COVID-19 Hospital Data Is a Hot Mess After WH HHS Takes Controlhttps://arstechnica.com/science/2020/07/covid-19-hospital-data-is-a-hot-mess-after-feds-take-control/With weird discrepancies and fluctuations, COVID trackers say the data is less useful.
As COVID-19 hospitalizations in the US approach the highest levels seen in the pandemic so far, national efforts to track patients and hospital resources remain in shambles after the federal government abruptly seized control of data collection earlier this month.
For some hospitals, that data has to be harvested from various sources, such as electronic medical records, lab reports, pharmacy data, and administrative sources. The task has been particularly onerous for small, rural hospitals and hospitals that are already strained by a crush of COVID-19 patients.
https://www.healthcareitnews.com/news/quick-pivot-new-hhs-covid-19-reporting-rules-meant-chaos-hospitals... Amid all the administrative and technical hurdles, the national data on hospitalizations has become a hot mess. The COVID Tracking Project—which collects data on a variety of COVID-19 pandemic metrics—wrote in a blog post July 28 that US hospitalization data is no longer reliable.
https://covidtracking.com/blog/whats-going-on-with-covid-19-hospitalization-dataThe blog noted that between July 20 and July 26, federal totals of currently hospitalized patients has been, on average, 24-percent higher than the totals reported by states. On a state-by-state level, some states are reporting fewer cases than the HHS, some are reporting more, and some federal data has significant day-to-day fluctuations not seen before the reporting transition.
In a July 30 update, the tracking project noted the continued problems, concluding: “Taken together, the gaps and uncertainties in the previously stable hospitalization data mean that this crucial indicator has become much less useful for understanding the true severity of COVID-19 outbreaks."
https://covidtracking.com/blog/cases-declining-deaths-rising-hospital-data-remains-a-question-mark----------------------------------
COVID-19 Hospital Data System That Bypasses CDC Plagued By Delays, Inaccuracieshttps://www.npr.org/sections/health-shots/2020/07/31/897429054/covid-19-hospital-data-system-that-bypasses-cdc-plagued-by-delays-inaccuraciesEarlier 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 and 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.
... 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 email, "We will be updating the site to make it clear that the estimates are only updated weekly."The HHS Protect Public Data Hub, the public-facing website set up by HHS, offers three items as a "Hospital Utilization Snapshot,"
all of which have data that is over a week old- A "Downloadable Dataset" estimating how many hospital beds are occupied by state — last updated on July 21.
- A table tallying the total number of hospital beds occupied across the country, which has not been updated since July 23.
- A map showing the percent of hospital beds occupied by state, which has not been updated since July 23.
https://protect-public.hhs.gov/pages/hospital-capacityThe only information about hospital capacity that appears to be updated regularly on the HHS Protect site is the percentage of hospitals that have submitted data in the past seven days.
But, the tallies do not include certain categories of hospitals, including rehabilitation or veterans' hospitals, which have suffered COVID-19 outbreaks. These rehabilitation and veterans' hospitals had previously been included in the data reported by CDC, says the official, who spoke to NPR on background because they were not authorized to speak on the record.
https://protect-public.hhs.gov/pages/covid19-moduleAnomaliesAfter 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.
In Colorado, the hospitalization data maintained by HHS conflicts with the state's data posted to a daily dashboard. As of July 30, the state dashboard lists 341 patients hospitalized in Colorado with confirmed or suspected COVID-19 cases. A dataset maintained by the HHS, updated on July 30, lists 491 patients in Colorado.
... Members of The COVID Tracking Project from The Atlantic describe the hospital capacity data as being "highly erratic in recent weeks," and noted that data has been missing or incomplete from many states, including California, Texas, South Carolina, Idaho, Missouri and Wyoming, because of complications related to switching reporting systems.The organizers of the tracking website COVID Exit Strategy initially found the data provided by HHS Protect to be unusable.
"It had some states like Rhode Island having an inpatient bed utilization of above 100%," says site co-founder Ryan Panchadsaram. "And Rhode Island is a state where hospitalizations are quite low for COVID."---------------------------------
A Federal Data Failure Is Making It Hard to Talk About COVIDhttps://www.govexec.com/management/2020/07/federal-data-failure-making-it-hard-talk-about-covid/166988/Without a standard, trusted language of COVID data collection, it’s been hard to measure the disease, track its trend, and build effective policy.When it comes to the language of COVID, the United States stands in sharp contrast with the rest of the world. The Germans have their Robert Koch Institute—the country’s version of the Centers for Disease Control and Prevention—and its reports are a model of clarity and precision and political neutrality in nailing down the problem.
In the United Kingdom, there’s an up-to-the-minute dashboard of cases, hospitalizations, and the death rate, with the data broken down by region. Australia, likewise, has an easy-to-read “BeCovidSafe” dashboard that tracks the virus. In Canada, there’s a handy outbreak update. Japan has its COVID tracker powered by data from the prefectural governments, and Korea’s website builds on data from the country’s Central Disease Control Headquarters. In all these cases, the building blocks of data come from the government, and they drive the public debate.
In the United States, by contrast, the COVID language problem has been muddled from the beginning. The New York Times is reporting daily trends and hot spots based on data from county governments. For the Washington Post, data comes from the paper’s reporters and from the notable Johns Hopkins University COVID-19 dashboard, whose numbers in turn are compiled from a vast array of local and state public health departments. Then, of course, there’s the University of Washington COVID model, which builds on the Johns Hopkins Github, and the University of Texas COVID-19 Modeling Consortium, which has its own methodology.
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