Big data has been having a big impact on industries globally, and healthcare is no exception. According to statistics, the global big data in healthcare is expected to reach $34.27 billion in 2022.
By leveraging data, MedTech companies can now provide patient-centric improvements, increase disease prevention and reduce costs so that more people have easier access to medical treatments.
To provide a bigger picture of how Big Data drives improvements in healthcare, we outlined the most critical ways in which it will reshape this industry in the years to come.
But, let’s first explain what Big Data in healthcare is.
What is Big Data in Healthcare?
Big Data in healthcare includes massive amounts of both unstructured and structured data gathered from EPRs, EHRs, and clinical decision support systems.
This data is then well-organized and managed and then made available to health professionals so that they can leverage it to make strategic business decisions, reduce costs and improve outcomes.
The data sets are so big that it is impossible to manage them with common data management methods and traditional hardware. But when this data is integrated and analyzed, it can have a massive effect on the healthcare industry as we know it.
Here are a few ways in which Big Data is revolutionizing healthcare:
One of the biggest challenges in medicine today is timely and proper disease identification. Big data technology offers tools like predictive maintenance, which can largely help identify the cause of illness.
For instance, the use of AI in medicine has been expanding rapidly. One of its main usages is in image-based diagnosis and pathology.
Using AI to evaluate images removes the burden of reviewing images without having to worry about the level of accuracy.
AI can be taught where to look for lessons, which further improves the process and even exceeds the capabilities of a senior human expert.
This specific tool can have a major impact on the early diagnosis of diseases such as Covid-19 as well as vaccine development. One of the technologies which also helped a lot in vaccine development is the UV Vis-NIR spectrometer.
Prevention of Human Errors
No matter how precise and dedicated humans are to their jobs, they can still make errors, like, for instance, prescribing wrong medications by accident. Consequently, this can cause great damage to the patient’s health and even lead to catastrophic endings.
According to a recent study, from almost 800,000 analyzed patients, 16,000 errors were flagged and only 75% of those flagged errors were validated.
Big data can be used to scan patients’ history of medical records and identify all the potential errors.
However, since the healthcare system still largely uses older technology, it is imperative that all medical institutions are equipped with the latest technology so that all the data analysis can be conducted more efficiently and with ease.
Most medical institutions are facing the same challenge today – they are either overstaffed or understaffed.
Predictive maintenance can help predict admission rates and allocate staff. This would further help companies focus their investments on other things that matter and utilize it to the maximum.
By using wearables and health trackers, patients do not need to stay in the hospital, which will save large amounts of money as well as improve the wait time for patients as hospitals will have enough beds for patients all the time.
In a recent study conducted by the Society of Actuaries, 47% of healthcare organizations are already using predictive analytics to achieve these goals. On top of this, the report states that over 57% of healthcare sectors believe that predictive maintenance will help them save 25% on annual costs over the period of five years.
The top machine learning companies agree that ML models can transform the ways physicians operate and assist professionals on a daily basis.
Improved Treatment of Opioid Addiction
Another huge advantage of big data is that it provides information about patients that are at a high risk of opioid abuse and even death.
Through the use of petabytes of insurance and pharmaceutical data, data scientists can detect factors that can help predict tendencies of opioid abuse.
More Efficient Access to Health Records
There is a huge amount of data surrounding patients, from demographic and historical data to medical data.
To be able to track all the information, medical institutions need a system that would keep all this data in one centralized place and thus reduce the amount of paperwork.
On top of this, by organizing data, medical companies can reduce the number of visits and lab tests, thus increasing the overall efficiency and customer care.
Using the system powered by Big Data, users can find what they are looking for more easily and quickly in both the public and private sectors.
Plus, through regular warnings and reminders, patients and doctors can have a clear view of key information like prescription tracking.
Reduction of Fraud
There is a high percentage of data breaches in hospitals, and the reason is quite simple: personal data has a high value and is quite profitable on the black market.
Any kind of data breach would lead to significant consequences. This is one of the reasons why many medical companies started using analytics to minimize or even reduce the number of security threats by identifying changes in network traffic or some kind of suspicious behavior.
On the other hand, many experts think that Big Data can only make the entire system even more vulnerable. However, anti-virus software, firewalls, and encryption technology are only some of the technological advances that improved the security of data.
Big data can also help prevent inaccurate claims and fraud, which will provide users with better returns on their claims and caregivers will be paid faster.
Leverage Big Data to Reshape the Future of Healthcare
It seems that with all these tools and benefits, the future of healthcare powered by Big Data looks bright.
Data-driven healthcare apps can significantly improve healthcare and ultimately save many lives. This is the reason good enough to make Big Data a priority for experts across the field.