The COVID-19 pandemic exposed the critical consequences of manual clinical data, inconsistent data quality and lack of interoperability on our ability to control public health threats. It is no secret that states and communities were challenged around COVID reporting. California suffered a backlog of 300,000 tests in the summer of 2020 because their system could not scale, as was widely reported in the media. In Oklahoma, as reported by Politico, “staffers shuffled through piles of paper they’d pulled out of fax machines and sorted through hundreds of secure emails to upload COVID-19 lab results manually to the state’s digital dashboard — a system that often malfunctioned.”

Unfortunately, the many challenges of incorporating patient test results into systems for analyzing the data slowed down the pandemic response and obscured the true picture of COVID-19 spread and prevalence.

A key part of the problem is that lab data is frequently missing crucial information or coded incorrectly. For example, Diameter Health’s ongoing analyses consistently show that 70% of lab results do not use the correct vocabulary or units. Oftentimes, laboratory data are reported in text descriptions instead of coded data. Any single medical test can be documented in hundreds of ways by different laboratories, hospitals and provider offices, including use of different codes and descriptions. Querying and subsequent analytics at a population level are especially challenging when variable text descriptions are relied upon to make population health decisions.

As a practicing physician, I’ve experienced some of the challenges surrounding communicable disease and emerging pathogen reporting in my own practice. The typical workflow can be challenging, beginning with laboratory results data entry from my Electronic Health Record (EHR) system. From there, it takes weeks before I receive a faxed or mailed questionnaire from my state’s agency requiring me to manually enter data about the patient’s presentation, affirm the source and results of the lab reports, document care plans, and provide evidence of treatment and/or cure. Not only is this an inefficient use of a provider’s time, but it is fraught with clerical errors that undermine patient care and contribute to inaccurate population surveillance.

In my role at Diameter Health, I have also seen how my personal clinical experience is emblematic of an even larger problem. Day in and day out, Diameter Health sees the wide variations in data quality that not only hamper the country’s response to COVID-19 but the ability to improve the health of individuals and communities in general.

The federal government has responded to the lessons learned by issuing an executive order aimed at “Ensuring a Data-Driven Response to COVID-⁠19 and Future High-Consequence Public Health Threats,” specifically calling out the need to “make data open to the public in human- and machine-readable formats as rapidly as possible.”  The feds also designated funds under the CARES Act to improving data interoperability and has issued the Data Modernization – COVID Guidance report to accelerate implementation of data modernization efforts.

Diameter Health believes that an industry commitment to data interoperability standards and applying technology to fix data quality will allow state and federal agencies to be better prepared to not only proactively monitor and address COVID-19 disease prevalence but also to strengthen our country’s public health reporting infrastructure.

To dive into this topic more, I’ve written an Issue Brief with additional details on the problems, and the solutions, to COVID reporting. We invite you to join us in fighting poor data quality that hampers public health response.

Read the Issue Brief, “COVID-19 Reporting Challenges Highlight the Importance of Normalized, Complete Clinical Data to Help Save Lives.”