Big data is expected to grow at a 36% CAGR in electronic health records with practise management systems in the healthcare sector by 2025. By 2024, this will have reached a value of $68 billion.

The majority of this valuable data is obtained through the increasing usage of wearable devices, which are already being used by doctors to detect diseases before treatment courses grow expensive and the prognosis becomes poor. Most popular devices are compiling structured data about healthcare and patients all across the world, and some of the results are astounding. Fitbit has alone documented:

• 167 billion minutes of exercise
• 90 billion hours of cardiovascular data
• 85 trillion steps

Medical imaging is critical, with around 600 million imaging operations performed in the United States each year. Analyzing and preserving manually these photos is expensive both in terms of time and money, as radiologists need to review each image individually, while hospitals need to retain them for several years.

Medical imaging service provider According to Carestream, big data analytics for healthcare could transform the way photos are read: algorithms developed after analysing hundreds of thousands of images could discover specific patterns in the pixels and convert them into numbers to assist the physician with diagnosis. They even go so far as to imply that it is likely that radiologists will no longer need to look at images and will instead study the results of the algorithms.

Big data in healthcare has tremendous power and can considerably benefit hospitals and medicine in general, as illustrated by the abstract visuals in this image.

1) Describe Big Data in Healthcare.

2) The Most Important Big Data Applications in Healthcare

3) How Can Big Data Be Used in Healthcare?

4) Why Should Big Data Analytics Be Used in Healthcare?

5) Big Data Obstacles in Healthcare

Across sectors, big data has transformed the way we handle, analyse, and exploit data. Healthcare is one of the most visible industries where data analytics is making a significant difference.

According to Forbes, big data analytics has been successfully used at Seattle Children's Hospital to diagnose and identify treatment plans more effectively and on time.

Parkland Hospital in Texas used big data to cut 30-day readmissions for cardiac patients by 31%, saving the hospital 0.5 million dollars per year and having a considerably larger impact on patients and healthcare expenses.

Human fraud is another major issue that drives up healthcare expenditures and leads to considerable negative patient outcomes, such as fake prescriptions and diagnosis fraud to obtain illegal pharmaceuticals. The best estimates place the cost of medical fraud between $80 billion and $200 billion, according to Chicago-based marketing consultants Digital Authority Partners. They confirmed that fraud and human error account for 10% of the total.

The Centers for Medicare and Medicaid Services used Big Data to discover fraud prevention, which could have cost $210 million. Big Data is also important in eliminating erroneous entitlement reimbursements, duplicating medical records, and identifying operational inefficiencies that cost patients a lot of money.

The healthcare business thrives on innovation, and big data is at the forefront of the race to the future of healthcare. With its precision, ubiquitous availability, and insights for cutting-edge prognosis, diagnosis, and patient welfare, big data will pave the way for the creation of novel medications and diagnostic instrument.

Regards

Annabella Rose

Manager Editor

Quality in Primary Care