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Covid-19 update #2

My uninformed monitoring of the daily flow of COVID-19 data generated the following observations and questions:

Efforts to increase testing. Governor Walz’s effort to ramp up Minnesota’s testing is showing results. But Minnesota (as of 4/28) remains mired in 42nd place (out of 50 states and DC) in testing rates on a population-adjusted basis, not that much different than before Walz’s announcement. The “moon shot” program was unveiled on April 22nd. We have six reported days of testing data since then.  (To be fair, they said it might take up to two weeks to see results. So, a bigger surge may be coming.) During April before the announcement, the average daily number of tests was 1,344. Since the announcement, the average daily test rate increased to 2,414, an impressive 79.6% increase.   In the same period, the average daily testing in the US also increased by 18.5%.  Minnesota remains 55% below the national rate.

Troubling trend in the percentage of tests that are positive.  As testing ramps up, one expects the percentage of positive tests to decline. That naturally follows from the idea that when testing was scarce, medical professionals using the state’s testing rubrics would administer tests to individuals with the high probability of being infected. As testing increases the percentage of positive tests should drop.  The reverse appears to have occurred.  During the April 1st to 22nd period, 7% of tests were positive, while for the following days with the higher testing levels (noted above), 10% were positive.  With my amateur background, I cannot think of an explanation for that and have not heard a rationale for it reported. The 6-day period of higher testing, of course, may simply be too small a sample to mean anything.  But eyeballing the data, even before the big ramp-up, the percentage of positives was increasing even as the number of tests increased. Weird.

Minnesota’s low case rates are probably misleading.  Minnesota continues to have low numbers of detected cases (only 6 other states have fewer on a population-adjusted basis).  But among the ten states with the lowest detected numbers of cases, Minnesota has the second lowest testing rate (only North Carolina is lower). Most of the states have much higher testing rates; Minnesota’s rate is about 40% lower than the 10-state average. The most reasonable conclusion is that Minnesota likely has proportionately more undetected cases than the other states with low numbers of reported cases.

Minnesota’s extremely high case fatality rate (CFR).  Perhaps most puzzling to me, Minnesota’s CFR (deaths from COVID1-19/positive cases) is the third highest in the nation.  Only Connecticut and Michigan, hot spot states each with more than 2,000 deaths, are higher.  Oklahoma, the number 4 state, has a CFR quite a bit lower than Minnesota’s.

The anomaly can be illustrated by comparing Minnesota with our sister state, Wisconsin.  Both states have similar populations (Wisconsin has about 200,000 more people than Minnesota) and similar numbers of COVID-19 deaths (Minnesota had 301 and Wisconsin 301 as of April 28th).  But Wisconsin has many more cases (6,289 compared to 4,181 for Minnesota).  Thus, although Wisconsin has more than 50% more cases than Minnesota, both states have about the same number of deaths. 

I have not seen a discussion of Minnesota’s unusually high CFR; much less a rationale for it. I can come up with conjectures, but I have no idea as to their potential validity:

  • It is possible that Minnesota’s SARS-CoV-2 exposures have been concentrated in places with many more individuals who are particularly susceptible to dying from the virus (think nursing homes and assisted living facilities) more so than in other states.  Residents of these facilities are older and have health conditions (heart disease, high blood pressure, etc.), which make them more susceptible to the virus.  That is true nationally and the media have reported large outbreaks in nursing homes and assisted living facilities in Washington, New York, New Jersey, and so forth.  Why would Minnesota’s exposure be particularly concentrated in those facilities? I can’t think of a good reason.
  • Minnesota’s elderly care facility management practices may have contributed in some way – i.e., more Minnesota nursing home or assisted living facility residents are allowed to be exposed and/or when they are exposed succumb than in other states.  This is just a wild conjecture on my part.
  • Minnesota’s lower testing rates probably contribute – particularly if the state has targeted testing to those who have the highest potential fatality rates (again those in the facilities). I think that has been the case. We are likely testing fewer individuals with low mortality risks than other states that are either (1) running more tests or (2) not targeting their tests as narrowly to high risk populations as Minnesota is.  But no other low testing state has a high CFR like Minnesota’s.
  • Maybe Minnesota’s suppression techniques have been more successful in preventing those who have lower mortality risks from being exposed.  More low risk individuals (e.g., those who are young and highly active or mobile) will likely be exposed in states with no or looser stay-at-home orders or cultures of respecting those directions. This conjecture also seems improbable to me.

In any case, it’s a mystery to me and I hope someone with actual expertise comes up with a good explanation that is published.

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Son of recovery rebate

More media coverage of the recovery rebate (a/k/a stimulus checks, economic relief payments, or whatever):

  • ProPublica story on how (surprise, surprise!) the website that Intuit “volunteered” to create for the IRS to help nonfilers and others get their banking and other information to IRS for recovery rebate administration purposes appears to be structured to make money for Intuit. My observation is why should anyone expect otherwise? Intuit is a for profit corporation whose goal is to make money for its shareholders (and indirectly executives and employees). If we really want to provide free filing, the government needs to do it directly and robustly or you inevitably will get these effects, the same as has occurred with the free file alliance.
  • Janet Holzblatt’s post (I really like her perspectives on tax administration and compliance issues) on what to call the payments. I had earlier mentioned my surprise at Congress calling them recovery rebates; she takes it to the next level.
  • NY Times story on how scammers are taking advantage of the program. The article cites some preliminary evidence that the program is providing a field day for fraudsters. It includes the following quotes: (1) “Security experts said that the I.R.S. had opened up the door to fraud by requiring so little data to claim the money. “The stimulus site is a little bit like ringing the dinner bell for hackers,” said Brian Stack, the vice president for dark web intelligence at Experian.” (2) “This is El Dorado for hackers and pure hell for the victims,” said Adam Levin, the founder of CyberScout, a firm that helps companies protect against and manage identity theft.” Part of the latter was used as the piece’s headline “Pure Hell for Victims,” which seems appropriate.
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COVID testing

General media sources, such as the NY Times, have started posting population-adjusted COVID-19 case and testing data. So, I’m no longer going to do it.

The big question I have, which so far I have not seen addressed by media coverage, is why Minnesota’s testing rate is stagnant (slightly dropping, actually). As I track the data, many other states are ramping up testing, while Minnesota testing rate is not. Minnesota continues to have low case numbers (fourth lowest state on a population-adjusted basis, only Montana, Hawaii, and Alaska are lower), but that ranking is probably meaningless given that Minnesota is testing at about 2/3 the national rate. (Three weeks ago it was close to the national average.) The natural conclusion is that Minnesota’s low case numbers are too low, compared with that in other states with higher testing levels.

The graph below shows the daily number of tests reported by MDH for April, which reveals – despite the day-to-day fluctuations – a consistent, slight decline since the first part of the month.

This is particularly troubling because robust testing is crucial to further loosening of the stay-at-home order and allowing more normal economic and social activity. Something needs to change and the sooner the better.

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CARES Act – PPP paradox

A popular provision of the CARES Act is the Paycheck Protection Program (PPP), which makes forgivable loans to small businesses and nonprofit entities. The $349 billion appropriation for the program has, according to media reports, already been exhausted and Congress is haggling over appropriating another $250 billion. Democrats are insisting that money for hospitals and state and local governments be included, but no one appears to be arguing not to allocate more money to the PPP.

So what is the paradox? These loans are intended to allow the recipient businesses and nonprofits to continue paying their employees. The law requires loan proceeds to be used for payroll, rent, utilities, and mortgage interest to qualify for forgiveness. Public Law, 116-136, sections 1102 – 1106. Hence, the name “paycheck protection” I assume. Under standard tax law principles, loan forgiveness is taxable. That follows from the fact that the loan principal was excluded from income because it was exactly offset by an obligation to repay. So when that obligation is forgiven, the proceeds become taxable. The CARES Act, however, provides that forgiveness of PPP loans is excluded from taxable income. Section 1106(i).

So, the paradox is why did Congress include this exclusion? To me it seems unnecessary and simply a complication of tax administration and compliance. That is so because the law requires the loan proceeds to be used exclusively for deductible items – payroll, rent, and so forth. So, if Congress had left matters alone, the loan forgiveness would have been exactly offset by deductible expenses. Does that mean that these businesses will be able to both exclude the income and deduct the expenses as a result, thereby getting a nice tax spiff? No, because the IRC section 265 explicitly disallows that. (Minnesota law contains a comparable provisions, Minnesota Statutes, section 290.10.)

I assume Congress thought it was making matters easier by adding the exclusion. My instinct is that the reverse is the case. True, it makes it easy for the taxpayer to exclude the loan proceeds from taxable income when the loan is forgiven. But then the business must take care to exclude the expenditures of the proceeds from its business expenses, which may have occurred in a prior tax year. It’s not clear to me why that is simpler than excluding the loan proceeds from income. (As usual, I could be wrong and there is some simplification I’m missing.)

What happens if a business cheats and takes out a forgivable loan that it does not use for a qualifying purposes and SBA does not catch the violation, but the IRS does? I assume that the IRS can compel the business to recognize the loan forgiveness as taxable income, but I would guess that could lead to wrangling, potentially in tax court, about the terms and intent of the statute and IRS authority under it.

In any case, this is a provision for which a failure by Minnesota to promptly adopt conformity legislation won’t make much difference in actual tax liability (if any), but rather will create compliance headaches for taxpayers. Conformity legislation on this should be scored a zero, as it apparently was federally (nothing appears in the JCT estimate, so they must have concluded there was no timing effect).

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Books I’ve read recently – The Price We Pay

This is another in my series of bad high school book reports on nonfiction books that I have read recently.

Name of book:

The Price We Pay – What Broke American Health Care–and How to Fix It by Marty Makary, (Bloomsbury Publishing 2019)

Why I read it:

This is the second in the series of books where I attempt to improve my understanding of the American health care system and health care economics. This book was a best seller and I was told that it was an easy read and interesting. So, I bit.

I had not heard of Makary, a Johns Hopkins MD with a national reputation as a cancer surgeon, who has authored several popular books on medicine and health care. This book is intended to dig into and reveal the “business side” of medicine and its problems. It’s a dramatic change from the first book I read in the series, Uwe Reinhardt’s book.

What I found interesting or worth writing about:

The book (Part I) starts with a collection of anecdotes or stories documenting problems on how American health care is delivered and financed. Makary pins responsibility for high health care costs in the US largely on a combination of:

  • Entities who provide care (e.g., hospitals, physicians, administrators, and air ambulance companies) and seek to maximize profits, often in ethically questionable ways, or who simply do not carefully and systematically follow best practices; and
  • Health care businesses, typically low-profile middlemen (PBMs, GPOs, insurance brokers, etc.), who use their positions in the complex US health care system to derive unreasonable profits in Makary’s view.

Oversimplifying things, Makary’s view is that the “health care cost crisis” is due to: 

  • Overtreatment and inappropriate treatment – lots of procedures or drugs that are, at best, unnecessary or inappropriate or, at worst, life threatening; and
  • Various forms of price gouging and other questionable business practices by various participants that are possible because of the lack of transparency in pricing, third party payment, and the proliferation of various middlemen (PBMs, GPOs, insurance brokers, etc.) in the complicated U.S. “health care system.”

His proposed fixes are a combination of prodding providers to work better and smarter (Part II) or to make pricing more open and transparent (Part III) so that providers and consumers of care make better informed decisions and gaming by miscreants is minimized. In short, his view seems premised on a notion that the market doesn’t work (too much is spent wastefully) because of a lack of good information by the people making the key decisions – patients and physicians – and that with more transparency on multiple levels and education this can be fixed.

The book’s strength is its readability and storytelling; its anecdotes make clear many of the flaws and fobiles that the structure of American health care finance and delivery systems have created. After reading it, you will have to conclude that is a quasi-private market system that is not functioning well.

What disappointed me about the book:

The book’s strengthen is also its weakness; it’s all about revealing the problems with system through compelling vignettes, but despite its subtitle (“and How to Fix It”) it really doesn’t propose in my judgment any realistic solutions.  All the things he proposes are sensible and probably should be done, but they will not measurably move the dial, at least in my judgment.

More troubling to me is his propensity to suggest that he is the one who discovered many of these stories, when in fact some of his specific examples appear to have been previously documented by the mainstream media, as my notes below suggest (e.g., NPR’s story on the helicopter ambulance business and the NY Times on the Carlsbad hospital’s pricing and debt collection, two of Makary’s anecdotes).  His lack of clear crediting of those stories seems borderline unethical (at least I did not notice him credit the stories, which appear to predate his personal experiences). They just happened to be ones that I was aware of and it made me wonder if most of his compelling stories had not, in fact, been dredged up by a research assistant and Makary, then, headed to scene to provide his first-person narratives.

In reading the book (a few months ago), I took notes on each chapter, which I haves copied below for anyone who wants the excruciating details.

Part I:

Chapter 1: Health Fair

The center piece example in this chapter is the use by vascular surgeons of health fairs at African American churches in the DC area to promote inappropriate and unnecessary use of angioplasty and stents in leg arteries. It is a pretty clear and outrageous abuse that is enabled by the fact that third parties (insurers, self-insured employers, or government programs like Medicare, Medicaid, and Tricare) pay for most health care in the US.  The subtext is when others are paying unscrupulous providers can easily use their authority, knowledge, and lay people’s deference to them to provide expensive and very profitable and unnecessary services.

Chapter 2: Welcome to the Game

This chapter delves into the bizarre pricing used in the US health care industry, where hospitals and other providers use a wide variety of prices – their “rack” price (or the “out of network” price that the uninsured individual who walks in off the street pays), various negotiated discounted prices charged to insurers, the Medicare price (set by the federal government), and the Medicaid price (set by some combination of federal and state government); these prices are typically opaque – i.e., not only are they not disclosed or they may be almost impossible to find out.  Doctors, nurses, and many administrators often do not know what the price is and cannot or will not tell when the question is asked. Makary tells the story of a French national who has a heart attack when he brought his son to college in DC.  The hospital tells him the price of a bypass surgery is $150K but starts cutting it when the administrator realizes that he will go back to France, where the price will be much lower. The final reduction to $30K is still higher than the French price and the Americans lose the sale.

My take: Makary finds price discrimination and opaqueness to a big indictment of the health care system. The typical person would likely agree. But how is that different from what occurs in other well-functioning, competitive markets? For example, the same charge could be made about how airline tickets and cars (new and used) are priced and sold – in both cases, there is rampant price discrimination (buyers of the same car or ticket paying wildly different prices) and a fair degree of opaqueness.[Note: MSRPs for new cars are an exception. I think the law requires that and there is no guarantee, though, that you can purchase a car for the MSRP if demand exceeds supply by a lot.] We don’t consider that to be a policy problem or a cause for government regulation.  Why is health care different? Makary never addresses that issue. It strikes me that analogizing from Lasik and cosmetic surgery to more general health care is fraught with problems – these are elective decisions for nonessential purposes (not like cancer treatment, e.g.) that are typically made occasionally by middle- and upper-income consumers.

Makary also uses the pricing of emergency room visits and surprise billing (when you discover one of the providers in your in-network hospital is actually out-of-network) and contrasts it with the way Lasik and cosmetic surgery is typically priced in a transparent way and patients/customers make informed decisions that take price into account.  The markets for Lasik and cosmetic surgery typically do not involve third-party payers – patients/customers pay cash. These markets probably are effective and well-functioning. But unlike most health care these services are discretionary, nonemergency, and the quality of their results are more easily evaluated by informed lay persons. I consider them to be more like getting a haircut than treating your cancer, so I think his analogy is not very apt.

Chapter 3: Carlsbad

This chapter details how the only hospital in a small city (Carlsbad, New Mexico) uses a combination of high prices (probably common for hospitals for their out-of-network patients) and routinely sues patients who fail to promptly pay their bills.  Many of his example patients have insurance, but still cannot pay. The hospital regularly sues them, gets de fault judgments, and, then, garnishes their wages. The folks in his examples are typically working poor or low-income individuals. He does not say this, but I assume the increases in deductibles and the spread of “high deductible” HSA plans probably mean that more people with insurance have very large medical bills as a result of these high prices and end up in medical debt as a result.  (The hospital in the next closest city – still far away since this is NM – has lower prices, he notes.)  He details this in a colorful way and finds that the hospital (part of a for-profit chain) is probably not an outlier. 

This tendency of health care providers to sue nonpayers and garnish wages has been documented by the media. A recent Pro Publica story about Coffeyville, Kansas and the widespread use of the contempt power (i.e., the ability to throw nonpayers in jail) is particularly shocking.  This suggests that our health care system as it applies to low-income families who do not qualify for Medicaid is verging on becoming Dickensian if it hasn’t already crossed over to that in some states or localities.  In fact, the NY Times covered the exact example Markey uses (Carlsbad New Mexico) in a 2015 story.  This is another instance where Markey creates the impression that he has uncovered an example that previously was the subject a national, mainstream media story.

Chapter 4: Two Americas

This chapter documents that Carlsbad practice (high prices, suing patients that do not pay, and garnishing wages for nonpayment) extends to the nonprofit sector as well.  Makary notes that this tends to hit lower-income workers (of course) – hence, the chapter title (Two Americas).

My take: He draws examples from Virginia (close to Hopkins’ home in Baltimore), rather than Maryland.  Maryland (a blue state) opted into ACA’s expansion of Medicaid; Virginia (Republicans controlled state government or had a veto over opting in) did not. He says nary a word about Virginia’s failure to opt into the ACA’s expansion, although I suspect you could find similar examples in Maryland. But for those with income below the ACA’s Medicaid limit, this is the elephant in the room, in addition to the inexorable movement to high deductible plans. If Virginia had opted in, I assume the effect for these folks (unclear how many of Makary examples, though) would be to (1) constrain the high prices, because Medicaid would dictate them and (2) eliminate the problem of suing the working poor for nonpayment.  Of course, it would do nothing for people with incomes above the Medicaid income limit and high deductible policies.

Chapter 5: Ride

This chapter details another niche of excess in American health practices: the excessive use and high pricing of air ambulances (helicopters) that is spawned by the system of third-party payment.  Of course, the fact that the ambulance is often “out-of-network” or not covered by government plans (Medicare, Medicaid, or Tricare) means yet more medical debt and financial pain for ordinary folks. Again, the media (e.g., NPR story about high prices) has documented this phenomenon; see this NPR story about how the problem (high prices that often fall on the individual, rather than an insurer or government plan) has led to a subscription model with its own abuses.  Makary doesn’t discuss that angle.

My take: Wasteful air ambulance use, excessively high prices, and too many providers undoubtedly push up overall health care costs and bankrupt individuals who get caught in the trap of using them unnecessarily. In the larger scheme of things (i.e., relative to total national health care expenditures), the effects are trivial. But measures should be taken to mitigate the effects. State laws dictating that the maximum price is some percentage of the Medicare rate (125%?) would likely do the trick, but good luck getting that through state legislatures.

Part II: Improving Wisely

Chapter 6: Woman in Labor

This chapter is the first in the second section of the book, which focuses on how to improve health care practices. It focuses on inappropriate use of C sections, a widely recognized problem that varies a lot from place to practice and practice to practice.  C sections have the twin problems of high cost and poor outcomes (when done unnecessarily). Makary leads with an anecdote about “Dinner Doctor,” a physician who performs C sections to accommodate his (one assume only a male would do this) personal schedule (being home in time for dinner) and more generally how C sections performed rise on Fridays, etc. He extends the examples to include unnecessary use of blood transfusions and, one presumes if you knew more about medical practice, many other instances could be found. Much of this is unconscious, due to inattention, reflects poor management, etc. He suggests sensible management techniques (e.g., peer comparisons to nudge physicians to improve) for making improvements.

My take: Similar inefficiencies are likely found in all sectors of economy, including ones subject to more competitive market pressures than health care providers. But the fact that the health care is pretty much immune to competitive evaluations of relative prices and quality likely makes it worse – just a guess since measuring this would seem to be incredibly difficult, if not impossible. The fact that physicians are subject to professional ethics and that his examples imply compromising them makes the examples seem more outrageous.

Chapter 7: Dear Doctor

This chapter extends the previous chapter’s discussion by describing similar problems with a common technique for removing skin cancers (referred to by the acronym MOHS). This involves removing skin cancer, doing a biopsy to determine if the surgery got all the cancer (are there positive margins?), and if not repeating the process.  The physician is reimbursed at a higher rate if the process is required to be repeated, not surprisingly because more time/work is required. Statistical analysis shows that some doctors consistently do multiple procedures, receiving more compensation (and causing more pain for their patients) – i.e., they are at the right tail of the distribution. One assumes that this is unconscious and reflects inattention, poor technique etc. Marary’s point is that simply informing physicians of how they are doing relative to their peers will stimulate significant improvements – better outcomes at lower cost. That may be the case simply because it stimulates physicians to work harder or smarter or because they have been consciously or semi-consciously been gaming the system and now fear they will be fingered (Makary doesn’t say the latter).

My take: This seems an obvious thing to do, but the current pricing model does not encourage it and rewards looking the other way. A natural question is whether the pricing should be changed to increase the basic price and not paying more for excising additional blocks of tissue. One would need to be an MOHS expert to judge if that makes sense (e.g., would it lead to counterproductive excising of too much on average, are some situations more prone to judging how much to excise so that some practitioners would be systematically disfavored, etc.?) or how to do it.

Chapter 8: Scaling Improvement

This chapter details more opportunities for curtailing expensive overtreatment – elective back surgery, lumpectomies for breast cancers, etc. He concludes “That overtreatment penetrates most corners of medicine.” (p. 120)  He does concede that many of the suggestions that he got from fellow physicians for improvements would not have been so easy to implement (as his examples are) because they did not lend themselves to clear measurements or agreements by the professional groups (maybe for political or other reasons?).

My take: In general, one of Makary’s consistent themes is that overtreatment (too many procedures) is a major cause of our high health care costs. I am sure that large savings could be realized by reducing the unnecessary services (in the billions every year, I am sure).  But international comparisons, per Reinhardt (“It’s the Prices, Stupid”), suggest that numbers of procedures do not explain why the US spends such a larger share of its economic output on health care than other developed nations.

Chapter 9: Opioids

Makary discusses how he and other surgical practices inattentively over prescribed opioids – as I read it, this occurred, because they never really bothered to put much effort in rigorously determining what a good default rule should be based on the likely severity of the pain for varying types of surgery.  When the growing attention on the opioid crisis induced them to do this, they discovered that they were mindlessly over prescribing opioids. (The implication is that his Hopkins practice has addressed this, but many other surgical practices have not?) Obviously, this increased health care costs – probably the direct costs were modest, but if those practices really were major contributors to the opioid crisis (I have no idea whether that is true or not and if Makary does, he doesn’t provide any evidence of it) the social costs are immense and they probably contributed to growing health care costs, since opioid addicts likely consume a lot of health care and addiction yields many other personal and social costs aside from the burden on health care.

Chapter 10: Overtreating Patients Like Me

More details are presented on overtreatment using examples drawn from his personal (not professional) experience – using Nexium (a heartburn drug) and statins rather than making diet and lifestyle changes or recognizing that the risks being addressed don’t need to be.

This is the last chapter of the part of the book that largely focuses on medical practice dynamics and includes a bunch of quotes about how overtreatment is a serious (perhaps the most important?) component of the health care cost crisis.  Here’s a sampling:

In recent years, a plethora of studies have shown that doctors have been overtesting, overmedicating, and over-operating. (p. 144)

Overtreatment is not just a side issue in medicine. It is the root cause of our greatest public health crisis. (p. 146) [Note to be fair to him: this is not necessary about costs, since outcomes are involved too – e.g., the problem with opioids, antibiotic resistance, and so forth. He notes a Korean example of overtreating thyroid cancer.]

Makary cites estimates of overtreatment elsewhere in the developed world.  Since all other developed nations spend so much less of their economic output on health care, that may suggest (given Reinhardt’s point that it’s the prices) that overtreatment isn’t the explanation for the US’s spending so much more than everyone else. Rather, overspending is probably an international problem; perhaps it is simply inherent to health care – a combination of high demand (i.e., health care being a superior good) and the difficulty of evaluating what is a cost-effective treatment.  Marary describes even more outrageous examples of overtreatment in the developing world that verge on or clearly are outright fraud – providing unneeded treatment that at best is inappropriate and at worst is life threatening.

Part III: Redesigning Health Care

Chapter 11: Starting from Scratch

One of Makary’s general themes is that the health care business needs disrupting (following I guess the high-tech business cliché – Uber etc). He turns to the example of Telsa’s marketing practices – transparent pricing and no haggling, I guess (maybe coming around to my point that there are similarities between the price and selling of cars and medical care). He holds out a specific Arizona clinical practice model, IORA, as a disrupter.  Although he isn’t very explicitly about exactly how the clinic works, it appears to be a staff model HMO that uses capitation pricing and strongly focuses on attempting to move its customers/patients into a more cost effective (e.g., life style changes) treatment by relying on a team of providers who work collaboratively.

Chapter 12: Disruption

This chapter returns to the price discrimination theme – the example he uses is an out-of-network emergency room treatment of a friend (“Dina”). The fact that it is out-of-network means that the highest Chargemaster price will apply. The consent forms a patient must sign to receive treatment includes an agreement to pay whatever these prices are. [Note: This is where my analogy to pricing of cars breaks down a bit (a lot?) in that medical care is often purchased/consumed before the price is revealed at all. That is not the case with car and truck sales or with airline tickets. That element of health care purchasing is part of a broader point relating to the complexity and often emergency nature of individual’s health care decision making; when authorizing treatment, one may not know exactly or even generally  what treatment will consists of or what the alternatives are (much less any of the relevant prices), This is one of the reasons why the competitive market model, in my judgment, will always have severe challenges as a way to allocate efficiently resources to health care.]  (Makary thwarts this by making them print out the form and crossing out that portion of the agreement – not something that would be possible if she had signed it electronically. He knows that federal law requires the hospital to treat her.)  The price they attempt to charge her is, of course, ridiculously high ($60K for some sort of minor surgery for which the in-network price was $12K).

The disruption in the chapter title refers to an individual, Jeffrey Rice, who created a business, Healthcare Blue Book, like the Kelly Blue Book car pricing service. It publishes the various prices of health care prices for procedures charged by providers and sells services to self-insured employers who attempt to steer their employees to use lower cost providers by providing various incentives and disincentives. Makary cites a recently enacted Florida law which requires providers (some or all?) to publicly disclose what they are actually paid for procedures. In Makary’s view (p. 175) the difference between Chargermaster prices and what is received is “at the dark heart of health care’s cost crisis.”

Reinhardt’s book refers to Maryland’s all payer law – i.e., a state regulation that requires some providers to charge everyone the same price – Makary, despite practicing in Maryland and despite the fact that this is squarely on topic with his critique of price discrimination and lack of transparency, never even mentions this.  Not sure why – maybe because it is inconsistent with his bias toward “market” (rather than regulatory) solutions or because it is controversial (read: partisan or opposed by his fellow providers?).

Makary cites a “large Rand study” about consumer/patient behavior when individuals are not responsible for paying for the cost of health care services. He says this study found that they (probably perversely, although he doesn’t explicitly say that) opt for the more expensive services on theory that they are better –  there is evidence for this in other contexts (e.g., how consumers use price as a proxy for quality – automatically thinking that high priced wine is better is the example I remember).  Makary does not explicitly ID this study, but I’m guessing it’s the one done back in the 1980s summarized here.  I was not aware that it showed the perverse price effect that he cites – rather that it just shows that overall consumption drops some as prices rise.  A more recent Rand study of the ACA (addressing health insurance choices) is more optimistic.  He does not cite the NBER paper that Reinhardt relies on to reject the efficacy of using “skin-in-the-game” to constrain high health costs.

Chapter 13: Buying Health Insurance

This chapter focuses on brokers who sell insurance to employers and how the typical financial arrangements (i.e., the way insurers compensate brokers) create conflicts of interest and may/will interfere with the recommendations that brokers make to employers.  Makary advocates for a flat fee (I suppose more accurately a model where the advisor provides services to the employer and is paid for those services unrelated to the amount paid for or the type of insurance purchased). This seems sensible and is like the recommendation that individuals should not rely on financial advisors who receive commissions based on the investments or other financial products they buy but should rather hire fee-only advisors. Undoubtedly, the model he disparages likely drives up the cost of health insurance. The ACA attempted to address this by allowing small employer coverage to be sold on the exchanges. But I assume (w/o knowing) that that has not worked because of the complexity of the products and the relationships between brokers and employers (as Makary points out) causes most employers to simply relying on the brokers that they have always used and trusted (perhaps misleadingly). As an aside, Makary rarely discusses the ACA, even if it seems relevant to the points he’s making.  I assume that he is trying to avoid touching a political hot stove or he is a conservative Republican.

Chapter 14: Pharmacy Hieroglyphics

This chapter goes after Pharmacy Benefits Management (PBM) companies as another explanation for high US health costs. Again, Makary thinks their fees (the structures for which are opaque and complex) lead to conflicts of interest and drive up costs. This industry is concentrated, so oligopolistic (“obligopsopic” – making up a new word – since PBMs are purchasers not producers) behavior might be going on here. None of this is obvious to me – i.e., why PBMs drive up the prices, rather than help hold them down. I assume that the entities (employers or insurers) that contract with them are sophisticated and can judge whether they are getting value for what they pay. Makary largely fingers PBMs, rather than the drug companies themselves, who are typically considered a logical culprit for high drug costs.  They obviously have a legal monopoly (patents) and other methods for milking the system even after the drugs are off patent to maximize profits. Makary may simply perceive that (bad Big Pharma) is a well-accepted public narrative and he is trying to demonstrate that PBMs are also a problem? I am not convinced by his arguments.  I know that Big Pharma tends to point a finger at PBMs when their own pricing practices are questioned.

Reinhardt’s book has a good graphic (Figure 1.9; p. 35) that shows the nature of these arrangements.

Chapter 15: 4K Screens

Moving on to another miscreant who may be responsible for high costs, Makary takes on GPOs, entities that I was unaware of. They are General Purchasing Organizations and either directly or indirectly buy or select the medical supplies and equipment that hospitals and clinics typically purchase. Again, this is a concentration and monopsony type problem that, in his view, drives up prices and stifles innovation in medical supplies and equipment. Federal law apparently provides an exemption for them from anti-kickback rules, heightening his suspicions. This seems counter intuitive to me. I can see a myriad of reasons why there is market failure in delivering health care services (lack of information, third party payments, consumers who don’t have the knowledge or expertise to make informed choices, etc.), but most of those do not apply to institutions contracting with service providers like GPOs as he describes them.

Chapter 16: Diagnosis: Overwellnessed

In this chapter, Makary takes on the wellness industry, i.e., the army of consultants and providers selling “wellness services” to employers – i.e., companies who try to get employees to make lifestyle changes (stopping smoking, exercising more, improving their diets, and so forth). Studies have shown his point is well taken. He also takes on genetic and biometric screening as a problem of “fishing for diseases” that probably are best left untreated. As usual, he has some good examples. He points out the problematic practice of using these programs to collect health data that, then, is sold without the subjects being aware of it.

Again, I assume that the dollar amounts involved are peanuts in the larger scheme of things. I also assume that employers will wise up or maybe employees view some of these incentives as valuable compensation. But all this stuff does add up eventually. One must wonder whether there is something about the US health care system that makes it particularly susceptible to this stuff. Are other developed countries similarly wasting their money?

Chapter 17: The Words We Use

Here Makary addresses medical education and how (in his opinion) it wastes a lot of time and money on stuff that is not helpful to practicing physicians and how it fails to train doctors in some key skills that they need to succeed – being good listeners, working well on teams, being empathetic, etc.  My observation is that these complaints probably echo those made about other types of professional education (i.e., they are similar to what I regularly heard about legal education from lawyers and how law schools fail to teach many practical skills lawyers really need to practice effectively, leaving that to law firms).  He makes some good points obviously, but none of this is likely to bend the cost curve, as they say. [Note: I thought his ideas about screening potential med students for the desired personal qualifies after they meet minimum (but high) intellectual requirements make sense. But of course, then, potential students will start figuring out how to game those criteria, I suppose.]

Makary makes a more general point (as suggested by the chapter title) that word selection matters a lot and that the profession needs to talk more simply and clearly. Some of his specific suggestions puzzle me and some of them are clearly slanted toward his analysis of what is wrong with the system (i.e., paying too much to brokers, PBMs, GPOs, etc.).

Chapter 18: What We Can Do

His underlying prescription/theme is that if the health care system has more transparency in its pricing and responsibility many (most?) of the problems (high costs) would go away. “Most of health care can behave like any other marketplace in any other industry: it responds to customer demands for non-urgent services, which account for most health care services.” (p. 245)

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Legislative veto of emergency powers order?

I had not had cause to look at (as far as I can remember) the emergency powers statute under which Governor Walz’s issued his COVID-19 emergency declaration. After seeing in the STRIB that a handful of GOP legislators had attempted to overturn the order, I read the statute, section 12.31.

Subdivision 2, the portion of the statute authorizing peacetime emergency orders, is not clearly drafted. Paragraph (a) authorizes the governor to declare peacetime emergencies to address various conditions. It requires the executive council to approve, by resolution, a declaration that extends beyond five days “up to 30 days.” In other words, paragraph (a) does not authorize explicitly declarations longer than 30 days.

Paragraph (b), however, appears to contemplate longer duration declarations because it authorizes the legislature to “terminate a peacetime emergency extending beyond 30 days” by a majority vote of each house. (If the legislature is not in session, the statute directs the governor to call it into session so it can do so.) It must be this power to terminate that the GOP legislators were seeking to exercise.

The interesting question is whether that provision – i.e., authorizing the legislature to terminate a declaration on its own – is constitutional. I’m fairly certain is not. The governor’s act clearly is an executive act; he or she is assessing whether the appropriate conditions are present and, then, is invoking the powers under the statute. In other words carrying out or executing the law. The legislation could have explicitly time-limited that power to 30 days and caused the order to end at that point. That would have been constitutional. But that is not what the statute does.

Rather, it (apparently) allows the governor to make declarations longer than 30 days, but reserves to the legislature the power to end them by majority vote of each house. It would do this not in the way the constitution provides generally for the legislature to act – i.e., by enacting laws subject to the governor’s veto power. But rather by the legislature acting unilaterally to veto or negate the governor’s act.

Thus, the statute is attempting either: (1) to grant the legislature executive power (i.e., to reverse the governor’s executive action) or (2) to enact a law while circumventing the governor’s veto authority. In one case, the statute is unconstitutionally assigning executive power to the legislature. Powers the constitution assigns exclusively to the executive branch unless otherwise specifically provided. Taking the other view, the statutory procedure is effectively rewriting the constitutional rules for enacting legislation. Neither is constitutional.

The U.S. Supreme Court has held unconstitutional similar federal statutes allowing congressional vetoes of executive acts. INS v. Chadha, 462 U.S. 919 (1983) (one house veto of immigration action) is the leading case. Although Chadha involved authority for one house of Congress to veto an executive action, its underlying theory extends to two-house vetoes as well. Of course, it is a matter of interpreting and applying the Minnesota Constitution, so Chadha is not direct authority. But the concepts are directly parallel, the relevant constitutional provisions analogous, and it seems highly likely the Minnesota Supreme Court would follow the logic and reasoning of Chadha.

As an aside, when I was acting as legislative counsel, I hated dealing with provisions like these. They were pretty clearly unconstitutional (at least to me), but my clients, the House and individual members, typically wanted them to be constitutional (because they arrogate power to the legislature) and wanted me to make the case for that. Contrary advice was not welcome and often ignored.

As an aside, I typically sympathized with legislators’ urges: it is often only practical to invest broad, discretionary powers in the executive to deal with difficult situations, like pandemics, but doing so requires ceding powers to someone who you may inherently not trust or may wish to subject to ongoing legislative limits or checks. But our rickety system of separation of powers, which imposes many checks and balances on the exercise of governmental powers, does not allow fudging the lines between the branches of government in doing so. A more robust role for the legislature requires edging more toward a parliamentary type system. Not in the U.S.

Addendum: The Kansas Legislature and Governor Laura Kelly have gotten into a tussle over their respective roles in her declaration of a state of emergency addressing the pandemic. A committee of the legislature (the Legislative Coordinating Council or LCC) attempted to terminate her declaration, stimulated by its application to Easter church services (also the locus of litigation in Kentucky but on first amendment grounds). The dispute ended in a Kansas Supreme Court decision concluding the LCC action was not authorized by the language of the legislative resolution extending the declaration’s term. That narrow basis for the decision allowed the court to avoid dealing with the legislature’s peculiar role in the process under the Kansas statute. However, one of the concurring judges noted the “vexing” separation powers issue raised by the legislature’s role in the process: “the structure of [the Kansas statute] itself risks violating the constitutional demand of separate powers.” Kelly v. Legislative Coordinating Council, Kansas Supreme Court, No. 122,765 (April 11, 2020), p. 18 (Stegall concurring). Note: Two church plaintiffs ultimately obtained a federal court TRO blocking enforcement of Governor Kelly’s order as applied to their services on free exercise of religion grounds, but subject to a page of public health restrictions imposed by the court. But not in time for Easter (decision was issued on the Friday after Easter).

These separation of powers issues may seem almost academic, but the Kansas example shows that they can have potential real world consequences.

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Recovery rebate redux

Early evidence is now available on payment of the stimulus to individuals (officially “recovery rebates”). Contrary to the concerns I expressed about the ability of the IRS to quickly get money into people’s hands, the agency has been delivering the dough. My middle daughter’s money showed up in her checking account last week. Media reports indicate that is pretty typical. But there is more to the story.

The IRS had to make some difficult decisions to accomplish that because (I assume) of the budget cuts that it has been subjected to by Republicans in Congress since they took over the House in 2010 Tea Party wave election. The agency made the reasonable decision (a classic utilitarian decision to get the largest benefit to the most people at the lowest cost) to prioritize people who filed electronically and used direct deposit – exactly the situation that my daughter was in. If you failed to do both, you’ll have to wait awhile.

  • If you used a tax preparer, like HR Block, and opted for a prepare-paid advance on your refund, you’ll have to wait. That happens because those refunds are directed to the preparer’s bank account to allow withholding payment for their services before transmitting the net amount to the taxpayer. Details here from WaPo. The articles estimates there could be 21 million filers in that boat. Inputting bank information on the IRS website might help; I wouldn’t hold my breath for quick turn around. See here for fraud concerns about the IRS’s widget for doing that for nonfilers. Some of the same concerns may apply to adding bank deposit information. I’m guessing the agency is rethinking things and putting more guardrails on it.
  • If you filed electronically, but did not provide direct deposit or direct payment information to the IRS, you’ll have to wait for a paper check. Those will be issued in batches over months (maybe up to 5). Of course, there was the slight delay to put the prez’s name on the checks; Commissioner Rettig should have held out for a naming rights payment in my opinion.
  • If you filed a paper return seeking a refund, you may have to wait that long or longer. The agency has stopped processing paper returns altogether given the demands of getting the recovery rebates out and protecting its workforce from the SARS-CoV-2 virus. See Janet Holtzblatt’s blog post.
  • If you starve the beast and expose it to a deadly virus, you can’t turn around and expect it to carry the load.

On another CARES Act issue, the JCT memo on the noncorporate losses and NOL distributions is available on Senator Whitehouse’s website here.

Addendum: After posting this, this Politico story was posted with additional shocking details about the situation at the IRS. Here are the first two graphs:

The IRS is drowning in unopened tax refund request amid the pandeminic

The IRS is piling unopened business tax refund requests into storage trailers and advising companies to file by fax instead. It’s stopped answering phone calls on taxpayer assistance lines. And it’s not processing millions of paper tax returns filed by individual Americans.
The coronavirus pandemic has nearly crippled the tax collection agency, which relies on antiquated technology and still does a lot of business on paper, just as it is most needed to help pump money into the ailing economy.
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CARES Act – noncorporate losses update

Some more light is being shined on the CARES Act retroactive allowance of the deduction of noncorporate losses to reduce tax on the other income of high income business owners. I previously blogged about this being the one provision of the Act that triggered my outrage meter.

Senator Sheldon Whitehouse (D-RI) requested a Joint Committee on Taxation (JCT) analysis of the provision, which is apparently scheduled to be released today as reported by WaPo. According to the article, 82% of the benefits will go to taxpayers with more than $1 million in income. Steve Rosenthal of TPC is quoted in the article as saying the prime beneficiaries (as I had hypothesized) are owners of hedge funds and real estate. I would add private equity firms. The analysis rolled in the effects of the CARES Act’s NOL changes – a change that does not outrage me, although surely one could come up with better targeted coronavirus relief than that.

The article quotes a Tax Foundation staffer as saying the TCJA provision was “poorly thought out” – I guess the implication is that the CARES Act is just fixing a TCJA “mistake.” There are two problems with that line of thinking – (1) it’s inappropriate in a coronavirus relief measure and (2) this was a pay-for that will increase the deficit effects of the TCJA by 10%; if you’re going to do as general tax policy improvement, offsetting revenue increasing provisions should be included. One can easily argue that the TCJA change was NOT poorly thought out. I would think the Tax Foundation argument could also be made about TRA86’s passive loss rules, limitations that have been in place for decades. The TCJA changes was a modest extension of them, an additional step toward a schedular income tax approach, as used by some countries (UK, I think). A similar provision has also applied to ag losses for years.

The WaPo article quotes a blog post by Alan Viard, an AEI tax economist, as favoring the CARES Act change to provide needed liquidity to businesses. Reading the blog post, his discussion appears to be directed at the general NOL provision, which I have less concern about, not the noncorporate loss provision. (Disclosure: I know Alan and loosely collaborated with him on something years ago; I tend to agree with the more general point he makes in the blog post.) At least, he does not explicitly mention the noncorporate loss allowance provision. Putting money in the personal pockets of high-buck investors seems like a really second best way of providing liquidity to businesses. How do we know what Stephen Schwarzman is actually going to do with his big tax refund? Will he put it in his existing businesses and keep workers on the payroll? I wouldn’t bet on it. More likely he will look to buy distressed assets at fire sale prices – providing no COVID-19 relief, rather leading to more misery for the current owners and employees. Congress should have used the money to directly help businesses instead. The could have added the $170 billion to the PPP loan program for which they’re now scrambling to appropriate more money.

As far as I can tell, the JCT analysis is not available on the Internet. JCT typically does not post these responses to requests (i.e., it’s not like a JCT publication); so, public release is more likely to come through Whitehouse’s office or through a news organization that gets access to it from the senator’s office. Obviously, they have already tipped off the media, so it should be forthcoming.

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Gleckman agrees with me

Howard Gleckman, a blogger at TPC, has a post about the charitable contribution deduction changes in the CARES Act, largely agreeing with the points in my post of a week ago. Of course, he manages to say it more succinctly than I did. He captures the effect of the above-the-line deduction as “benefit[ting] low- and middle-income households, but do[ing] little for the charities it is intended to support.” That describes it in a sentence. He notes that the AGI limit increase will encourage a handful of wealthy contributors to accelerate their contributions. Given the circumstances, I can see some justification for that – particularly if it were targeted to charities involved with COVID-19 relief, such as hospitals, clinics, and so forth (it’s not).

Gleckman points out a potential negative effect of the CARES Act’s RMD changes on charitable contributions. I expressed the view the Act’s RMD changes were unrelated to its purposes (as well as being bad policy), but had not made that argument. That effect had not occurred to me; it’s real but small. Gleckman suggests that “putting off RMDs may reduce their charitable giving somewhat.” I think that is fair, but in my judgment the financial effect is really small (a time value of money deal). It’s worth spending a paragraph to describe that. The more interesting question is whether the behavioral response reflects the financial effect or maybe bigger.

The law allows individuals who are subject to RMDs (“required minimum distributions” that must be withdrawn from IRAs each year, yielding taxable income) to transfer IRA money to a charity and thereby satisfy the RMD, while not recognizing the transfer as taxable income. The CARES Act says RMDs need not be taken in 2020. That does not, however, prevent an individual aged 70-1/2 (by June 30, 2019) from transferring IRA money to a charity and not recognizing it as income. Thus, the CARES Act leaves the tax benefit of making the transfer intact; it but just delays when the tax benefit occurs. The way to think about an IRA’s assets is that they include an embedded or deferred tax obligation that should be deducted from the nominal value to get an aftertax value. (One should do that in calculating asset allocations when holdings include taxable and Roth assets, as well as traditional IRAs. That will put the holdings of each type of account on an equal afertax footing with the others.) The timing of the recognition of those deferred tax obligations are determined by the RMD rules. So, essentially the deferred tax obligation must be discounted to present value under the RMD rules’ timing requirements, also taking into account potential changes in the account holder’s and beneficiaries’ tax rates.

In the case of the one-year delay under the CARES Act, the math is mildly complicated because making a qualified charitable transfer in 2020 does not satisfy the 2021 RMD. Rather it reduces the account value used to calculate the 2021 and later RMDs. Making the transfer will modestly reduce the 2021 RMD, the 2022 RMD, and so on. These future tax benefits must be reduced to present value. But given the low interest rate environment we’re in, the discount rate will be low and the financial effect should be small. Put another way, if you don’t think you’re going to earn a lot of income/interest by investing your IRA, why not give some of it away now (up to the limits of the qualified charitable distribution limits), rather than waiting until you’re actually subject to an RMD in 2021? That would be particularly true if one budgets for charitable contributions similarly to budgeting for other forms of consumption.

The bigger issue is how the RMD holiday actually affects behavior (i.e., the willingness to give) based on perceptions or misperceptions regarding the value of the resulting tax benefits – assuming that giving is actually affected by tax benefits. Behavioral economic research has shown that perceptions can be more important that actual financial or economic effects. Answering that would require some research for which I’m not sure data is readily available (e.g., from SOI). After the Cares Act data is in, we’ll have two data points – tax years 2009 and 2020 when RMDs were suspended but qualified charitable distributions were still permitted to be made – probably not enough to reach reliable conclusions, although I have seen research predicated on even thinner slices of data.

COVID update

Below is an update of the table on the ten states with the fewest confirmed cases of COVID-19 on a population adjusted basis. Minnesota continues to have the lowest number, but these numbers are highly sensitive to testing protocols. Minnesota’s total testing numbers continue to fall farther behind the national rates. Since April 1st, Minnesota’s positive test results have increased by 80%, while its total number of tests increased by 50%. That’s obviously concerning. I have not heard an explanation for this – whether it is due to lack of supplies, testing rules, or some combination of both. As you can see from the table, other high ranked states tend to have low testing rates, even lower than Minnesota’s below average rate (particularly Texas, North Carolina, and Nebraska).

StatePositive tests
per 10k pop
Total tests
per 10K pop
% tests
positive
Deaths
per million
CFR
Minnesota2.0554.533.8%6.93.4%
West Virginia2.7071.753.8%2.20.8%
Nebraska2.7041.616.5%7.22.7%
Oregon2.9458.245.0%9.03.1%
Kentucky3.0148.806.2%16.35.4%
Hawaii3.07111.252.8%3.51.1%
Alaska3.0996.623.2%9.63.1%
Montana3.1169.224.5%5.61.8%
Texas3.2333.209.7%6.11.9%
North Carolina3.2740.998.0%5.11.5%
National12.9568.2519.1%44.73.5%
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Covid-19 update

I can’t stop myself – more amateur observations on the virus and state-by-state data.

Minnesota just put out its April 5th update of COVID-19 data and it doesn’t appear to be good news. For some reason, Minnesota’s testing rate appears to be lagging a bit behind the national rate, whereas it had been slightly above a few days back. The differences are too small to be significant, but it’s not a good sign to me. More troubling, the number of positive tests is increasing faster than total tests (8.1% versus 5.3% for the one-day increase, 4/5 over 4/4), which could suggest more rationing of testing just when I had expected it to move in the opposite direction.

Nate Silver has a good piece over at 538 about how to be very cautious about reading much into case numbers because of state-by-state differences in testing. Its title’s assertion that the data is “meaningless” seems a little strong. That’s probably more true in making national comparisons, because testing differences by country vary a lot. But it is also relevant to state-by-state comparison. For example, in my earlier ranking, the explanation for West Virginia’s and Nebraska’s high ranking was likely due to the lower testing levels. Now that their testing has caught up to Minnesota’s, they’ve dropped in the case rankings – see the table below. Minnesota’s slightly below average testing rates suggests not reading too much into its #1 ranking, in any case.

I had thought the mortality numbers were pretty solid numbers (with the obvious lag resulting from how long it takes for the virus to run its course and differences in when it arrives in states), but WaPo has a story on how shaky even those numbers likely are. They only represent (obviously) deaths where there was a positive test – almost always before the deaths since it makes little sense to use scarce testing resources on corpses – and in some places there is so little testing that a fair number of people die from COVID-19 without being tested. Also there is the problem of false negatives. Silver says some studies show that could be as high as 30% (he guesses 20% is more reasonable)! That surprised me. The result is that the number of deaths may significantly understate the disease’s impact, particularly in places with low testing rates.

An update of the table from my earlier post is below. It shows that Minnesota has the lowest number of positive tests of any state on a population adjusted basis. The table now adds a column for case fatality rate (CFR) or the percentage positive tests that end with the patient dying. The data are from the COVID Tracking Project (with my population scaling using Census data) and are as of April 4, 2020 at 10 PM.

StatePositive tests
per 10k pop
Total tests
per 10K pop
% tests
positive
Deaths
per million
CFR
Minnesota1.5345.083.4%4.32.8%
West Virginia1.5742.893.7%1.10.7%
Nebraska1.6627.866.0%3.11.9%
Kentucky1.8634.855.3%8.34.5%
Texas2.1121.999.6%3.61.7%
Oregon2.1341.335.2%5.22.4%
Hawaii2.2586.722.6%2.10.9%
North Carolina2.2936.976.2%2.31.0%
Alaska2.3482.562.8%6.82.9%
New Mexico2.3674.553.2%4.82.0%
National9.2949.3818.8%25.22.7%

Plug: My niece (and goddaughter), Emily Troemel, is a professor of biology at the University of California San Diego. She and three colleagues have posted a video providing basic background information on the evolutionary and molecular biology of the SARS-CoV-2 virus. If you want to some clear and easy to understand background on the biology of the virus, I recommend watching the video – warning it is over an hour long. They’re biologists, not epidemiologists, so they’re not making projections or conclusions about the spread of the disease, but I found it very informative and interesting.

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