An Evaluation of Patient Safety Event Report Categories Using Unsupervised Topic Modeling.
Journal:
Methods of information in medicine
Published Date:
Apr 2, 2015
Abstract
OBJECTIVE: Patient safety event data repositories have the potential to dramatically improve safety if analyzed and leveraged appropriately. These safety event reports often consist of both structured data, such as general event type categories, and unstructured data, such as free text descriptions of the event. Analyzing these data, particularly the rich free text narratives, can be challenging, especially with tens of thousands of reports. To overcome the resource intensive manual review process of the free text descriptions, we demonstrate the effectiveness of using an unsupervised natural language processing approach.