Lessons learned in improving the adoption of a real-time NLP decision support system

Abstract

While most research in the NLP domain focuses on information accuracy, the adoption of NLP applications in healthcare extends beyond technical innovations. This study investigates the adoption issues of an NLP application in three different field sites. Using both quantitative log analysis and qualitative user interviews, we identified four main factors that affect NLP adoption: organizational culture and support, system usability, information quality and system reliability. These factors must be considered to ensure successful adoption of NLP applications that provide real-time decision support in a clinical care setting.