At Georgetown, outpatients are scanned predominately during the day, while inpatients and emergency patients make up most of the night imaging volume, according to presenter Dr. Linda Kelahan.
"As a second-year [resident] beginning call, it was surprising to realize the differences in pathology on call versus the workday," she told AuntMinnie.com.
Kelahan sought to create a real-time dashboard of acute call cases to measure residents' exposure to such cases. This software would benefit residents and also help faculty -- especially program directors -- identify potential deficiencies in exposure to these types of cases prior to beginning call, she said.
"Our dashboard tracks not only positive high-acuity cases, but also negative cases when there was a high clinical suspicion (i.e., a clinical history of right lower quadrant pain and a normal appendix on a CT scan)," she said. "Because the dashboard uses natural language processing (NLP) algorithms, we can passively monitor, or survey, resident progress without any additional effort by the human. This provides valuable information to residents without introducing extra work."
Having a real-time dashboard for these cases enables objective resident feedback and identification of potential educational deficiencies, Kelahan said. The dashboard also displays the accession numbers of cases, essentially acting as a case repository for resident education. In addition, the program director can access resident statistics for faculty feedback.
"It is our hope that our dashboard provides a mechanism by which to prepare first-year residents for call," she said. "We also hope to encourage the use of natural language algorithms in dashboard development."
