Addressing the Data Quality Conundrum in Healthcare: Five Gaps to Close

It is increasingly important for health systems to ensure the highest levels of data quality across the entire patient journey. Quality patient data is essential for EHR accuracy, patient safety and informed clinical decision-making.

Correct and complete patient information also improves end-user satisfaction and staff productivity while mitigating risk of revenue leakage and patient frustration. Furthermore, the benefits of health data quality increase exponentially as information is digitally shared across the healthcare ecosystem through interoperability and health information exchange.

With the U.S. predicted to spend $19.9B on EHRs by the end of 2024 and so much riding on the accuracy of patient data, now is the time for health systems to improve and protect the patient data they create. EHR vendors can’t, and won’t, do it all.

Healthcare provider organizations (HCOs) must invest time, money and resources into their data quality programs. The downside cost is just too high.

In our work with health systems nationwide, we see five data quality areas commonly overlooked and unbudgeted during major EHR transitions. These five areas all contribute to cleaner and more complete patient data.

This white paper explores each of these steps and provides valuable advice for health IT leaders making major EHR and other IT system transitions in the year ahead.

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IT leaders who commit to optimal patient data quality for each system implementation ultimately improve our nation’s healthcare outcomes overall. Together we can support optimal healthcare delivery, informed decision-making, and trustworthy patient-provider relationships. The first step is better patient data quality.