Big Data is now being used in almost every sector and so how healthcare can’t use it. There is multiple big data application in healthcare which is playing an important role in the growth.
Majorly big data in healthcare is being used to reduce cost overhead, curing diseases, improving profits, predicting epidemics and enhancing the quality of human life by preventing deaths. So, we can say that Big data Hadoop has almost revolutionized the healthcare field.
As per the report shared by US National Library of Medicine National Institutes of Health (NCBI), alone US healthcare has generated over 150 exabytes of data by 2011. At this rate, very soon the generated data from US healthcare will soon touch zettabyte (10^21 GB) and even yottabyte (10^24 GB). Now with such a huge amount of data, a lot can be improved in healthcare and Big Data Hadoop is executing the job very beautifully.
Here are some of the solutions from Big Data Hadoop to the healthcare industry. This figure explains the overview of verticals where big data is solving the healthcare issue or improving it.
Now let’s see some of the top big data application in healthcare and how it is being used.
5 top big data application in healthcare
Let’s start and see how Big Data Hadoop is helping to solve the real-time healthcare problems. Apart from the normal issues, it is also helping to enhance the technology and reducing the cost involved in major operations.
Hadoop in Monitoring Patient Vitals
Many big hospital chains are using Hadoop to educate their staffs and practitioner to work efficiently and better. Many such hospitals use some kind of sensor around the patients’ bed which capture and store the patients’ activities and behavior like BP, Cholesterol, etc.
It also captures the kind of issues patient is facing and report. Now, these sensors generate a huge amount of data which an RDBMS can’t store for longer and so Big Data Hadoop is needed.
Later these data are being analyzed and used for enhancing the hospitals’ service and treatment.
In hospitals, Clinical Decision Support (CDS) analyses medical data on the spot and advice health practitioners as they make prescriptive decisions.
Usually, doctors’ want the patient to stay outside the hospital due to the high living cost involved and even the patient wants the same to avoid heavy treatment cost until the time there is an emergency.
There are wearables available which if the patient will wear, sends the health data to the cloud. Now, these data are available to the doctors and they can act on that in real-time.
This has helped a lot in real-time alerting. For example, if the BP of some patient has increased suddenly, the doctor can act immediately by seeing their record.
Later these data are being analyzed to improve the healthcare service delivery with the help of Big Data Hadoop.
Fraud Prevention and Detection
The number of fake claims in Healthcare is not a new thing and is getting increased day by day. If you will consider the total false healthcare claims done, the total value will be in billions.
In a survey, over 40% people accept that the high cost of healthcare insurance is due the more number of fraud claims.
Healthcare insurance companies are making use of Big Data Hadoop to minimize such claims. They make use of real-time and historical data on medical claims, weather data, wages, voice recordings, demographics, the cost of attorneys and call center notes.
Readmission is a very big problem for all the hospitals especially those who returns within 30 days of treatment. At any cost, the hospital wants to keep such cases away.
Hospitals like Texas Hospital used Hadoop in EMRs and found that patients those return in 30 days need additional treatment and extra supervision. By doing so the hospital was able to reduce the readmission from 26 to 21. That means just by using Hadoop in EMRs, they were able to reduce the readmission by 5%.
Electronic Health Records (EHRs)
EHRs are the widely used big data application in Healthcare. In the country like the US, every patient has their own digital records which include their demographic details, health records, medical history etc. which is available to all the public and private healthcare service providers.
Every record is comprised of one modifiable file, which means that doctors can implement changes over time with no paperwork and no danger of data replication.
EHRs also trigger warning to the patients if their lab test or doctor visit is pending and ensures that patients are taking care of this. Although implementing EHRs in all the health centers is a big task but the US has able to implement this in over 96% of hospitals. But if you talk about India or Asia pacific, the rate is still very less and more challenges are there.
These were some top big data application in Healthcare. As we saw Hadoop is helping the industry very well both in terms of service as well as treatment cost and so even the small health centers are now adopting the technology and making use of it.
In India also hospitals like AIIMS (check AIIMS Exam pattern here) are making use of Big data to improve their service and quality.