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The impact of emerging standards adoption on automated quality reporting
Paul C Fu1, Daniel Rosenthal, Joshua M Pevnick
1Harbor-UCLA Medical Center, Torrance, CA 90502, USA. pfu@labiomed.org
Abstract:
Current quality measurement processes are labor-intensive, involving manual chart reviews and use of paper-based quality measures that vary in format and definitions from measure to measure. Automated quality reporting is considered by many to be an important tool that will help close the gaps in the quality of US health by increasing the timeliness, effectiveness, and use of quality assessment. In 2007, the US Department of Health and Human Services Office of the National Coordinator for Health Information Technology (ONC) funded three Nationwide Health Information Network (NHIN) health information exchanges (HIE) to demonstrate the feasibility of automated quality reporting by using existing or emerging standards to aggregate information from multiple providers, transmit patient-level quality data in standardized formats, perform an automated quality assessment, and generate a quality report document for electronic transmission. Long Beach Network for Health (LBNH), a NHIN Cooperative HIE, developed a web-based, real-time quality assessment service that calculates quality of care measure using clinical data aggregated through a HIE. LBNH used a set of draft standards to demonstrate automated quality reporting, but noted three important recommendations for future work. First, greater coordination is needed around initiatives that address the gaps in electronic quality measurement standards and processes, including strong Federal involvement and guidance. Second, a harmonized, evergreen quality use case is needed to provide stakeholders with a common understanding on the constantly evolving approaches towards automated quality measurement and reporting. Finally, there needs to be substantial investment in building on existing work and developing a comprehensive set of data and messaging standards to preserve semantic interoperability of quality measure data.
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