Cognitive Support During High-Consequence Episodes of Care in Cardiovascular Surgery

被引:0
|
作者
Conboy, Heather M. [1 ]
Avrunin, George S. [1 ]
Clarke, Lori A. [1 ]
Osterweil, Leon J. [1 ]
Goldman, Julian M. [2 ,3 ]
Yule, Steven J. [2 ,3 ]
Zenati, Marco A. [2 ,3 ]
Christov, Stefan C. [4 ]
机构
[1] Univ Massachusetts, Coll Informat & Comp Sci, Amherst, MA 01003 USA
[2] BWH, STRATUS Simulat Ctr, MGH, Anesthesiol, Boston, MA USA
[3] Harvard Med Sch, VABHCS, Div Cardiac Surg, Boston, MA USA
[4] Quinnipiac Univ, Dept Engn, Hamden, CT USA
基金
美国国家科学基金会; 美国国家卫生研究院;
关键词
process modeling; checklists; situation management; HEART-ASSOCIATION;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Despite significant efforts to reduce preventable adverse events in medical processes, such events continue to occur at unacceptable rates. This paper describes a computer science approach that uses formal process modeling to provide situationally aware monitoring and management support to medical professionals performing complex processes. These process models represent both normative and non-normative situations, and are validated by rigorous automated techniques such as model checking and fault tree analysis, in addition to careful review by experts. Context-aware Smart Checklists are then generated from the models, providing cognitive support during high-consequence surgical episodes. The approach is illustrated with a case study in cardiovascular surgery.
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页数:3
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