Laying the groundwork for enterprise-wide medical language processing services: architecture and process.
A systematic and standard process for capturing information within free-text clinical documents could facilitate opportunities for improving quality and safety of patient care, enhancing decision support, and advancing data warehousing across an enterprise setting. At Partners HealthCare System, the Medical Language Processing (MLP) services project was initiated to establish a component-based architectural model and processes to facilitate putting MLP functionality into production for enterprise consumption, promote sharing of components, and encourage reuse. Key objectives included exploring the use of an open-source framework called the Unstructured Information Management Architecture (UIMA) and leveraging existing MLP-related efforts, terminology, and document standards. This paper describes early experiences in defining the infrastructure and standards for extracting, encoding, and structuring clinical observations from a variety of clinical documents to serve enterprise-wide needs.
Chen
Elizabeth S
ES
Center for Clinical & Translational Science, University of Vermont, Burlington, VT, USA.
Maloney
Francine L
FL
Shilmayster
Eugene
E
Goldberg
Howard S
HS
D057225:Data Mining / Q000379:methods / Q000592:standards*; D057286:Electronic Health Records; D009323:Natural Language Processing; D012984:Software; D018875:Vocabulary, Controlled