| Literature DB >> 30815092 |
Yufan Guo1, Joy Wu1, Tyler Baldwin1, David Beymer1, Vandana V Mukherjee1, Tanveer F Syeda-Mahmood1.
Abstract
EMR systems are intended to improve patient-centered care management and hospital administrative processing. However, the information stored in EMRs can be disorganized, incomplete, or inconsistent, creating problems at the patient and system level. We present a technology that reconciles inconsistencies between clinical diagnoses and administrative records by analyzing free-text notes, problem lists and recorded diagnoses in real time. A fully integrated pipeline has been developed for efficient, knowledge-driven extraction, normalization, and matching of disease terms among structured and unstructured data, with modular precision of 94-98% on over 1000 patients. This cognitive data review tool improves the path from diagnosis to documentation, facilitating accurate and timely clinical and administrative decision-making.Entities:
Mesh:
Year: 2018 PMID: 30815092 PMCID: PMC6371384
Source DB: PubMed Journal: AMIA Annu Symp Proc ISSN: 1559-4076