Enhancing the expressiveness of structured reporting systems

Abstract

The overall goal of this research is to build a structured reporting system that reduces the cost, delays, and inconvenience associated with conventional dictation and speech recognition systems. We have implemented such a structed reporting system for radiology that replaces current dictation and transcription processes by allowing radiologists and other imaging professionals to select imaging findings from a medical lexicon. The system uses an imaging-specific information model, called a “description set’, to organize selected terms in a relational database. Unique features of the knowledge representation that enhance its expressiveness include its ability to codify uncertainty about an imaging observation and to represent explicity the logical relationships among imaging findings. In addition, the system does not require the user to fill in “blanks’ in a static text template. Instead, it allows entry of terms in arbitrary order and uses automated text-generation techniques to create a text report that referring physicians are accustomed to receiving. In parallel, the system also produces a multimedia report that the referring physician can use as a quick reference. Unlike the results of conventional dictation or speech recognition, each finding is coded in a relational database for later information processing. Thus, the structured report database can be used to index images by content, to provide real-time decision support, to enhance radiologists’ performance, to conduct exploratory clinical research, and to transmit imaging report data to computer-based patients record systems.