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ST. PAUL, Minn. — There are 93,000 people on the list for a kidney transplant in the United States. Last year, more than 4,700 died waiting.

And yet in each of the past five years, 2,600 to 2,800 kidneys were recovered from deceased donors and then discarded, government data show.

In many instances, organs that seemed promising were discovered to have problems.

But many experts agree that a significant number of discarded kidneys — perhaps even half, some think — could be transplanted if the system for allocating them better matched the right organ to the right recipient in the right amount of time.

The current process is made inefficient, they say, by an outdated computer matching program, stifling government oversight, the overreliance by doctors on inconclusive tests and even federal laws against age discrimination.

“There is no doubt that organs that can help somebody and have a survival benefit are being discarded every day,” said Dr. Dorry Segev, a transplant surgeon at Johns Hopkins University School of Medicine.

For 25 years, the wait list for deceased donor kidneys has remained stubbornly rooted in a federal policy that amounts largely to first come, first served.

As designed by the government’s Organ Procurement and Transplantation Network, which is managed under federal contract by the nonprofit United Network for Organ Sharing, the system is considered simple and transparent. But many in the field argue that it wastes precious opportunities for transplants.

The transplant community has grappled for years with the problem of viable kidneys being discarded. Eight years after the United Network for Organ Sharing charged its kidney- transplantation committee with improving the system, there has been no change.

On Friday, the committee plans to circulate a new proposal that would leave most of the system in place. The top 20 percent of kidneys would be matched to the candidates expected to survive the longest, placing older patients at a disadvantage. But the remaining 80 percent would still be allocated primarily by time spent on the wait list.

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