Report: NQF releases Quality Data Set for clinical EHRs
The National Quality Forum (NQF) has released its Quality Data Set (QDS) report, which addresses the gap between EHR systems and the lack of quality measure specifications in clinical use EHRs.
The report, “Health IT: Automation of Quality Measurement: Quality Data Set and Data Flow,” was drafted by the NQF Health IT Expert Panel (HITEP) and focused on measures for the capture and quality of data for EHRs that need to be more clearly and consistently defined in the wake of the American Recovery and Reinvestment Act (ARRA).
This is the second report from HITEP concerning EHRs. The first recommended 11 data categories and 39 data types for a set of 84 high-priority performance measures to enhance capabilities for the electronic capture of data for quality measurement. That information is now utilized by the Healthcare IT Technology Standards Panel (HITSP) and many of those measures have been incorporated into certification requirements for EHRs by the Certification Commission for Health IT (CCHIT).
HITEP created two work groups--the QDS Workgroup and the Date Flow Workgroup- to focus on standardizing data elements and creating a framework of characteristics to represent data used within measures based on their representation within EHRs, respectively.
The QDS contains three levels of information: standard elements, quality data elements and data flow attributes.
Standard data refers to information identified by a data element name, a code set and a code list composed of one or more enumerated values. Quality data elements are pieces of information that are used in quality measures to describe part of the clinical process.
Data flow attributes describe the authoritative source for the information that is required to represent any quality data element, including the data source, recorder, setting and health record field.
HITEP offered the following recommendations for further work to enhance the development and use of the QDS and electronic data sources:
The NQF concluded that future work should include the ongoing maintenance of the QDS, reusable code lists and the development of a measure authoring tool to ease incorporation of the QDS into the quality measurement development process.
The report was supported by the Agency for Healthcare Research and Quality (AHRQ).
The report, “Health IT: Automation of Quality Measurement: Quality Data Set and Data Flow,” was drafted by the NQF Health IT Expert Panel (HITEP) and focused on measures for the capture and quality of data for EHRs that need to be more clearly and consistently defined in the wake of the American Recovery and Reinvestment Act (ARRA).
This is the second report from HITEP concerning EHRs. The first recommended 11 data categories and 39 data types for a set of 84 high-priority performance measures to enhance capabilities for the electronic capture of data for quality measurement. That information is now utilized by the Healthcare IT Technology Standards Panel (HITSP) and many of those measures have been incorporated into certification requirements for EHRs by the Certification Commission for Health IT (CCHIT).
HITEP created two work groups--the QDS Workgroup and the Date Flow Workgroup- to focus on standardizing data elements and creating a framework of characteristics to represent data used within measures based on their representation within EHRs, respectively.
The QDS contains three levels of information: standard elements, quality data elements and data flow attributes.
Standard data refers to information identified by a data element name, a code set and a code list composed of one or more enumerated values. Quality data elements are pieces of information that are used in quality measures to describe part of the clinical process.
Data flow attributes describe the authoritative source for the information that is required to represent any quality data element, including the data source, recorder, setting and health record field.
HITEP offered the following recommendations for further work to enhance the development and use of the QDS and electronic data sources:
- NQF should develop and maintain the QDS; involving all stakeholders;
- Develop measures that use the richness of all available data, focusing on clinical, patient-centered outcomes;
- Communicate with all stakeholders and seek their buy-in, educate and train the quality measure supply chain regarding the QDS and its associated authoring tool;
- Set a timeline for QDS implementation, including demonstrated functionality, workflow assessment and enumerate the essential activities and stakeholders;
- NQF should quickly incorporate the QDS into the Consensus Development Process; and
- Future quality measure development should use the National Priorities and Goals as a guide.
The NQF concluded that future work should include the ongoing maintenance of the QDS, reusable code lists and the development of a measure authoring tool to ease incorporation of the QDS into the quality measurement development process.
The report was supported by the Agency for Healthcare Research and Quality (AHRQ).