There is an old saying among computer programmers and health IT pros — garbage in, garbage out. It means that no matter how great our technologies are, bad data input results in bad data output. For health IT professionals, like Telligen’s Stan Rankins, Integration Architect, ensuring data quality is becoming even more important.

In 2020, Stan and 20 other CMS measure development contractors were selected by The National Quality Forum (NQF) to serve on a technical expert panel to explore electronic health record (EHR) data quality issues and recommend solutions for addressing them. The project, funded by the Centers for Medicare & Medicaid Services (CMS), is a step toward fulfilling the agency’s goal of reporting all quality measures digitally by 2030.

While electronic Clinical Quality Measures (eCQMs) are viewed as the best option for a digital reporting future, their promise has yet to be fully realized. “In a perfect world, all quality data would be held within reliable, uniform systems capable of collecting consistent data from a variety of sources,” says Stan.

Instead, providers struggle with complex reporting requirements and the high burden posed by eCQM implementation, data capture, and reporting. This is compounded by what the National Committee for Quality Alliance (NCQA) describes in a recent report as, “performance incentives [based] on insufficiently validated data processed through complex systems prone to error.”

To better understand these issues, Stan and the NQF panel spent 18-months assessing EHR data quality challenges and their impact on the eCQM lifecycle (i.e., development, endorsement, and implementation). Their findings are summarized in two reports — an environmental scan capturing eCQM-related challenges and final recommendations for meeting those challenges.

For Stan, participation in the NQF technical expert panel offered an opportunity to be a part of the digital reporting solution which he summarizes as the need for, “standardized, interoperable e-measures with standard specifications for data collection.”

A summary of the panel’s final recommendations for the Department of Health and Human Services, CMS, and NQF include:

  • Awarding incentives and/or grants to health IT vendors implementing eCQMs and EHR-sourced measures into their products
  • Increasing initiatives around a national testing collaborative and test bed efforts
  • Strengthening patient health records by aligning use cases and measures across multiple settings
  • Determining cost and/or ROI related to increasing measure testing, employing user groups, and developing an EHR data catalog
  • Building out existing EHR data quality frameworks like the Fast Healthcare Interoperability Resource (FHIR) model
  • Expanding the measures outside EHR data to include manual and electronic abstraction
  • Increasing the investment and use of natural language processing tools