Standardization and Automatic Extraction of Quality Measures in an Ambulatory Electronic Medical Record (EMR)

Citizens Memorial Healthcare (CMH) established the standardization necessary for data capture of 62 quality measures in its ambulatory electronic medical record (EMR) system and demonstrated the efficiency and accuracy of using automated data extraction to perform quality measurement and reporting in the ambulatory care setting. CMH standardized and integrated data capture for quality-of-care measurement into the normal documentation of care within the ambulatory EMR. The standardization efforts include both tools and processes for physician documentation, medication prescription ordering, and collection and recording of allergies. Workflow analysis was used to examine existing processes and design new, standard processes to be implemented. Proven adoption strategies, such as PatientBridge and Family Team Care, will be implemented in the future to assist providers in learning and adapting to the changes in processes.

Using the resulting standardized data elements, CMH implemented an automated system for data extraction of quality measures in the ambulatory setting. Data were mapped, linked, extracted, normalized, analyzed, reported, and exported by the Institute for Health Metrics (IHM), a quality data extraction partner. The study was conducted in 15 primary care, certified rural health clinics, and specialty physician practices affiliated with CMH. Specifically, the investigators sought to determine if:

1. All of the data needed for quality measurement available in an ambulatory EMR can be captured in data elements readily available for automated extraction if documentation processes are standardized, and
2. Automatic data extraction will be significantly more efficient and accurate when compared to the manual claims-coding method of quality measurement reporting utilized within the Centers for Medicare & Medicaid Services' Physician Quality Reporting Initiative (PQRI).

Results showed that while only 52 percent of providers who reported data to the PQRI successfully reported on 3 quality measures in 2009, CMH and IHM were able to extract and report on 62 measures. The results validate that quality reporting from an EMR system is more complete and accurate than manual coding. In addition, automated data extraction relied heavily on documentation queries, and without incentives and feedback, providers may not use the documentation queries that are needed for accurate quality measurement. Without provider use of those queries, quality measurement can be done but may not reflect the care provided.

Modifications and further standardization of the measures could improve use and measurement. Future studies are indicated on the use of quality measure queries, data fields, and assessments within an EMR system. Targeted feedback, workflow enhancement, and training are methods to be considered for further research.