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NQF Issues Guidelines for High EHR Data Quality, Quality Measures

The National Quality Forum responded to its initial environmental scan with its final recommendations for EHR data quality.

Improved EHR data quality can be utilized to support automated clinical quality measurement, according to The National Quality Forum (NQF).  

NQF identified challenges that impact the healthcare performance measures from a development, endorsement, and implementation standpoint using EHR data and recommendations from a technical expert panel (TEP).

NQF established the multi-stakeholder TEP to create two reports. The first was an environmental scan report that recognized the current EHR data quality issues and the second was a final recommendations report, the Technical Expert Panel on Electronic Health Record Data Quality Best Practices for Increased Scientific Acceptability.

The initial environmental scan report described challenges associated with electronic clinical quality measures basics (eCQMs) implementation, unstructured data, and NQF endorsement. It also identified an existing framework for assessing EHR and guidance from standard-setting bodies.

This final recommendation report identified and developed solutions to address the key challenges established in the environmental scan. It assessed key phases of the measure lifecycle, including development, endorsement, and implementation.

TEP recommended opportunities for expanding the availability and accessibility to EHR data to measure developmental challenges. TEP also recommended increased agency interactions and federal initiatives around national testing collaborative and test bed efforts.

The group said the Department of Health and Human Services (HHS) should offer health IT providers and health IT vendors credit towards federal program participation to boost measure development and establish recognition programs for measure development.

Furthermore, the Centers for Medicare and Medicaid Services (CMS) should contemplate aligning use cases and measures across multiple settings in an effort to ensure care quality and an extensive patient health record, wrote TEP.

Through its measure evaluation criteria and Consensus Development Process (CDP), NQF endorses measures for use in accountability programs and public reporting.

Next, TEP wrote several recommendations to NQF aiming to address challenges during the measure endorsement process:

  • Adding EHR-sourced measure and scientific methods expertise to develop guidance for evaluating scientific acceptability of EHR-sourced measures
  • Assessing and updating both the measure evaluation criteria and the measure evaluation processes to boost clarity and decrease EHR-sourced measure conflicting criteria
  • Providing updated measure evaluation guidance to current committees and measure developers
  • Considering additional experts in EHR-sourced measures to support the Scientific Methods Panel and current committees
  • Providing added technical assistance to measure developers prior to measure submission

Next, TEP recommended CMS or ONC establish and award grants to health IT vendors to hire professionals to implement eCQMs and EHR-sourced measures into their health IT products.

Looking forward, the group said opportunities exist to describe the cost and return on investment for increased measure testing, the utilization of existing user groups, and the development of an EHR data catalog.

TEP pointed to potential opportunities that could arise from the Fast Healthcare Interoperability Resources (FHIR) specification, the Observational Medical Outcomes Partnership (OMOP), the CMS Post-Acute Care Interoperability (PACIO) project, and the Health Level Seven International (HL7) Gravity project.

The group also recommended further development and use of existing frameworks related to EHR data quality and cited the NQF Feasibility Scorecard and the FHIR Maturity Model as two examples. It also recommended including manually and electronically abstracted EHR data to expand the measures outside the scope of current EHR data.

Finally, TEP recommended further investment in learning more about natural language processing (NLP) tools to make these tools more prevalent in the future.

“Although the recommendations in this report primarily focus on opportunities for HHS, CMS and NQF, it should be noted that these opportunities to advance development, endorsement, and implementation of this measure type is not limited to only these stakeholder groups,” concluded TEP. “It is recommended that future work should focus on opportunities for additional stakeholders beyond HHS, CMS and NQF who can impact EHR data quality issues.”

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