Every year, tens of thousands of Americans receive new organs, giving them a new lease on life when the ones they were born with start to fail. In 2016 there were more than 33,600 transplants, a number that has risen by 20 percent in the past five years.
However, there are many more than that waiting on the transplant list — about 120,000 people total. Sometimes they wait for years; an average of about 8,000 people die every year waiting for the organs they need. Researchers, doctors and policymakers are exploring new strategies to increase the supply of organs needed to meet the demand.
Part of the reason for the shortfall is that not all donated organs can be used. One factor is the standard method of transport and storage. There is a short window of time to get the organ to the recipient in time. Another problem is mismatching donors to recipients. In response, there is a movement afoot to find tech solutions to combat the crisis.
Most transplantable organs come from deceased donors, and once an organ becomes available, doctors have just a few hours to find a recipient and complete the transplant. "Once an organ is procured, the clock starts ticking," says David Klassen, the chief medical officer at the United Network for Organ Sharing (UNOS). The longer an organ stays outside the body and on ice, the worse it functions, putting the recipient at risk of complications. Sometimes if it takes too long or a donated organ doesn't meet the standards mandated by medical protocols, it must simply be discarded.
UNOS is the organization responsible for organ allocation, and they are constantly working to improve the way they allocate organs for transplantation. Each organ has a different policy, and the allocation algorithms are built around these policies, says Anne Paschke, a spokesperson for UNOS. Programmers and testers create the algorithm from scratch and make sure it works before it is implemented.
Unlike algorithms used by places like Facebook or Netflix, which incorporate machine learning or artificial intelligence, UNOS' algorithm compares complex and multifaceted medical and logistical factors, such as the patient's blood type and antigens, and logistical factors such as distance and medical urgency, to match donors to recipients.