Customer Company Size
Large Corporate
Region
- America
Country
- United States
Product
- Decision Lens
Tech Stack
- Analytical Hierarchy Process (AHP)
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Productivity Improvements
- Customer Satisfaction
Technology Category
- Analytics & Modeling - Predictive Analytics
Applicable Industries
- Healthcare & Hospitals
Applicable Functions
- Logistics & Transportation
Use Cases
- Predictive Replenishment
Services
- Data Science Services
About The Customer
The United Network for Organ Sharing (UNOS) is a private, non-profit organization that serves as the nation’s Organ Procurement and Transplantation Network (OPTN) under contract with the Federal government. UNOS brings together hundreds of transplant organ procurement professionals and thousands of volunteers to help make lifesaving organ transplants possible each day. Over the last 25 years, the number of organ transplants performed in the U.S. has doubled, but as long as there are people on the waiting list, there is work to be done.
The Challenge
The United Network for Organ Sharing (UNOS) is a non-profit organization that serves as the nation’s Organ Procurement and Transplantation Network (OPTN). Over the last 25 years, the number of organ transplants performed in the U.S. has doubled, but there are still people on the waiting list. The current system for matching donated organs to potential recipients includes a classification system with dozens or hundreds of characteristics for each organ. This system has hard boundaries on the different classifications, which can result in unfair allocation of organs. For example, someone who qualifies for an organ 251 miles away is lower on the priority list than those who are only 249 miles away, even if other attributes were comparatively more urgent.
The Solution
To make the process more fair and flexible, the OPTN Lung Transplantation Committee is developing a continuous distribution system based on assigning points for different attributes, rather than having hardline classifications for each of the factors involved. This way the allocation system would be able to account for all factors simultaneously, accounting for the importance of each factor in determining where a patient falls on the list. UNOS partnered with Decision Lens to collect the feedback necessary to prioritize attributes against each other and assign points to those attributes. Almost 200 participants were able to login and use the system. UNOS had researched a few different AHP tools, prior to choosing Decision Lens and liked the easy-to-use user interface for volunteers viewing reports and for the patients and transplant professionals participating.
Operational Impact
Quantitative Benefit
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