Even modest improvements in the organ exchange market can save many people’s lives. This is where economists and experts in operations come into play.
Akbarpour, a professor of economics and associate professor at Stanford GSB, recalls: “We used these tools I was familiar with to solve this social problem.” “I’d never seen such an elegant application of math.”
Nearly 100,000 Americans are waiting for a kidney. Around 8,000 are removed yearly because they have become too sick for significant surgery or died before an organ became available. Others are on dialysis and have a dramatically reduced quality of life as they survive the slow decline in kidney function.
Medicare’s program for end-stage kidney disease pays for dialysis or transplantation in cases where private insurance is unavailable. The cost of this program, which amounts to just 1% of federal spending (a staggering 49.2 billion dollars in 2018), is shocking. The moral and economic importance of this problem makes it a natural question to ask how to maximize the allocation system.
Akbarpour spent considerable time thinking about this question. Two of Akbarpour’s colleagues, Paulo Somaini and Stefanos Zenios, studied the question from different angles. Roth shared the Nobel Memorial Prize in Economic Sciences in 2012, in part because of his research on kidney exchanges.
This work perfectly exemplifies the two-way interaction between research and practice at Stanford GSB. Research informs the training, which raises questions that researchers must answer. Although the challenges are still technically challenging and ethically complex, the fact remains that even minor improvements in the system can save lives.
Winners and losers
Since the 1960s, when surgical and pharmaceutical innovations made kidney transplants feasible, the demand for kidneys has always exceeded supply. In 1995, approximately 42,000 people waited for a kidney. By 2004, that number was 77,000. It’s now around 100,000 people, with about 20,000 kidney transplants and 40,000 new patients joining the list each year.
Somaini says that doctors are very aware that they have limited resources. This is why they began talking to economists. Economics has always dealt with how to use scarce resources best.
In the late 1990s to early 2000s, a few economists and operations specialists, including Roth, became involved in kidneys. They realized that game theory and queueing theory could be applied to increase the number of kidneys available and allocate them more effectively.
Somaini explains, “Efficiency is a hard concept to grasp in this case.” The healthy will live longer than the sick and the young because they have a new kidney. While they may seem beneficial, other changes made to improve efficiency can end up discriminating against people based on race or blood type.
Somaini says that when you change a distributional system, one group generally wins and the other loses. Finding the right balance between efficiency and equity would be best.
Aside from this, there are two ways to donate a kidney: by living donation or deceased donation. A living gift is when someone alive donates a kidney to someone else who needs it. This can be a friend or family member, sometimes even a stranger. This is possible since most people are born healthy with two kidneys but can live perfectly well with just one. The deceased donation, which will make up 70% of all kidney transplants in 2020, is when someone who had previously decided to donate organs dies. Each of these options is unique and poses different challenges.
When Economics and Ethics Collide
United Network for Organ Sharing, a nonprofit organization, is responsible for managing the national waiting list and formulating the ranking policy that governs the distribution of deceased donor kidneys. The current algorithm creates scores based on a few factors, including how long the patient has been waiting on the list or how well the donated kidney matches the recipient’s blood type and tissue. The recipient can decide whether to accept a kidney if a good match (high score) is found.
In 2014, a tweak in the algorithm offered the best-quality kidneys for candidates with the most extended post-transplant survival times. This was done to avoid transplanting kidneys with the most longevity potential to people nearing their end of life.
Somaini, along with two colleagues, recently examined whether adjustments made to the algorithm could improve outcomes. What would happen if people of different backgrounds were given priority for different types of kidneys? In an extreme case, the researchers looked at the results if they tried to maximize the lifespan of all patients in the transplant pool. This led to a five-year increase in the median survival time — from nine to 14 years. However, the gain was only realized by a drastic reshuffle of the kidney recipients. The sickest patients on the waiting lists were often overlooked. Somaini said, “I looked at this option with my economist hat, not my ethicalist hat.”
Levin believes that this tension makes the kidney allocation question so intriguing. This issue is at the intersection between economics and ethical issues — an area in which economists don’t usually spend time but are forced to do so,” says Levin. “We are in this world where we must think about the best way to solve the problems facing those with renal failure that is morally right.”
Zenios has been studying deceased donation for nearly two decades and has identified several avenues to improve outcomes. In a paper published in 2004, he and his coauthors modeled the effects of patients declaring their willingness to accept different kidneys. Some patients may wait only for high-quality kidneys, while others might be willing to take any available kidney. This approach, which creates separate waiting lists inside the central waiting list, could increase the number of kidneys available by up to 15 percent and reduce the number of people who die on the waiting list by 30 percent.
Zenios’ and his co-workers’ are more recent study supported the policy change in 2014 that offered the best kidneys to patients with the highest health. The researchers suggest that the same policy shift be made at the opposite end of the list by prioritizing patients with lower-quality kidneys. The researchers also point out that, despite being an intuitive measure, prioritizing people based on their waiting time hurts outcomes. Finding a new metric could result in significant improvements.