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Hortonworks Customer
Clearsense

Hortonworks has helped Clearsense be first in healthcare by providing us the technology that allowed us to be first in actually helping clinicians understand where their patients are at any given point in time.

–Charles Boicey, Chief Innovation Officer at Clearsense

cloud Clearsense Case Study

DOWNLOAD CASE STUDY

The story of Hortonworks customer Clearsense is different. Clearsense founders started the company with Hortonworks Data Platform at the center of its data architecture. Like many other Big Data start-ups, Clearsense built their data systems from scratch, architected with Hortonworks Connected Data Platforms at the core of its offering.

Simply put, Clearsense would probably not exist were it not for the capabilities provided by Hortonworks Data Platform (HDP) and Hortonworks DataFlow (HDF).

A New Company and a New Product for Real-Time Notification in the Hospital

The Clearsense team is proud to be first in delivering SMART, real-time streaming data to its healthcare customers. Its Inception™ product makes data available for critical decisions in three areas:

Clinical Decisions – pulling in all relevant patient information in real-time for early detection of patient deterioration to reduce catastrophic consequences and optimize outcomes

Financial Decisions – tracking organizational KPIs related to financial goals

Operational Decisions – identifying and eliminating variation in the care delivery processes, providing visibility into current performance to help identify opportunities for improvement

The Inception product is architected on HDP, so it offers its users many of the same Big Data efficiencies that the initial Hadoop architects designed into the platform at Yahoo! in the early 2000s. Both Clearsense and its Inception product also benefit from the rapid innovation and ecosystem friendliness that come from Hortonworks’ 100% open-source approach.

DRIVING THE FUTURE OF HEALTHCARE WITH THE POWER OF OPEN SOURCE

Clearsense is seeing great results with its initial algorithms for code blue (cardiac arrest) and sepsis prediction. The team is looking forward to developing solutions around reducing costs for its hospital clients in the two biggest expense categories: supply chain management and staffing.