Extracting cancer quality indicators from electronic medical records: evaluation of an ontology-based virtual medical record approach

Measuring quality in clinical care is a time-consuming manual task. The vast amounts of clinical data collected through electronic medical records (EMRs) create an opportunity to develop tools that automatically assess quality indicators; however, the diversity of EMR implementations limits the ability to implement general, reusable methods. We evaluate an ontology-based virtual medical record (VMR) approach as a standardized, sharable methodology for defining data abstractions needed for quality of care assessment. Using a set of cancer quality indicators, we conducted a requirements analysis for modeling these abstractions with an OWL-based VMR. We found that the VMR approach needs to be extended to support population-based aggregations of clinical events, models of intended versus completed actions, and models of workflow and delivery systems. Incorporating the patient perspective on quality also requires additional extension of the VMR. We are using these results to create a virtual quality record based on EMR data.