Supernova Award Category

The Problem

On average, 85 lives are saved or enhanced every day in the United States through organ donation, yet there is still room for improvement. There are more than 120,000 people in the U.S. waiting for a lifesaving organ transplant, and every 10 minutes another name is added to the list. However, there is a lack of donors and making a better use of organs is a challenge.

UNOS databases currently contains approximately three terabytes of data. When it first brought Hadoop onboard, UNOS Data Services development team, which consists of an architect/developer and another developer, were hand-coding it. The team soon recognized they needed an enterprise tool that could integrate all its different technologies into one pipeline and eliminate the hand-coding so that they could get a complete picture of transplant centers transplantation activity at their hospital for a given month. 

The Solution

UNOS had a set of requirements and set out to do a proof of concept; they were looking for a tool that had a familiar programming language such as Java and one that was very extensible. After the successful proof of concept, UNOS decided on Talend Big Data that includes Big Data Integration and Data Quality. It took UNOS only two and a half months to go live with the Organ Offer Report functionality, which essentially makes data available to transplant centers so they can find ways to use organs that may not have been used before, transplant more patients and save more lives through transplantation. UNOS liked that Talend is a part of a new generation of tools that have been built natively to work with Hadoop platforms. In fact, Talend is an integral part of the UNOS project to build a data warehouse within Hadoop in order to do historical and predictive analysis on data sets. 

The results

Talend processes the data within Hadoop, and outputs the results to a source system where Tableau data visualization software can read them. Tableau then serves up the Organ Offer Reports. Talend makes the Organ Offer Report available sooner by allowing UNOS to rapidly ingest and process data from several systems. Transplant centers accessing the report can now see bio statistics about a specific organ, such as blood type and antigens, and the history of what they’ve transplanted over the last three months.

The UNOS Data Services development team consists of an architect/developer and another developer.

The company also has researchers who help load data and use Tableau to validate it by providing unit

test cases to make sure that computed results look correct. With Talend, UNOS can be very productive with a small development team and be very efficient in terms of organizing and building code.

Talend provided almost a thousand prebuilt components that are easy to drag and drop and then hook up. That replaced all the hand-coding. It’s a lot faster than coding it all in Linux or Java. UNOS can also extend Talend by adding its own custom Java code if it needed to, which is extremely powerful. The ability to re-use components not only allowed UNOS to avoid writing something over and over, it also increased the consistency and quality of the software. All this has dramatically shortened the time needed to develop and unit-test components for specific tasks.

Metrics

Using Talend has enabled UNOS to automate the process of integrating systems and processing data as well as reduce the time required for this essential task from 18 hours down to three or four hours – a 60 percent increase for more efficient organ donor matching. As a result, 85 lives are saved or enhanced

every day in the United States through organ donation.

The Technology

Talend Big Data

Disruptive Factor

While it was a big piece to rewrite because the system included 45 or 50 different jobs and thousands of lines of Java code and a process that crosses several different platforms and technologies, it only took UNOS only two and a half months to go live with the Organ Offer Report functionality. The UNOS Data Services development team consists of an architect/developer and another developer. The company also has researchers who help load data and use Tableau to validate it by providing unit test cases to make sure that computed results look correct. So in short, they have a small development team, but they were able to be very efficient in terms of organizing and building code.

Shining Moment

Using Talend Big Data to speed system processing time by 60 percent for more efficient organ donor matching.

On average, 85 lives saved or enhanced every day in the United States through organ donation, yet there is still room for improvement. There are more than 120,000 people in the U.S. waiting for a lifesaving organ transplant, and every 10 minutes another name is added to the list.