Author(s): Cheligeer C; Southern DA; Yan J; Wu G; Pan J; Lee S; Martin EA; Jafarpour H; Eastwood CA; Zeng Y; Quan H;

Objectives: Adverse event detection from Electronic Medical Records (EMRs) is challenging due to the low incidence of the event, variability in clinical documentation, and the complexity of data formats. Pulmonary embolism as an adverse event (PEAE) is particularly difficult to identify using exi ...

Article GUID: 40105654

Author(s): Wu G; Eastwood C; Zeng Y; Quan H; Long Q; Zhang Z; Ghali WA; Bakal J; Boussat B; Flemons W; Forster A; Southern DA; Knudsen S; Popowich B; Xu Y;

Background: Measurement of care quality and safety mainly relies on abstracted administrative data. However, it is well studied that administrative data-based adverse event (AE) detection methods are suboptimal due to lack of clinical information. Electronic medical records (EMR) have been widely ...

Article GUID: 36197944