A few years ago, artificial intelligence, big data, and IoT were generally considered as the technology of the future. That future is here now. Today, almost all industries use big data to optimize their processes and reduce their costs. The healthcare sector is no different. Data analytics has played a major role in making healthcare better, more accessible, and affordable for everyone.
The following text takes a look at the 5 most important ways big data is improving the healthcare sector and helping patients get the best care without overburdening the medical staff.
1. Enhanced continuous care for chronic patients
Many chronic conditions need doctors and healthcare staff to keep an eye on several essential parameters at all times. Patient conditions are often time-sensitive and the sooner you intervene, the better the chances of survival.
Data analytics has played a huge role in making this technology more practical and usable. Today, patients who need continuous monitoring of any health parameter are not required to be strapped on an elaborate machine. They can instead go on with their lives normally while wearing a small health monitor.
In case of an emergency or a sudden drop in any variable, the doctors and healthcare staff will automatically be notified and start preparing before the patient arrives at the hospital. This saves crucial time and stacks the odds in the patient’s favour.
2. Better predictive analytics for strategic planning
A vast majority of afflictions, especially chronic, don’t develop overnight. Lifestyle, genetic predistortion, and environmental factors have a combined effect on all our health. Data analytics makes it possible to analyse the overwhelming number of factors and predict the likelihood of developing certain conditions. This allows doctors and other healthcare workers to get ahead of the problem and proactively deal with the issues to improve any patient’s quality of life.
3. Better patient engagement
Engagement is an important parameter that has a direct impact on patient compliance and satisfaction. There are several medical wearable devices in the market or under development that not only keep an eye on specific health trends, but also ensure compliance by reminding patients about medication, exercise, and other activities.
Doctors can also access continuous data about patients and recognize specific trends in health parameters early. Something quite difficult to do with intermittent checking and other traditional methods.
4. Reduced overall costs
It’s no secret that healthcare is expensive for both patients and providers. However, data shows that these costs can be significantly reduced through optimization and efficient handling of processes. A recent study stated that over 75% of resources used in healthcare are wasted due to inefficient processes in the United States. The numbers are not much different in other areas. However, data analytics can play a part in improving this situation.
The biggest difference data analytics can make in this regard is through addressing administrational inefficiencies and streamlining the decision-making processes. With a centralized database, doctors can cross-reference data and perform multiple checks before proceeding with a major operation. This will reduce many associated costs and ensure reliable healthcare for the patients. Data analytics is also proven to reduce hospitalizations and recurring/non-recurring costs associated with healthcare. As the technology advances, so will the opportunities to further reduce overall healthcare costs without compromising on the quality of healthcare.
5. Faster, safer, and more reliable cures
Medical research requires the processing and analysis of data on an unprecedented scale. Cross-referencing treatment response and recovery rate with factors like age, health, blood type, lifestyle, and multiple other variables requires significant resources and capabilities.
Data analytics is the perfect solution to help researchers understand, and ultimately cure major diseases. From cancer research to better surgeries, and even vaccines. Data analytics is being used everywhere.
A recent example of how data analytics, AI, and other technologies expedite medical research is the Covid – 19 vaccines. Developing a vaccine from the scratch has traditionally been a very long process. However, the Covid vaccine was developed in a little over a year. Among many things, data analytics and AI had a large part in making it possible.
Final thoughts
Today, the inflow of data from a myriad of health monitoring devices has exceeded the data analytic capabilities of traditional methods. Data analytics and AI not only have the capability to analyse that data but also boost the overall quality of healthcare at a fraction of cost. The 5 aforementioned examples are only the tip of the iceberg.
There are multiple advantages and benefits for healthcare that data analytics can bring to the table. If we can knock out a vaccine for Covid in just over a year, imagine what we can do as a collective for other diseases. Shared data, along with funding, could see how world health community take on finding cures for diseases we never thought could be cured.
