According to IBM TJ Watson Research Center reports, as of 2012, worldwide digital healthcare data was estimated to be about 500 petabytes and is expected to reach 25,000 petabytes in 2020. Data collection is exponentially increasing, but the ability to analyze this quantity of data is crucial for big data in health care.

A multitude of structured, semi-structured, or unstructured data such as doctors notes and health surveys provides opportunities to improve the quality and efficiency of patient care, this is achieved through predicting outcomes and using the available primary or historical data.

• This data is generated from patients examination, laboratory results, medical device sensors, wearable, health monitoring, medical imaging, clinical, and other sources.
• It uncovers an opportunity to perform advanced analytics and data mining such as Clinical decision support (evidence-based medicine and diagnosis), workflow improvements, inpatient alerting, fraud prevention, patient profiling, population health management, early detection of diseases, revenue cycle management, etc.

DataKare analytical services are aimed to help healthcare organizations to deal better with this huge volume of big data by creating an efficient data pipeline and developing actionable insights to improve outcomes, quality of patient care, revenue cycle, and increase value on investment to develop sustainable healthcare systems.