Automated coded ambulatory problem lists: evaluation of a vocabulary and a data entry tool

Background: Problem lists are fundamental to electronic medical records (EMRs). However, obtaining an appropriate problem list dictionary is difficult, and getting users to code their problems at the time of data entry can be challenging. Objective: To develop a problem list dictionary and search algorithm for an EMR system and evaluate its use. Methods: We developed a problem list dictionary and lookup tool and implemented it in several EMR systems. A sample of 10,000 problem entries was reviewed from each system to assess overall coding rates. We also performed a manual review of a subset of entries to determine the appropriateness of coded entries, and to assess the reasons other entries were left uncoded. Results: The overall coding rate varied significantly between different EMR implementations (63–79%). Coded entries were virtually always appropriate (99%). The most frequent reasons for uncoded entries were due to user interface failures (44–45%), insufficient dictionary coverage (20–32%), and non-problem entries (10–12%). Conclusion: The problem list dictionary and search algorithm has achieved a good coding rate, but the rate is dependent on the specific user interface implementation. Problem coding is essential for providing clinical decision support, and improving usability should result in better coding rates.