Strategies for Medical Data Extraction and Presentation Part 1: Current Limitations and Deficiencies

Abstract

Data overload is a burgeoning challenge for the medical imaging community; with resulting technical, clinical, and economic ramifications. A primary concern for radiologists is the timely, efficient, and accurate extraction of imaging and clinical data, which collectively are essential in determining accurate diagnosis. In current practice, imaging data retrieval is limited by the fact that imaging and report data are de-coupled from one another, along with the non-standardized and often ambiguous free text data contained within narrative radiology reports. Clinical data retrieval is equally challenging and flawed by the lack of information system integration, paucity of clinical order entry data, and diminished role of the technologist in providing clinical data. These combined factors have the potential to adversely affect radiologist performance and clinical outcomes by diminishing workflow, report accuracy, and diagnostic confidence. New and innovative strategies are required to improve and automate data extraction and presentation, in a context- and user-specific fashion.