How Big Data Technology like Hadoop is used in Healthcare Industry?

Hadoop has the least cost for every TB (terabyte) of data processing. Did you know that 80% of all healthcare information is unstructured? Doing Big Data analysis with Hadoop is relatively inexpensive as when compared to other forms of data processing. You can get to know how exactly Hadoop is used in healthcare data analytics through Intellipaat’s big data training. The ins hosts competent training in Hadoop along with Hadoop projects which will give you hands-on experience with the technology.

Benefits of deploying Hadoop in healthcare

• Early discovery of diseases and also used as a check for epidemics. Before a disease becomes widespread Hadoop can recognize it aptly and prevent it. Mass vaccinations can be deployed in preventing such dreadful diseases to gain ground.
• Healthcare institutions can obviously get increased profits using Hadoop
• Based on genomics and patient profiling new treatments can be incepted
• Highly accurate detection and curing of those diseases which have low treatment success ratio. I will shortly discuss how Hadoop is used in tackling the disease of cancer.
• Consider finding correlations between different datasets which involves many variables. It is that hard for human researchers to do all that with full efficiency. That is why Hadoop has so much potential in the healthcare industry which requires these specific capabilities.
• Prevention of medical insurance fraud

Hadoop use cases in Healthcare

Hadoop in Cancer Treatment

There are about 3 billion base pairs of human DNA and if defeating the cancer is the goal then this data on the human DNA needs to be organized. Cancer mutates in different ways and reacts differently as per the genetic makeup of an individual. This is why it is difficult to cure cancer. Why else do you think some people are able to beat cancer while others can’t even put up with the treatment? Hence oncologists declare that the best way to cure cancer is to provide personalized treatment as per the genetic makeup of the patient. Hadoop is a great help in this regard which provides parallelized treatment and aids in mapping 3 billion DNA base pairs through MapReduce programs. Now you know how problems in healthcare analytics get solved by introducing Big Data in healthcare.

Monitoring Patient’s Vitals

Already Hadoop is being used in various hospitals across the world. Without this technology, working with unstructured data is unimaginable by those who want to use patient care systems. Children’s Healthcare of Atlanta in their ICU units treats over 6,200 kids. The time period which a kid spends in pediatric ICU varies from a month to a year. The hospital usually places sensor beside the patient’s bed to continuously monitor the heartbeat, respiration and other vital inputs. If there is any change in these signs then the hospital will immediately notify the doctors, therapists so that they can take care of the patients. All this is possible because of the potential of Hadoop.

Hadoop used in Fraud Detection and Prevention

FRAUDULENT MEDICAL INSURANCE CLAIMS ACCOUNT FOR ABOUT 10% OF THE TOTAL HEALTH INSURANCE PAYMENTS. GLOBALLY THIS AMOUNTS TO BILLIONS OF DOLLARS OF FRAUD. IT IS HARD TO DISCERN INSURANCE FRAUDS BECAUSE THEY ARE INCREASINGLY TURNING COMPLEX. HEALTHCARE COMPANIES HAVE THEREFORE TOUGH TIME IN DEALING WITH THESE CROOKS.   

Big Data analytics help the healthcare insurance companies to prevent fraud at an early stage. They take into account medical claims, voice recordings, attorney costs, call center notes, and many other variables in determining fraud. To process all these variables Hadoop technology is used. Hadoop’s potential in storing a vast amount of unstructured data in HDFS and its processing power which MapReduce provides is highly leveraged in fraud detection.

Storage and Processing Capabilities of Hadoop

About 7 years ago the cost of the scalable relational database with lifelong software license was around $100,000 for a TB (terabyte). Hadoop changed the rules where it can store, look over and process the same amount of data at around just $1,200 per year. This decreasing cost for storage is one of the main reasons why Hadoop is being increasingly used in healthcare. So there is somewhat an inversely proportional relationship. Generic treatment for a disease will be a thing of the past. Patients will get personalized treatments based on their disease patterns and all that in reduced costs.

Conclusion

The process of introducing new variables to the processing model is made simple by Hadoop. Most healthcare companies still are stuck in legacy healthcare data processing systems. They are yet to realize the potential of Hadoop in data analytics. In future our SSN (social security number) or Aadhar may be linked with our medical history and the processing of healthcare data can be based on it. Patterns in diseases related to a particular geographic region can be soon be realized by data analytics tools like Hadoop. As said earlier storage costs of Hadoop is very low compared to legacy storage and processing costs. This along with other benefits of Hadoop will ensure that it will rule the healthcare industry for long.

 

Source: wipsen