Steve Jobs’ liver—and the quest for a better organ algorithm

ARS TECHNICA | Mallory Locklear
The legacy system is inefficient, but can equations overcome emotions?
As Stephen Merritt once sang, "I think I need a new heart."/ GettyImages
In 2009, Steve Jobs received a liver transplant—not in northern California where he lived, but across the country in Memphis, Tennessee. Given the general complications of both travel and a transplant, Jobs’ decision may seem like an odd choice. But it was a strategic move that almost certainly got him a liver much more quickly than if Jobs had just waited for a liver to become available in California. Eight years later, the Apple founder’s procedure continues to highlight the state of transplants in the US: when it comes to organs, we have a big math problem.

Today, there’s a much greater need than there are organs to go around. It’s a problem currently being tackled in part by mathematicians and developers, who are crafting clever algorithms that aim to make organ allocation as fair as possible. But it’s complicated math that’s done against a backdrop of sticky ethical issues, and the debates surrounding it are heated and contentious.

The problem(s)

Before we can understand how researchers are using math to take on the bigger issues plaguing organ allocation, we have to understand what those issues are and where current strategies—mathematical or otherwise—have failed.

Organs are allocated differently depending on the organ. For hearts and lungs, the time between organ procurement and transplantation has to be kept very short. So, a recipient is first searched for within a limited radius from the donor hospital. If no suitable person is found, the radius is extended out. Continue reading
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