJHA believes that the center, which will focus on using big data analysis techniques to evaluation patient data, can detail the underlying socioeconomic conditions that often drive society's healthcare issues from as-of-yet unseen areas. With data analytics on their side, researchers and medical professionals are now able to peer into the dark and discover a greater number of useful findings than ever before.
Elsewhere, the day to day operations of modern hospitals are becoming more efficient with the help of data analysis programs that can automate the more mundane processes of healthcare while enabling human experts to spend more face-to-face time with their patients. The Hospital Corporation of America reported that its Sepsis Prediction and Optimization of Therapy (SPOT) program has helped to save 8,000 lives by identifying sepsis symptoms early. Sepsis is usually a big time-consumer for staff because it can currently only be identified by its symptoms, rather than through tests such as blood tests. With AI monitoring patients' vital signs, hospital staff are free to deal with patients where human care is more urgent.
AI in hospital settings is becoming more powerful, yet machine learning programs cannot work in the first place unless they have access to nearly unlimited sums of useful data churned out by big data analytics operations. As AI powered healthcare becomes more mainstream, the additional generation, maintenance and surveying of complex data troves will become more integral to delivering positive patient outcomes.
The doctor is in – and he's a robot
Furthermore, big data will also achieve its full potential in healthcare by automating the entire healthcare industry to a never before seen extent. Far too many doctors and nurses are familiar with being overworked to the point where they struggle to deal withevery patient who walks through their doors, but this could be solved in the future as automated chatbots help patients deal with more trivial issues while experts focus on more serious cases. Medical facilities around the nation are already experimentingwith intelligent chatbots that appear to be totally human, satisfying patients with their quick response times and informative answers. According to Northwell Health, New York State's largest healthcare provider, 96% of surveyed patients who held a conversation with a chatbot found it useful.
Such initiatives are only possible in the first place if huge sums of data are being constantly created. Hospitals and healthcare facilities of the future will be even more sensory-laden than they are right now, with the very infrastructure of the building itself being tapped into by data analytics programs that want to scoop up data on literally everything. This could lead medical professionals in the near-future to become data scientists, as an ability to interpret huge sums of dizzying information with an algorithm's assistance will doubtlessly become essential towards some important healthcare operations.
With the evolution of medical professionals into IT-savvy data scientists well-underway, it is only a matter of time until the doctors and nurses of the future are just as good with data-crunching software as they are at identifying the various bones in the human body. As doctors become data scientists, the entire healthcare industry will be fundamentally overhauled as it becomes easier to cater to a growing number of patients. This is important, as an aging global population is already putting serious strains on our current means of delivering positive patient outcomes.
Big changes are coming to the healthcare industry
As more Americans live to become older than ever before, they will demand additional medical treatments that push doctors and nurses to their very limits. Healthcare facilities around the country are already swamped with massive patient demand that has led to a serious shortage of qualified professionals. Nurses and doctors will take more time to train in the future given the necessity of making them data gurus, too, so meeting this growing demand for medical professionals will not be easy. We will likely need to automate parts of the medical training process and keep relying on these disruptive yet innovative technologies if we want to bolster public health.