Appl Clin Inform 2017; 08(01): 80-96
DOI: 10.4338/ACI-2016-10-RA-0164
Research Article
Schattauer GmbH

Development and Feasibility of a Real-Time Clinical Decision Support System for Traumatic Brain Injury Anesthesia Care

Taniga Kiatchai
1  Department of Anesthesiology & Pain Medicine, University of Washington, Seattle, WA
2  Harborview Injury Prevention and Research Center, Seattle, WA
,
Ashley A. Colletti
1  Department of Anesthesiology & Pain Medicine, University of Washington, Seattle, WA
,
Vivian H. Lyons
2  Harborview Injury Prevention and Research Center, Seattle, WA
3  Department of Epidemiology, University of Washington, Seattle, WA
,
Rosemary M. Grant
4  Clinical Education, Harborview Medical Center, Seattle, WA
,
Monica S. Vavilala
1  Department of Anesthesiology & Pain Medicine, University of Washington, Seattle, WA
2  Harborview Injury Prevention and Research Center, Seattle, WA
5  Department of Pediatrics, University of Washington, Seattle, WA
6  Department of Neurological Surgery and Global Health Medicine, University of Washington, Seattle, WA
,
Bala G. Nair
1  Department of Anesthesiology & Pain Medicine, University of Washington, Seattle, WA
2  Harborview Injury Prevention and Research Center, Seattle, WA
› Author Affiliations
FundingThis work was supported by a grant from National Institute of Health [R01 NS072308–05]
Further Information

Publication History

Received: 06 October 2016

Accepted: 26 January 2016

Publication Date:
20 December 2017 (online)

Summary

Background: Real-time clinical decision support (CDS) integrated with anesthesia information management systems (AIMS) can generate point of care reminders to improve quality of care. Objective: To develop, implement and evaluate a real-time clinical decision support system for anesthetic management of pediatric traumatic brain injury (TBI) patients undergoing urgent neurosurgery.

Methods: We iteratively developed a CDS system for pediatric TBI patients undergoing urgent neurosurgery. The system automatically detects eligible cases and evidence-based key performance indicators (KPIs). Unwanted clinical events trigger and display real-time messages on the AIMS computer screen. Main outcomes were feasibility of detecting eligible cases and KPIs, and user acceptance.

Results: The CDS system was triggered in 22 out of 28 (79%) patients. The sensitivity of detecting continuously sampled KPIs reached 93.8%. For intermittently sampled KPIs, sensitivity and specificity reached 90.9% and 100%, respectively. 88% of providers reported that CDS helped with TBI anesthesia care.

Conclusions: CDS implementation is feasible and acceptable with a high rate of case capture and appropriate generation of alert and guidance messages for TBI anesthesia care.