When the data isn’t there: COVID-19 and the complexity of information gathering

When it comes to COVID-19, we all have questions we want answered. But without reliable data and analytics, it’s a near impossible task, as illustrated by the challenges hospitals in the Midwest are now facing.
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COVID-19 Analytics and Data

Hospitals in Kansas and Missouri warn that a recent change in how healthcare data is reported to the federal government is making it difficult to know the true burden of COVID-19 on the states’ healthcare systems, according to NPR.

Prior to July 10, 2020, health systems reported public health data – including information about COVID-19 – to the Centers for Disease Control. Now, they’ll need to send it to a new system within the US Department of Health and Human Services (HHS), known as HHS Protect.

For healthcare professionals in the heartland, this means that the release of valuable information about the spread of the novel coronavirus in each state will be delayed, and in its current format, may be inaccurate.

The change highlights competing priorities that have long challenged those working in healthcare IT (HIT) – acknowledging the need for accurate, robust data that can help health systems make the best decisions for their patients, while also understanding the difficulties of trying to change or improve the way we collect that data without interrupting the status quo.

While this issue in Kansas and Missouri has an immediate impact, it’s a case that highlights broader issues that aren’t news to the HIT sector. How do we make sure that we help institutions gather accurate, important data, and how can we make the process of collecting it easy for providers on the front lines? When is a course correction needed, and when will it cause more harm than good? While the answers to these questions – and others – aren’t necessarily easy or straightforward, the pandemic has certainly helped to show how urgently they are needed.

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