COVID-19 Hospital Data System That Bypasses CDC Plagued By Delays, Inaccuracies

https://www.npr.org/sections/health-shots/2020/07/31/897429054/covid-19-hospital-data-system-that-bypasses-cdc-plagued-by-delays-inaccuracies


July 31, 20205:00 AM ET
Pien Huang
Selena Simmons-Duffin

Earlier this month, when the Trump administration told hospitals to send crucial data about coronavirus cases and intensive care capacity to a new online system, it promised the change would be worth it. The data would be more complete, transparent, and an improvement over the old platform run by the Centers for Disease Control and Prevention, administration officials said.

Instead, the public data hub created under the new system is updated erratically and is rife with inconsistencies and errors, data analysts say.

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The delays and problems with data on the availability of beds, ventilators and safety equipment could have profound consequences as infections and deaths soar throughout most of the country, public health experts say.

"If the information is not accurate, it could cost time — and lives," says Lisa M. Lee, formerly the chief science officer for public health surveillance at CDC, now at Virginia Tech. For instance, knowing which hospitals have the capacity to take on new patients is critical, she explains. "If all the ICU beds are taken up, emergency medical personnel need to take [new patients] to the next town over or to the next county."

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Hospitals are supposed to report daily to the federal government the total many beds they have, the number occupied and the availability of intensive care beds. Under the new system, the Department of Health and Human Services aggregates the information at a state level, and shares a daily spreadsheet of the information that has been reported — gaps and all.

But the old CDC approach interpreted the data a step further. CDC posted estimates derived from the data to show an approximation of the actual availability of ICU beds, accounting for the lags and gaps in reporting. These estimates — promised on the HHS website — have not been updated in over a week.

By contrast, the CDC estimates was updated three times a week. And while the data sent to CDC was vetted for accuracy before being posted publicly, the data sent to the new platform appears to be posted as it is received and contains multiple anomalies, analysts note.

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The data now available to the public appears to be neither faster nor more complete.

When HHS took over the collection and reporting of this hospital capacity data, it promised to update "multiple times each day." Later, the agency walked that back to say it would be updated daily.

Those daily updates have yet to materialize. On Thursday, an HHS spokesperson told NPR via e-mail, "We will be updating the site to make it clear that the estimates are only updated weekly."

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After the data reporting switch, unusual numbers started cropping up in data that show how many hospital beds are filled in a given state, data analysts say. In some states, the bed occupancy rates soared, even though the number of hospitalized COVID-19 patients dropped or only increased modestly.

Take, for example, Arizona. Under the old system, in data last collected by CDC on July 14, an estimated 3,205 COVID-19 patients in Arizona occupied 24% of the state's inpatient hospital beds. After the switch to the new HHS reporting system, an analogous dataset posted by HHS showed 82 fewer COVID-19 patients hospitalized, but the bed occupancy rate had jumped to 42%. It's unclear how fewer patients could be occupying more hospital capacity.

There are similar anomalies in the data for other states, including Georgia and New Mexico.

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