Real Numeracy

I happened upon a personal finance column that appeared in the New York Times April 1981. The story predicted that treatment of end-stage renal disease (ESRD) would soon become a serious financial and moral issue.

The article pointed out that in 1980, there were slightly over 62,000 patients on dialysis. The total annual cost to the federal government for treatment was $1 billion and climbing. (ESRD is the only disease covered under Medicare regardless of age.) Medicare covers 80% of the cost with the rest coming from private insurance or state Medicaid programs.

At the time, medical experts worried that by the end of the decade the number of ESRD patients could reach 90,000 with costs rising to $4 billion to $5 billion annually. (It’s not clear why a 50% growth in patients would lead to a 400% growth in cost, though the early 80s was a time of double-digit inflation.)

I did a bit of investigation, looking at data collected by the United Network for Organ Sharing (UNOS) and U.S. Renal Data System (USRDS) to find out what the actual outcomes were.

In 1989, there were 175,000 patients with ESRD, of which 130,000 were on dialysis and 45,000 with a functioning transplant. That’s nearly double the number predicted. The total cost of treatment was $4 billion which after adjustments indicates that per patient costs were rising about as fast as inflation. That’s a bit of a bargain since total medical costs rose significantly faster than inflation during that period.

So where are we today? In 2008 (the latest year data is available) there were 547,000 patients with ESRD, of which 382,000 were on dialysis and 165,000 with a functioning transplant. Total Medicare expenditures on ESRD were $27 billion, consuming about 6% of the total Medicare budget. The growth in kidney disease may have been a crisis in 1989. Today, it is an absolute financial disaster with an immeasurable human toll as patients on dialysis die waiting for transplants.

ESRD prevalence counts and prevalence rates in the U.S. Graphic from USRDS 2010 Annual Report

Medicare expenditures on ESRD, not adjusted for inflation. Graphic from USRDS 2010 Annual Report

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Incidentally, the 1981 NY Times article said the best chance of reducing costs for dialysis was to encourage use of home dialysis which would reduce capital and labor costs for dialysis facilities. Home dialysis never became popular. The number of patients using peritoneal dialysis, the most common home treatment, has remained steady since the mid-1980s while the total number of ESRD patients has grown rapidly. Today only 5 percent of kidney patients choose it as their form of therapy.

The article also stated that few patients could be helped by transplantation therapy. Unknown to the author, the immunosuppressant drug cyclosporine would be released in 1983, making transplant from deceased donors and unrelated living donors possible. The number of transplants boomed. But as the data above shows, the number of kidney patients grew even faster, creating a waiting list that continues to grow to this day.

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For another interesting historical note, see this May 2010 blog post.

The Wired Feb 2011 contains an article entitled “The Red Market”. This is the name that investigative reporter Scott Carney gives to the commercial trade in human organs, tissue, and reproductive capacity. Mr. Carney, who once lived in Chennai, India is also the author of a forthcoming book and  blog of the same name.

The Red Market. Image from Amazon

I like Mr. Carney’s work, though I disagree with his belief that the organ trade in India is mostly driven by demand from rich American patients and could be curbed by forcing all Americans to donate their organs upon death. (More on that in a future blog post.)

The Red Market article is misleading in two very disturbing ways. Scott Chaney and Wired describe the exploitation of the poor in less developed nations.

“The problem is, demand for replacement flesh grossly outstrips supply. In the US and like-minded countries, it’s illegal to sell body parts–they can be taken only from those who filled out a donor card before they died or who are willing to give up an organ out of sheer benevolence. This means there isn’t enough tissue to go around. So, as with any outlawed or heavily regulated resource, a bustling underground trade has formed.

“Sometimes the market in body parts is exploitative: Desperate people are paid tiny sums for huge donations. Other times it is ghoulish: Pieces are stolen from the recently dead. And every so often, the resource grab is lethal–people are simply killed for their organs. Welcome to the red market.”

The paragraphs above leave the impression that these gruesome activities are commonly practiced in the U.S. They are not. Organ trafficking is outlawed in the U.S. by the National Organ Transplant Act of 1984. No hospital or surgeon in the U.S. would dare violate the law and lose its accreditation or go to jail (despite what you see on TV night-time soap operas). Outside the U.S., transplants that are suspected to exploit the donor are prohibited at any hospital that abides by the Declaration of Istanbul which denounces transplant tourism.

The story is followed by six pages listing the price of various types of transplant surgery in the U.S. Unfortunately, the data is illustrated using price tags. Thus, the reader may assume the price is for the organ only. Further, they may get the impression that there is an active black market for organs in the U.S. There is not.

By mixing practices in India with the U.S. and making it appear that organs are sold in the U.S., this popular magazine may deter rich Americans from donating their organs. This is the exact opposite of what needs to happen for the global organ shortage to be mitigated. Damn you Wired!

Photo by Christian Weber and illustrations by Istvan Orosz for Wired

What has me really worked up is that this isn’t the first time that Wired has sensationalized the organ shortage by featuring the prices of organs. In April 2007, it published a map showing the black market price of various  organs in several less developed countries. Gore may sell magazines, but it doesn’t help any patients get off the waiting list.

[Update: Added link to the article.]

This is the conclusion of the story (see part 1 and part 2) featuring Paul Brown and David Allen, who were coworkers in Denver. Paul donated a kidney to David after David was suddenly diagnosed with kidney failure or end-stage renal disease (ESRD). The transplant was successful, but David began losing kidney function. He describes the problem.

“The [immunosuppressant] drugs they gave me left me vulnerable to catch a cold or infection. I was constantly getting colds. And that often turned into pneumonia and I’d go into the hospital.

“Eventually, my new kidney started to fail. But it wasn’t due to rejection, though. It turns out I have a type of glomerulonephritis. Whenever I catch a cold or have some other infection, the nephrons in my kidney close up, causing reduced kidney function. When the infection is over, the function returns, but there is scarring, so it doesn’t all come back. And my blood pressure rises.”

High blood pressure, even for short periods, puts stress on the kidneys. The cycles of infection, scarring, and rising blood pressure took their toll. Despite a change in medication, David suffered from irreversible loss of kidney function and was again diagnosed with ESRD. He went back on the transplant waiting list in 2005.

Luckily, he was able to find another donor. This time, it was his younger brother Jamie. He is tall, like David, making his kidney a better size match than Paul’s, although there is no evidence that having a smaller kidney had any adverse impact on David’s health. Jamie had offered to donate a kidney for the first transplant, but had been ruled out by the University of Colorado Hospital as unsuitable to be a donor. David explains why.

“Jamie sometimes faints, a condition called neurocardiogenic syncope. That’s why they rejected him the first time. We finally get a cardiologist to sign off saying that his condition is not a health risk. This time we’re going through Presbyterian St. Luke’s Medical Center, though I don’t know if that made a difference. So we do the [HLA] crossmatch, and he turns out to be a perfect match. Usually, that’s a good thing. But in my case the doctors were worried that his kidney might be susceptible to my condition.”

David and Jamie went in for their transplant surgery on August 1, 2007, which happened to be David’s 44th birthday. Since the transplant, David has been on a different regimen of immunosuppressant medication that takes into account his glomerulonephritis.

“I’ve had a lot fewer colds and there’s been no loss in kidney function. His [Jamie’s donated] kidney hasn’t been affected by my disease.”

David Allen with beer in hand. Photo by Julie Brown

Here are some final words from David.

“I never asked anyone for a kidney and I wouldn’t do that. Some people say that your life changes after a transplant. I certainly live the best life I can, knowing that I’m on borrowed time, courtesy of someone else.”

This is a continuation of the story of two of my former coworkers at Quark, David Allen who was suddenly diagnosed with end-stage kidney disease and Paul Brown who donated a kidney to David.

On May 14, 2000, David and Paul checked in to the University of Colorado Hospital in Denver for their separate surgeries. In the morning, just prior to the start of surgery, Paul remembers being on a gurney in a hallway outside the operating room after being sedated. He recalls seeing David prior to being rolled into their adjoining operating rooms. Says Paul,

“I think I was making some jokes and he was laughing. But that may have been a hallucination.”

Paul’s donor nephrectomy (kidney removal surgery) was done laparoscopically, which involved a single 5-inch lateral (vertical) incision in his abdomen through which the kidney was extracted and two smaller incision for inserting the instruments and a camera. Once Paul’s kidney was recovered, it was cleaned and taken the operating room where David was already prepped to receive the kidney. Paul’s surgery was completed and he was taken to a post-anesthesia care unit (PACU) a few hours before David’s surgery was finished. Despite completing his surgery first, Paul recalls that he spent more time in post-operative recovery than David before being taken to his room.

“After waking up, the pain was so intense. It was unbelievable. The morphine didn’t help. David and I shared a room. I remember he was already in the room and coherent when I came in. He looked a lot better than me. Pretty soon, they [the hospital staff] wanted us to get up and walk around. It wasn’t a long walk, that’s for sure. Maybe once around the floor. It took us a good ten minutes. A shuffle walk, 3 or 4 inches at a time.”

Paul was out of the hospital after three days and was back to work in two weeks. He continues,

“There’s a big difference between being able to get to work and sit at a desk and getting back to normal. Prior to surgery I was skiing every weekend, hiking, and playing soccer. [When I went in to get tested,] the doctors were quite surprised by how low my pulse was and by my low blood pressure. [After the surgery,] I was really shocked how long it took for me to get back to normal. I didn’t have the lung capacity. It was like I was out of shape. I would say I eventually got back to normal a year later. [Since then,] I haven’t felt limited in any way though.”

Paul says that he’s had a full recovery and that he almost never thinks about his kidney surgery. In fact, he had forgotten the advice to avoid large doses of ibuprofen, which has been linked to kidney toxicity.

“I pulled a muscle and been taking a lot of Advil recently. I went to my doctor and he said, ‘You shouldn’t be taking that. You have a wife and two young kids now. You’ve got to be more careful.’ And wow, it finally hit home that I have to pay attention to this.”

Paul, his wife Julie, and their two daughters. Photo by Paul Brown (using timer)

David’s recovery took about a month and says he felt much better than before his surgery while he was on dialysis. However, he was not fully healthy as the immunosuppressant medication he is required to take to prevent organ rejection made him susceptible to infections. Despite it all, David says he doesn’t know what his life would have been like if Paul hadn’t offered his kidney.

Next, David has a setback and a new prognosis.

[Update: Removed quote about Paul’s serum creatinine since it is not a health factor for him. More about kidney function after a donation in an Apr 2011 blog post.]

I distinctly remember how I first learned about unrelated donor transplants. In the late 1990s I was working in Denver at Quark, Inc. when one of my coworkers offered to donate a kidney to another coworker. I didn’t even know that someone unrelated to the recipient could donate a kidney. Their mostly positive experience is a major reason why I become a nondirected donor.

The story start with David Allen, who in the fall of 1999 was a product analyst at Quark. David is a big guy, about 7-foot tall, a former pro baseball prospect who was still very athletic. He describes the events leading to his diagnosis of end-stage renal disease (ESRD).

“I first noticed a problem while playing [recreational league] baseball. I was losing my eyesight and had trouble reading pitches. It progressively got worse. One day a ground ball came to me. I missed it and turned around and I couldn’t see it. I turned my head and I could see it in my peripheral vision, but if I looked directly at it, it disappeared. I told the coach I have to take myself out of the game. I was pretty concerned at that point.

“I already had an appointment with the optometrist for the next day. He said, ‘I can work on your eyes, but I want to send you to an internist.’ They were in the office next door.”

One of the doctors checked David’s blood pressure, it was 275/175. A systolic/diastolic blood pressure between 110/65 and 130/85mm Hg is considered the optimal range. 210/120mm Hg is considered Stage 4-very severe. David’s blood pressure was significantly above that. His loss of eyesight was a side effect of high blood pressure known as hypertensive retinopathy.

“They took some blood samples and asked me if I wanted to go home or check into the ICU. At that point, I was in bad shape. I’d lost 75% of my vision. So I went in [to the hospital]. He [a nephrologist] later told me, ‘Your creatinine is 14. You have end-stage renal failure.’”

The optimal serum creatinine level for an adult male is between 0.7 and 1.2 mg/dl. (For women, the optimal range is lower, from 0.5 to 1.0 mg/dl.) A level of 10 or higher indicates kidney failure and requires immediate renal replacement therapy, either dialysis or a transplant, to avoid death. David continues,

“I saw a really badly produced video about kidney disease. They wanted to put me on dialysis then, but my blood pressure was too high. Finally, after a week of treatment, my blood pressure is still high, but they put me on emergency dialysis.”

Getting an offer of a kidney

Another of my coworkers at Quark, Paul Brown, saw how kidney disease was taking its toll on David. He recalls how he made the decision to get an HLA crossmatch test, one of the first step to becoming a donor.

“I don’t remember him [David] ever being sick. He was just fine one day and the next day we heard he’s in intensive care. Certainly after he came back to work, I noticed a change. He was dependent on dialysis. I was working closely with him on a couple of projects and he was gone three days a week for treatment. It was pretty disturbing, thinking about what his life was going to be like.

“I knew he was hoping to get a transplant. He mentioned that some of the guys on the baseball team were thinking about getting tested. So I decided to get tested too.”

David remembers the events a bit differently.

“One day as I was leaving work to go to dialysis, Paul asked me for the phone number of the center. He had just been promoted to assistant product manager and I thought he wanted the number so he could call me with questions about work. But I didn’t want him bothering me, so I said ‘no, I’ve got to leave now.’

“The next day he asked again. And I still thought he was just being pushy. So asked him what was so important that he wanted the number of the dialysis center. And he said, ‘not that number, the number for the transplant center.’ He wanted to get tested.

“I said, ‘Are you sure you want to do this? I mean, sure I want your kidney. But don’t do it if you want to be a hero. You have to realize how serious this is.’”

Paul went in and began the donor process. Like most people who volunteer to donate, he was unfamiliar with the evaluation process. He also wasn’t expecting to be accepted since David’s own brother had been tested and rejected. However, it turns out Paul was a good match for David. He was blood type compatible and HLA crossmatch compatible. In fact, out of the six major human leukocyte antigens, Paul was an identical match for two of David’s. When Paul learned he was a good match, he was surprised.

David Allen (left) and Paul Brown after their successful surgeries. Photo by Julie Brown

Every person who makes the decision whether to donate a kidney takes a slightly different path. Most people, even if they know someone with kidney disease, never think about donating. So the decision never gets made. But once confronted with the decision, there are lots of reactions. Some people make the decision instantly, based solely on their emotional ties to the recipient, without regard to the medical consequences. Others take more time, talking to friends and family before making their decision. A few spend time poring over medical research before deciding. Paul jokingly describes how he made his own decision.

“It’s kind of funny. I never made the decision to donate. I just went to get tested and figured that would be it. But then I matched and so I went to the next step. And then the next, and so on. Then I woke up and I was down one kidney.

“I never sat down and did any research on it [kidney donation]. I put my faith in the medical crew that if they say ‘yes, this is something you can do’ then they must think it’s acceptable. I never felt I couldn’t trust them.”

There was another reason that Paul knew he should continue with the donation process. Paul is tall, about 6’-2”, but is still ten inches shorter than David. Like other organs, kidney size is related to height. And ideally, a transplanted kidney’s volume should be similar to the recipient’s original kidney. This put Paul’s kidney at the lower end of the range of the ideal kidney volume for David. Says Paul,

“I remember thinking at the time that with his [kidney size] restriction, his chance of finding a suitable donor was next to zero.”

The next blog entry discusses the day of the transplant.

As mentioned in a Nov 2009 blog post, the United Network for Organ Sharing (UNOS) has been working on a pilot program to conduct its own kidney exchange. The program, under development for over a year, announced in Feb 2010 that four existing kidney exchanges had been selected to participate

• Alliance for Paired Donation, APD (Maumee, OH)
• Johns Hopkins Hospital (Baltimore, MD)
• New England Program for Kidney Exchange, NEPKE (Newton, MA)
• UCLA Medical Center (Los Angeles, CA)/California Pacific Medical Center (San Francisco, CA)

On Oct 27, 2010 the UNOS conducted its first match run with a pool that contained 40 pairs from the four participating centers. It resulted in two 2-way matches and one 3-way match (total of 7 transplants) offered to the participating hospitals. One of the 2-way exchanges was accepted and resulted in two transplants that took place on Dec 9.

A second match run was conducted on Dec 8, 2010. That pool contained 62 donor-recipient pairs and resulted in  four 3-way matches (12 transplants) offered to the participating hospitals. It appears that none of the offers were accepted. The next match run is scheduled for Jan 19, 2011.

In an article in amednews Jan 2011, Alvin Roth, a Harvard economics professor and one of the founders of NEPKE says,

“It’s nice that the [UNOS program] got going in a preliminary way, but it’s got a long way to go before it’s a big exchange. They’re working now on a very small-scale. The promise of a national exchange is there will be really lots of donor-patient pairs. We have to work to make that happen; it won’t just happen automatically.”

One of the reasons that the UNOS exchange is not providing as many matches as some other kidney exchanges is because it has more stringent criteria regarding which donors and recipients may enter the pool. A future blog post will describe the major kidney exchanges and compare their entry and matching criteria.

Look at all the pretty circles. Image from Chron. Higher Educ.

by George Taniwaki

A front-page story in Chron. Higher Educ. Jan 2011 claims that newly elected Republican governors are more likely to cut spending than Democrats or even incumbent Republicans. Since education (which includes both K-12 and higher ed) is one of the largest components of state budgets, this implies that the higher education expenditures will fall in states where governors plan to make budget cuts.

As evidence, the article contains the graphic shown above. It plots total projected budget shortfall in 2012 for six states and their higher education appropriation in 2010.

There are so many problems with this graphic that it is hard to know where to begin. But I will try to critique it.

1. The most serious problem is that this chart displays a meaningless comparison. There is no a priori reason to believe that higher-education appropriations in FY2010 and total projected budget shortfall two years later in FY2012 should be correlated. Nor should one expect the two numbers to be about the same size. My guess is the fact that the two numbers appear to be the same magnitude for these six states for these two years is just a coincidence.

2. The chart should include more years. If expenditures and budget gap are correlated, then the relationship should be stable over time. Prove it by showing time series data of total budget and higher-education appropriations during previous years. It would be even better if data from previous recessions was available. My guess is that the numbers vary greatly and the relationship disappears.

3. The chart should include more states. The article and the chart predicts newly elected Republican governors will cut higher education budgets more than other classes of governors. But the chart only shows data for six states with newly elected Republican governors. There is no comparative data for incumbent Republicans or any Democrats. Again, if the relationship is due to party affiliation and incumbency of governor, then showing data for all states will emphasize it. My guess is such data would show there is little or no relationship between governor status and budgets.

4. The chart should be adjusted to aid comparisons. The size of state budgets and higher education expenditures vary because of many factors. At a minimum, the data should be adjusted for population. A few other possible adjustments that come to mind are median household income, population of 18-25 year olds, proportion of population with college degrees (presumably, grads will be more likely to favor higher ed spending), enrollment at in-state public colleges (presumably parents of current students will be more likely to favor higher ed spending), etc.

5. The chart should not use areas to represent linear values. Look at the two circles under Ohio. The red circle representing the budget gap of $3,000 million is more than twice as large as the orange circle showing the higher education appropriation of $1,900 million even though $3,000 million is less than 60% bigger than $1,900 million. That’s wrong. The area of a circle is proportional to the square of the diameter. One of the basic rules of drawing a graph (for example, see Edward Tufte’s The Visual Display of Quantitative Information) is to make sure the size and shape of data markers actually assist in understanding the values being measured.

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My proposed improvement to the original chart is shown below. The data come from the same sources used in the Chron. Higher Educ. chart, state budget gaps from the Center on Budget and Policy Priorities, state higher education expenditures from the  Illinois State Univ. Grapevine Project, and political alignment from the Nat. Conf. State Legis. I also added U.S. Census annual estimates of population and U.S. Census counts so that I could calculate per capita state budget gaps and higher education expenditures. The data are posted on SkyDrive in case you want to create your own charts.

My scatterplot shows the cumulative budget gap per capita at the end of FY2009 for each state on the horizontal axis and the increase or decrease in higher education expenditures for state monies (excludes federal stimulus monies) from FY2009 to FY2010. My hypothesis is that deficits at the end of one fiscal year may impact changes in expenditures in the following year.

Each data point is colored to show the political affiliation of the governor (using blue for Democrat and red for Republican). The marker shape indicates if the party changed hands (triangle) or if it did not (square or diamond) in the 2010 election. The green line shows the least squares line through the data (not weighted for state population).

Look at all the tiny dots. Chart by George Taniwaki

I didn’t spend much time analyzing this chart but a few things caught my eye. First, the slope of the regression line is negative meaning that states with the largest deficits tended to cut education expenditures the least. Specifically, California, with the largest deficit at the end of 2009 at $1,004 per capita actually increased higher education expenditures in FY2010 by $7 per capita.

Second, the states with the largest budget gaps at the end of FY2009 were more likely to have Republican governors. They were also more likely to elect a Democratic governor in 2010. The three states that fit this pattern are California, Rhode Island, and Connecticut.

Finally, the states that made the biggest cuts in higher education expenditures in FY2010 were more likely to have a Democratic governor. They were also more likely to elect a Republican governor in 2010. The three states that fit this pattern are Wyoming, Iowa, and New Mexico.

It could be that these correlations are spurious. But my conclusions are no more unreliable than those claimed based on the weak analysis in the original chart.

Much thanks to Susan Wolcott who pointed out the original chart to me.