Customer Experience and Design

Quality Reporting Data Architecture (QRDA) Primer

One of the key ways to improve productivity in healthcare is to become more efficient at interoperability within a healthcare organization and between healthcare organizations. Sharing quality reporting results is a good example of a healthcare area faced with challenges in interoperability and efficiency. According to the Agency for Healthcare Research & Quality, the United States healthcare system has challenges with using data for Quality Performance Measurement including, but not limited to:

  • Time-consuming and problematic operations for data acquisition from electronic systems
  • Multiple and disparate systems within health care organizations complicate data mining and coordination of efforts
  • Resource-intensive data mapping efforts to link systems and performance measurement data requirements
  • Conflicts or differences between administrative data sets
  • Physicians and providers struggle to meet increasing demands for performance data

A solution is in sight to improve or eliminate these problems by using the Quality Reporting
Document Architecture or QRDA for short. The purpose of the QRDA is to develop a standard for healthcare information systems to communicate quality measurement data across disparate systems in a standardized fashion. The QRDA supports the efficient collection, aggregation and reporting of quality measurement information for sharing among providers within a healthcare system or providers from different healthcare systems. The architecture will support the exchange of quality data between providers and requestors of that information (e.g. QIOs, payers, accrediting orgs, etc.).

In today’s healthcare IT environment, a healthcare provider sends one set of quality measure information to multiple requestors of quality data. This is a time consuming task and each quality data set is custom to the requestor of the data. Through the adoption of the HL7 V3, QRDA set, Quality Reporting Document Architecture would standardize one set of measure information to be sent to multiple requestors of quality data, thus improving productivity and allowing automation of the consumption of the data.


The key idea is that standardizing the quality measure sets and the reporting details of each quality measure set will simplify the communication of standard results from one healthcare organization to another. The use of Content Document Architecture for QRDA sets up the interoperability between the creator of quality measure reporting and the receiving organization. An example of the internal QRDA Document Architecture would include the following data elements: Measure Name, Measure Set, Submitting Entity, Receiving Entity, Procedure Code, Diagnosis Code, Lab Results, Criteria, Patient/Provider data, etc. This abstraction approach allows for the creation of new measures in the future and growth in use of current quality measures.

In summary, Quality Reporting Data Architecture (QRDA) is an evolutionary step in healthcare interoperability that can simplify communication of quality measure results and allow the movement of those results within and between healthcare organizations. The standardization of the format of quality results will improve the ease of creating comparative results for quality departments as well. Let’s start slowly and expand into disease registries, right?

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Martin Sizemore

Enterprise Architect with specialized skills in Enterprise Application Integration (EAI) and Service Oriented Architecture (SOA). Consultant and a trusted advisor to Chief Executive Officers, COOs, CIOs and senior managers for global multi-national companies and healthcare organizations. Deep industry experience as a consultant in manufacturing, healthcare and financial services industries. Broad knowledge of IBM hardware and software offerings with numerous certifications and recognitions from IBM including On-Demand Computing and SOA Advisor. Experienced with Microsoft general software products and architecture, including Sharepoint and SQL Server. Deep technical skills in system integration, system and software selection, data architecture, data warehousing and infrastructure design including virtualization.

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