A Mixed Methods Task Analysis of the Implementation and Validation of EHR-Based Clinical Quality Measures

Abstract

Clinical quality measures (CQMs) are important tools for the assessment and improvement of health care quality. Federal requirements initially set forth in the American Recovery and Reinvestment Act, and advanced in subsequent stages of the requirements, codified electronic health record (EHR)-based CQM reporting, and have made automated CQM implementation a priority amongst the clinical and informatics communities. Nevertheless, the processes surrounding CQM implementation and validation remain complex, time-consuming, and largely undefined. We collected issue-tracking data during the course of an agile and rigorous collaborative project to build an analytics platform for the Knight Cardiovascular Institute at OHSU, with nine heart failure CQMs defined by the American College of Cardiology (ACC) as an exemplar. Using a mixed methods approach we provide an overview of our CQM implementation and validation process, identify major roadblocks and bottlenecks, and make recommendations for other professionals working in the area of health care quality assessment and improvement.

Figure 1.

Number of tasks and time spent on tasks in each category, by measure. Tasks assigned to all measures are not included here.

Figure 2.

By-measure workflows. Concurrent tasks within categories will overlap.

Figure 3.

Expected process, which is mostly linear with specific instances of iteration at the development and debugging stages, and observed process, which may include substantial iteration.