Sep 09 2022
Data Analytics

Why Should Healthcare Organizations Hire a Data Quality Manager?

Quality data is crucial as providers look to do more with patient information, including improving diagnostics, patient outcomes and even preventive healthcare efforts.

Data is becoming increasingly important in healthcare as providers look to personalize medicine by identifying social determinants of health, creating a holistic view of a patient’s health. However, data must be of good quality to give physicians the insights they need to make a difference in patient outcomes.

Hiring a data quality manager can help healthcare organizations take their data out of silos and unlock valuable insights. As health IT leaders and executives consider whether they could benefit from hiring a data quality manager, it’s important for them to understand what they do and how they improve data.

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What Is the Role of a Data Quality Manager in Healthcare?

Data quality managers understand why complete, correct and consistent data is important, not only as a matter of principle but also as it relates to business and clinical goals in healthcare. They are interested in several factors of data quality, including completeness, reliability, validity and consistency.

People in this role don’t have to be computer programmers, but they do need to understand how to do threshold and metric setting, which may require knowledge of statistics. In addition, they should be able to implement algorithms and methodologies to detect when data does not meet standards or expectations set by the healthcare organization.

That means it’s also important for data quality managers to understand standards as well as what’s available within the data streams being used, says Charles Hawley, director of projects at the National Association of Health Data Organizations (NAHDO).

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For example, Hawley points out that data about a patient’s language may be in the enrollment file but not in the claims data, both of which are exchanged using different standards than the one used for incorporating data into medical records. Data completeness will depend upon what’s available in the system. If an organization is interested in data related to language but that data isn’t being entered into the correct forms or the electronic medical record, there will be a 0 percent completion rate of that data collection. Hawley explains that this isn’t an issue of data quality per se, but simply that the desired data isn’t being collected.

“You need to have somebody on your team making sure that you’re getting what you think you’re getting and identifying ways to make it even better,” says Norm Thurston, NAHDO’s executive director. “You can’t just trust that someone is sending the data you asked for in the format you want, and you need someone to own those issues.”

Data quality managers can’t be comfortable with the way things have always been done, he adds. They should constantly be looking at data in new ways.

What Are the Benefits of Hiring a Data Quality Manager in Healthcare?

Data quality managers have three main benefits for healthcare organizations, according to Hawley: quality improvement, compliance and efficiency.

While data quality managers set policies to ensure the quality of healthcare data, they are not compliance officers. They have open communication with an organization’s compliance team so that when a file is rejected, they can discuss why and then the compliance officer can enforce the data policies.

“People want data to turn into information and then into knowledge or action. That knowledge or action is only reliable if data are reliable. To make that happen, you have to have a compliance effort,” Hawley says.

In addition, Thurston explains that data quality managers are the stewards or guardians of data submission manuals. They must identify needed additions annually. The data quality manager acts as a good cop or white hat, while the compliance officer plays the role of bad cop to ensure people follow the data guidelines. However, the data quality manager should still understand the same governance, policy regulations, contracts and business needs that the compliance officer must know.

Once the compliance effort is sorted out, the data quality manager can focus on efficiency, such as automating data quality checks. Hawley emphasizes that automation allows a data quality team to continue to build on the data quality processes that are in place.

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Data quality checks don’t end with the data intake. It’s also important to monitor the quality of data outputs, which could be used for research, clinical initiatives or business operation improvements.

Once the data is clean and without duplicates and the extract, transform and load process is complete, the data quality manager can check the reliability of data, such as social determinants of health , by comparing them against other known data, such as figures from the U.S. Census. The quality data outputs can be used to better understand the healthcare ecosystem and improve population health initiatives.

Tips for Implementing a Data Quality Manager in Healthcare

Health IT leaders should have realistic expectations, a clear sense of what they hope to achieve and a procedure for bringing in the data quality manager to begin building their process.

It’s also important that they be involved in conversations with the security and IT teams to make sure the data is protected.

To ensure the data quality manager can do their job well, Thurston recommends that healthcare organizations give them enough time and resources to explore and understand the existing data quality.

“That exploration time needs to be built in so the data quality manager can try things out,” he says. “The manager needs to have that type of outlook and should know the data better than anyone else.”

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