Digital Quality and Related Standards Overview

 A previous blog discussed FHIR-CQL—the most important dQM standard for the future—and its predecessor, QDM-CQL. This blog takes a broader view of relevant standards. 

It's easy to get confused by existing and emerging standards in the transition to digital quality measures. In addition to NCQA measures (which include 11 ECDS measures for MY 2020 in addition to FHIR-CQL), there are other partially overlapping measure sets, including pharmacy measures (PQA), CMS measures, state measures and emerging patient-reported outcomes measures (PROM), and a host of related standards relevant to health plans generally. 

Yet the full potential of digital quality measures will only be realized if the data acquisition for quality measurement is also standardized and streamlined. We need a broader, more comprehensive approach beyond dQM standards—a quality (or clinical) data ecosystem whose primary objective is secure, efficient sharing and collecting of clinical data. HL7 interoperability standards are the most relevant. The
second-generation document standards CCD and CCDA are widely adopted and used. The third-generation, modern API-technology-based FHIR is rapidly being adopted across the industry and widely mandated by recent regulations. 

All these standards are concerned mostly with defining the organization, assembly, transport and disassembly of data, but there is another important set of standards that defines the actual data elements—the content or values—so every user and system can confidently interpret
the data’s “meaning.” Examples of these standards are ICD-10 diagnoses codes, SNOMED clinical terminology and LOINC codes for lab observations. 

But although these standards are important, there are two pressing questions: 

• Can we move forward with dQM without knowing/understanding and using some or most of these standards?
• How can we possibly comprehend and align all these standards for broad and uniform use? 

The answer to the first question is “yes.” We can use digital measures to report data as it exists today, with all the issues and pitfalls of the traditional measures and mechanics. But stopping there would be like driving 10 mph on an autobahn: So much more is possible!  

And that brings us to FHIR. When we browse the internet, we simply open a browser on any computer, anywhere in the world, enter a URL and the page loads instantly. It just happens, we don’t need to know the dozens of discrete steps and systems that make it happen. FHIR can
solve the issue of complexity for clinical interoperability in a similar way. It has the capability to “incorporate” or “reference” other standards such as SNOMED, which means we don’t need to deal with them separately and explicitly—and that’s significant. Which answers the second question: in a mature data ecosystem built around FHIR, the vast majority of stakeholders don’t need to comprehend all the underlying standards and technologies. Using FHIR properly to access and process clinical/quality data will eventually be similar to browsing the internet: It just works!  

FHIR might not be a silver bullet—we’re not there yet—but we can move forward with dQMs, knowing that the entire ecosystem is evolving in the right direction. 

Additional Resources

• NCQA page on ECDS: https://www.ncqa.org/hedis/the-future-of-hedis/hedis-electronic-clinical-data-system-ecds-reporting/ 
• HHS National Health Quality Roadmap: https://www.hhs.gov/about/leadership/eric-d-hargan/quality-roadmap/index.html 

Share your thoughts in the community forum.  

• Do you understand how traditional, ECDS and dQMs differ? 
• How deep of an understanding of these standards do you have? 
• Given your job/role, how deep of an understanding do you think you need to be effective going forward?
• Does your organization have a plan/roadmap to adapt to the digital quality ecosystem?