Tag Archives: Don Wolt

Reformed Covid Reporting Might Quell the Omicron Panic

31 Friday Dec 2021

Posted by in Coronavirus, Data Integrity

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That’s our Commander and Chief this week, posing in a mask on the beach in what is a phenomenal display of stupidity. More importantly, that kind of messaging contributes to the wholly unwarranted panic surrounding the Omicron variant of Covid-19. Panic, you say? Take a look at this admission from a New York health official. She says a recent alert on pediatric hospitalizations was driven by a desire to “motivate” parents to vaccinate their children. Yet Covid has never posed a significant risk to children. And take a look at what this insane physician posted. It’s fair to say he’s “catastrophizing”, an all too common psychological coping mechanism for alarmists.

The Omicrommon Cold

Given Omicron’s low apparent severity, it might be the variant that allows a return to normalcy. It’s perhaps the forefront of a more benign but endemic Covid, as it seems to be out-competing and displacing the far more dangerous Delta variant. In fact, Omicron infections are protective against Delta, probably for much longer than vaccines. The mild severity we’ve seen thus far is due in part to protection from vaccines and acquired immunity against breakthrough infections, but there’s more: there are plenty of non-breakthrough cases of Omicron, and most hospitalizations are among the unvaccinated. Yet we see this drastic decline in Florida’s ratio of ICU to hospital admissions (as well as a reduction in length of stay — not shown on chart). Similar patterns appear elsewhere. Omicron’s more rapid onset and course make it less likely that these patterns are caused by lags in the data.

Panic Begets Lockdowns

The frantic Omicron lunacy is driven partly by data on the number of new cases, which can be highly misleading as a guide to the real state of affairs. Testing is obviously necessary for diagnosis, but case totals as an emphasis of reporting have a way of feeding back to panic and destructive public policy: every wave brings surges in cases and the positivity rate prompting authoritarian measures with dubious benefits and significant harms (see here and here).

Flawed Case Data

In many respects, the data on Covid case totals have been flawed from the beginning, owing largely to regulators. At the outset in early 2020, there was a severe shortage in testing capacity due to the CDC’s delays in approving tests, as well as restrictions on testing by private labs. Many cases went undiagnosed, including a great many asymptomatic cases. The undercount of cases inflated the early case fatality rate (CFR). Subsequently, the FDA dithered in its reviews of low-cost, rapid, at-home tests. The latest revelation was the Administration’s decision in October to nix a large rollout of at-home tests. While the results of those tests are often unreported, they would have been helpful to individual decisions about seeking care and quarantining.

The PCR test finally distributed in March 2020 was often too sensitive, which the CDC has finally acknowledged, This is a flaw I’ve noted several times in the past. It led to false positives. Hospitals began testing all admitted patients, which was practical, and the hospitals were happy to do so given the financial rewards attendant to treating Covid patients under the CARES Act. However, it resulted in the counting of “incidental” Covid-positives: patients admitted with Covid, but not for Covid. That inflates apparent severity gleaned through measures like hospitalized cases, and it can distort counts of Covid fatalities and the CFR.

On balance, the bias caused by the test shortage at the start of the pandemic likely constrained total case counts, but the subsequent impact of testing practices is uncertain except for incidental hospitalized cases and the impact on counts of deaths.

Omicron Enlightenment

Omicron spreads rapidly, so the clamoring for tests by panicked consumers has resulted in another testing shortage, both for PCR tests and at-home tests at pharmacies. The shortage might not be relieved until the Omicron wave has crested, which could occur within a matter of a few weeks if the experience of South Africa and London are guides. In the meantime, another deleterious effect of the “case panic” is the crush of nervous individuals at emergency rooms presenting with relatively minor symptoms. Now more than ever, many of the cases identified at hospitals are incidental, particularly pediatric cases.

A thread by Monica Gandhi, and her recent article in the New York Times, makes the case that hospitalizations should be the primary focus of Covid reporting, rather than new cases. Quite apart from the inaccuracies of case counting and the mild symptoms experienced by most of those infected, Gandhi reasons that breakthrough infections so common with Omicron render case counts less relevant. That’s because high rates of vaccination (not to mention natural immunity from prior infections) reduce severity. Even Jennifer Rubin has taken this position, a complete reversal of her earlier case-count sanctimony.

Incidental Infections

Phil Kerpen’s reaction to Gandhi’s article was on point, however:

“Unless HHS Protect adds a primary [diagnosis] column, hospital census isn’t much more useful than cases.”

HHS Protect refers to the Health and Human Services public data hub. Without knowing whether Covid is the primary diagnosis at admission, we have no way of knowing whether the case is incidental. If Covid is the primary reason for admission, the infection is likely to be fairly severe. It is more useful to know both the number of patients hospitalized for Covid and tge number hospitalized for other conditions (incidentally with Covid). The distinction has been extremely important to those interpreting data from South Africa, where a high proportion of incidental admissions was a tip-off that Omicron is less severe than earlier variants.

The absence of such coding is similar to the confusion caused by the CDC’s decision early in pandemic to issue new guidance on the completion of death certificates when Covid is present or even suspected. A special exception was created at that time requiring all deaths involving primary or incidental Covid infections to be ruled as Covid deaths. This represented another terrible corruption of the data.

Summary

Earlier variants of Covid were extremely dangerous to the elderly, obese, and the immune-compromised. Yet public health authorities seemed to take every opportunity to mismanage the pandemic, including contradictory messaging and decisions that compromised the usefulness of data on the pandemic. But here we are with Omicron, which might well be the variant that spells the end of the deadly Covid waves, and the focus is still squarely on case counts, vaccine mandates, useless masking requirements, and President Brandon wearing a mask on the beach!

Case counts should certainly be available, as Gandhi goes to great lengths to emphasize. However, other metrics like hospitalizations are more reliable indicators of the current wave’s severity, especially if paired with information on primary diagnoses. Fortunately, there has been a very recent shift of interest to that kind of focus because the superior information content of reports from countries like South Africa and Denmark is too obvious. As Don Wolt marvels:

“Behold the sudden interest by the public health establishment in the “With/From” COVID distinction. While long an important & troubling issue for many who sought to understand the true impact of the virus, it was, until very recently, actively ignored by Fauci & crew.”

That change in emphasis would reduce the current sense of panic, partly by making it more difficult for the media to purvey scare stories and for authorities to justify draconian non-pharmaceutical interventions. It’s no exaggeration to say that anything that might keep the authoritarians at bay should be a public health priority.

Cash Flows and Hospital Woes

10 Sunday Jan 2021

Posted by in Coronavirus, Health Care

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Here’s one of the many entertaining videos made by people who want to convince you that hospitals are overrun with COVID patients (and here is another, and here, here, and here). That assertion has been made repeatedly since early in the pandemic, but as I’ve made clear on at least two occasions, the overall system has plenty of capacity. There are certainly a few hospitals at or very near capacity, but diverting patients is a long-standing practice, and other hospitals have spare capacity to handle those patients in every state. Those with short memories would do well to remember 2018 before claiming that this winter is unique in terms of available hospital beds.

An old friend with long experience as a hospital administrator claimed that I didn’t account for staffing shortfalls in my earlier posts on this topic, but in fact the statistics I presented were all based on staffed inpatient or ICU beds. Apparently, he didn’t read those posts too carefully. Moreover, it’s curious that a hospital administrator would complain so bitterly of staffing shortfalls in the wake of widespread hospital layoffs in the spring. And it’s curious that so many layoffs would accompany huge bailouts of hospital systems by the federal government, courtesy of the CARES Act.

In fairness, hospitals suffered huge declines in revenue in the spring of 2020 as elective procedures were cancelled and non-COVID patients stayed away in droves. Then hospitals faced the expense of covering their shortfalls in PPE. We know staffing was undercut when health care workers were diagnosed with COVID, but in an effort to stem the red ink, hospitals began laying-off staff anyway just as the the COVID crisis peaked in the spring. About 160,000 staffers were laid off in April and May, though more than half of those losses had been recovered as of December.

Did these layoffs lead to a noticeable shortfall in hospital capacity? It’s hard to say because bed capacity is a squishy metric. When patients are discharged, staffed beds can ratchet down because beds might be taken “off-line”. When patients are admitted, beds can be brought back on-line. ICU capacity is flexible as well, as parts of other units can be quickly modified for patients requiring intensive care. And patient ratios can be adjusted to accommodate layoffs or an influx of admissions. Since early in the fall, occupancy has been overstated for several reasons, including a new requirement that beds in use for observation of outpatients with COVID symptoms for 8 hours or more must be reported as beds occupied. However, there are hospitals claiming that COVID is stressing capacity limits, but nary a mention of the earlier layoffs.

So where are we now in terms of staffed hospital occupancy. The screen shot below is from the HHS website and represents staffed bed utilization nationwide. 29% of capacity is open, hardly a seasonal anomaly, and there are very few influenza admissions thus far this winter, which is rather unique. 37% of ICU beds are available, and COVID patients, those admitted either “for” or “with” COVID, account for less than 18% of inpatients, though again, that includes observational beds.

Next are the 25 states with the highest inpatient bed utilization as of January 7th. Rhode Island tops the list at just over 90%, and eight other states are over 80%. In terms of ICU utilization, Georgia and Alabama are very tight. California and Arizona are outliers with respect to proportions of COVID inpatients, 41% and 38%, respectively. Finally, CA, GA, AL and AZ are all near or above 50% of ICU beds occupied by COVID patients.

So some of the states reaching the peak of their fall waves are pretty tight, and there are states with large numbers of very serious cases. Nevertheless, in all states there is variation across local hospitals to serve in relief, and it is not unusual for hospitals to suffer wintertime strains on capacity.

Los Angeles County is receiving much attention for recent COViD stress placed on hospital capacity. But it is hard to square that narrative with certain statistics. For example, Don Wolt notes that the state of California reports available ICU capacity in Southern CA of zero, but LA County has reported 10% ~ 11% for weeks. And the following chart shows that LA County occupancy remains well below it’s July peak, especially after a recent downward revision from the higher level shown by the blue dashed line.

Interestingly, the friend I mentioned said I should talk with some health system CEOs about recent occupancies. He overlooked the fact that I quoted or linked to comments from some system CEOs in my earlier posts (linked above). It’s noteworthy that one of those CEOs, and this report from the KPI Institute, propose that an occupancy rate of 85% is optimal. This medical director prefers a 75% – 85% rate, depending on day of week. These authors write that there is no one “optimal” occupancy rate, but they seem to lean toward rates below 85%. This paper reports a literature search indicating ICU occupancy of 70% -75% is optimal, while noting a variety of conditions may dictate otherwise. Seasonal effects on occupancy are of course very important. In general, we can conclude that hospital utilization in most states is well within acceptable if not “optimal” levels, especially in the context of normal seasonal conditions. However, there are a few states in which some hospitals are facing tight capacity, both in total staffed beds and in their ICUs.

None of this is to minimize the challenges faced by administrators in managing hospital resources. No real crisis in hospital capacity exists currently, though hospital finances are certainly under stress. Yes, hospitals collect greater reimbursements on COVID patients via the CARES Act, but COVID patients carry high costs of care. Also, hospitals have faced steep declines in revenue from the fall-off in other care, high costs in terms of PPE, specialized equipment and medications, and probably high temporary staffing costs in light of earlier layoffs and short-term losses of staff to COVID infections. The obvious salve for many of these difficulties is cash, and the most promising source is public funding. So it’s unsurprising that executives are inclined to cry wolf about a capacity crisis. It’s a simple story and more appealing than pleading for cash, and it’s a scare story that media are eager to push.

Most Hospitals Have Ample Capacity

05 Saturday Dec 2020

Posted by in Coronavirus, Health Care

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Let’s get one thing straight: when you read that “hospitalizations have hit record highs”, as the Wall Street Journal headline blared Friday morning, they aren’t talking about total hospitalizations. They reference a far more limited set of patients: those admitted either “for” or “with” COVID. And yes, COVID admissions have increased this fall nationwide, and especially in certain hot spots (though some of those are now coming down). Admissions for respiratory illness tend to be highest in the winter months. However, overall hospital capacity utilization has been stable this fall. The same contrast holds for ICU utilization: more COVID patients, but overall occupancy rates have been fairly stable. Several factors account for these differing trends.

Admissions and Utilization

First, take a look at total staffed beds, beds occupied, and beds occupied by COVID patients (admitted “for” or “with” COVID), courtesy of Don Wolt. Notice that COVID patients occupied about 14% of all staffed beds over the past week or so, and total beds occupied are at about 70% of all staffed beds.

Is this unusual? Utilization is a little high based on the following annual averages of staffed-bed occupancy from Statista (which end in 2017, unfortunately). I don’t have a comparable utilization average for the November 30 date in recent years. However, the medical director interviewed at this link believes there is a consensus that the “optimal” capacity utilization rate for hospitals is as high as 85%! On that basis, we’re fine in the aggregate!

The chart below shows that about 21% of staffed Intensive Care Unit (ICU) beds are occupied by patients having COVID infections, and 74% of all ICU beds are occupied.

Here’s some information on the regional variation in ICU occupancy rates by COVID patients, which pretty much mirror the intensity of total beds occupied by COVID patients. Fortunately, new cases have declined recently in most of the states with high ICU occupancies.

Resolving an Apparent Contradiction

There are several factors that account for the upward trend in COVID admissions with stable total occupancy. Several links below are courtesy of AJ Kay:

  • The flu season has been remarkably light, though outpatients with symptoms of influenza-like illness (ILI) have ticked-up a bit in the past couple of weeks. Still, thus far, the light flu season has freed up hospital resources for COVID patients. Take a look at the low CDC numbers through the first nine weeks of the current flu season (from Phil Kerpen):
  • There is always flexibility in the number of staffed beds both in ICUs and otherwise. Hospitals adjust staffing levels, and beds are sometimes reassigned to ICUs or from outpatient use to inpatient use. More extreme adjustments are possible as well, as when hallways or tents are deployed for temporary beds. This tends to stabilize total bed utilization.
  • The panic about the fall wave of the virus sowed by media and public officials has no doubt “spooked” individuals into deferring care and elective procedures that might require hospitalization. This has been an unfortunate hallmark of the pandemic with terrible medical implications, but it has almost surely freed-up capacity.
  • COVID beds occupied are inflated by a failure to distinguish between patients admitted “for” COVID-like illness (CLI) and patients admitted for other reasons but who happen to test positive for COVID — patients “with” COVID (and all admissions are tested).
  • Case inflation from other kinds of admissions is amplified by false positives, which are rife. This leads to a direct reallocation of patients from “beds occupied” to “COVID beds occupied”.
  • In early October, the CDC changed its guidelines for bed counts. Out-patients presenting CLI symptoms or a positive test, and who are assigned to a bed for observation for more than eight hours, were henceforth to be included in COVID-occupied beds.
  • Also in October, the FDA approve an Emergency Use Authorization for Remdesivir as a first line treatment for COVID. That requires hospitalization, so it probably inflated COVID admissions.
  • The CDC also announced severe penalties in October for facilities which fail to meet its rather inclusive COVID reporting requirements, creating another incentive to capture any suspected COVID case in its reports.

In addition to the above, let’s not forget: early on, hospitals were given an incentive to diagnose patients with COVID, whether tested or merely “suspected”. The CARES Act authorized $175 billion dollars for hospitals for the care of COVID patients. In the spring and even now, hospitals have lost revenue due to the cancellation of many elective procedures, so the law helped replace those losses (though the distribution was highly uneven). The point is that incentives were and still are in place to diagnose COVID to the extent possible under the law (with a major assist from false-positive PCR tests).

Improved Treatment and Treatment

While more COVID patients are using beds, they are surviving their infections at a much higher rate than in the spring, according to data from FAIR Health. Moreover, the average length of their hospital stay has fallen by more than half, from 10.5 to 4.6 days. That means beds turn over more quickly, so more patients can be admitted over a week or month while maintaining a given level of hospital occupancy.

The CDC just published a report on “under-reported” hospitalization, but as AJ Kay notes, it can only be described as terrible research. Okay, propaganda is probably a better word! Biased research would be okay as well. The basic idea is to say that all non-hospitalized, symptomatic COVID patients should be counted as “under-counted” hospitalizations. We’ve entered the theater of the absurd! It’s certainly true that maxed-out hospitals must prioritize admissions based on the severity of cases. Some patients might be diverted to other facilities or sent home. Those decisions depend on professional judgement and sometimes on the basis of patient preference. But let’s not confuse beds that are unoccupied with beds that “should be occupied” if only every symptomatic COVID patient were admitted.

Regional Differences

Finally, here’s a little more information on regional variation in bed utilization from the HealthData.gov web site. The table below lists the top 25 states by staffed bed utilization at the end of November. A few states are highlighted based on my loose awareness of their status as “COVID “hot spots” this fall (and I’m sure I have overlooked a couple. Only two states were above 80% occupancy, however.

The next table shows the 25 states with the largest increase in staffed bed utilization during November. Only a handful would appear to be at all alarming based on these increases, but Missouri, for example, at the top of the list, still had 27% of beds unoccupied on November 30. Also, 21 states had decreases in bed utilization during November. Importantly, it is not unusual for hospitals to operate with this much headroom or less, which many administrators would actually prefer.

Of course, certain local markets and individual hospitals face greater capacity pressures at this point. Often, the most crimped situations are in small hospitals in underserved communities. This is exacerbated by more limited availability of staff members with school-age children at home due to school closures. Nevertheless, overall needs for beds look quite manageable, especially in view of some of the factors inflating COVID occupancy.

Conclusion

Marc Boom, President and CEO of Houston Methodist Hospital, had some enlightening comments in this article:

“Hospital capacity is incredibly fluid, as Boom explained on the call, with shifting beds and staffing adjustments an ongoing affair. He also noted that as a rule, hospitals actually try to operate as near to capacity as possible in order to maximize resources and minimize cost burdens. Boom said numbers from one year ago, June 25, 2019, show that capacity was at 95%.”

So there are ample beds available at most hospitals. A few are pinched, but resources can and should be devoted to diverting serious COVID cases to other facilities. But on the whole, the panic over hospital capacity for COVID patients is unwarranted.

November Pandemic Perspective

18 Wednesday Nov 2020

Posted by in Coronavirus, Pandemic, Uncategorized

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I hope readers share my compulsion to see updated COVID numbers. It’s become a regular feature on this blog and will probably remain one until infections subside, vaccine or otherwise. Or maybe when people get used to the idea of living normally again in the presence of an endemic pathogen, as they have with many other pathogens and myriad risks of greater proportions, and as they should. That might require more court challenges, political changes, and plain old civil disobedience.

So here, then, is an update on the U.S. COVID numbers released over the past few days. The charts below are attributable to Don Wolt (@tlowdon on Twitter).

First, reported deaths began to creep up again in the latter half of October and have escalated in November. They’ve now reached the highs of the mid-summer wave in the south, but this time the outbreak is concentrated in the midwest and especially the upper midwest.

Reported deaths are the basis of claims that we are seeing 1,500 people dying every day, which is an obvious exaggeration. There have been recent days when reported deaths exceeded that level, but the weekly average of reported deaths is now between 1,100 and 1,200 a day.

It’s important to understand that deaths reported in a given week actually occurred earlier, sometimes eight or more weeks before the week in which they are reported. Most occur within three weeks of reporting, but sometimes the numbers added from four-plus weeks earlier are significant.

The following chart reproduces weekly reported deaths from above using blue bars, ending with the week of November 14th. Deaths by actual date-of-death (DOD) are shown by the orange bars. The most recent three-plus weeks always show less than complete counts of deaths by DOD. But going back to mid-October, actual weekly deaths were running below reported deaths. If the pattern were to follow the upswings of the first two waves of infections, then actual weekly deaths would exceed reported deaths by perhaps the end of October. However, it’s doubtful that will occur, in part because we’ve made substantial progress since the spring and summer in treating the disease.

To reinforce the last point, it’s helpful to view deaths relative to COVID case counts. Deaths by DOD are plotted below by the orange line using the scale on the right-hand vertical axis. New positive tests are represented by the solid blue line, using the left-hand axis, along with COVID hospitalizations. There is no question that the relationship between cases, hospitalizations, and deaths has weakened over time. My suspicions were aroused somewhat by the noticeable compression of the right axis for deaths relative to the two charts above, but on reviewing the actual patterns (peak relative to troughs) in those charts, I’m satisfied that the relationships have indeed “decoupled”, as Wolt puts it.

Cases are going through the roof, but there is strong evidence that a large share of these cases are false positives. COVID hospitalizations are up as well, but their apparent co-movement with new cases appears to be dampening with successive waves of the virus. That’s at least partly a consequence of the low number of tests early in the pandemic.

So where is this going? The next chart again shows COVID deaths by DOD using orange bars. Wolt has concluded, and I have reported here, that the single-best short-term predictor of COVID deaths by DOD is the percentage of emergency room visits at which patients presented symptoms of either COVID-like illness (CLI) or influenza-like illness (ILI). The sum of these percentages, CLI + ILI, is shown below by the dark blue line, but the values are shifted forward by three weeks to better align with deaths. This suggests that actual COVID deaths by DOD will be somewhere around 7,000 a week by the end of November, or about 1,000 a day. Beyond that time, the path will depend on a number of factors, including the weather, prevalence and immunity levels, and changes in mobility.

I am highly skeptical that lockdowns have any independent effect in knocking down the virus, though interventionists will try to take credit if the wave happens to subside soon for any other reason. They won’t take credit for the grim lockdown deaths reaped by their policies.

Despite the bleak prospect of 1,000 or more COVID-attributed deaths a day by the end of November, the way in which these deaths are counted is suspect. Early in the pandemic, the CDC significantly altered guidelines for the completion of death certificates for COVID such that deaths are often improperly attributed to the virus. Some COVID deaths stem from false-positive PCR tests, and again, almost since the beginning of the pandemic, hospitals were given a financial incentive to classify inpatients as COVID-infected.

It’s also important to remember that while any true COVID fatality is premature, they are generally not even close to the prematurity of lockdown deaths. That’s a simple consequence of the age profile of COVID deaths, which indicate relatively few life-years lost, and the preponderance of co-morbidities among COVID fatalities.

Again, COVId deaths are bad enough, but we are seeing an unacceptable and ongoing level of lockdown deaths. This is now to the point where they may account for almost all of the continuing excess deaths, even with the fall COVID wave. It’s probable that public health would be better served with reduced emphasis on COVID-mitigation for the general population and more intense focus on protecting the vulnerable, including the distribution of vaccines.