Comparison of methods of alert acknowledgement by critical care clinicians in the ICU setting.

Authors:
Dr Andrew M Harrison, MD, PhD
Dr Andrew M Harrison, MD, PhD
Mayo Clinic
Postdoctoral researcher
Clinical Informatics
Rochester, MN | United States
Charat Thongprayoon
Charat Thongprayoon
Mayo Clinic
Phoenix | United States
Christopher A Aakre
Christopher A Aakre
Mayo Clinic
United Kingdom
Jack Y Jeng
Jack Y Jeng
Mayo Medical School
Rochester | United States
Mikhail A Dziadzko
Mikhail A Dziadzko
Mayo Clinic
Rochester | United States
Ognjen Gajic
Ognjen Gajic
Mayo Clinic
United States
Brian W Pickering
Brian W Pickering
Mayo Clinic
United States
Vitaly Herasevich
Vitaly Herasevich
Mayo Clinic
United States

PeerJ 2017 14;5:e3083. Epub 2017 Mar 14.

Department of Anesthesiology, Mayo Clinic , Rochester , MN , United States of America.

Background: Electronic Health Record (EHR)-based sepsis alert systems have failed to demonstrate improvements in clinically meaningful endpoints. However, the effect of implementation barriers on the success of new sepsis alert systems is rarely explored.

Objective: To test the hypothesis time to severe sepsis alert acknowledgement by critical care clinicians in the ICU setting would be reduced using an EHR-based alert acknowledgement system compared to a text paging-based system.

Study Design: In one arm of this simulation study, real alerts for patients in the medical ICU were delivered to critical care clinicians through the EHR. In the other arm, simulated alerts were delivered through text paging. The primary outcome was time to alert acknowledgement. The secondary outcomes were a structured, mixed quantitative/qualitative survey and informal group interview.

Results: The alert acknowledgement rate from the severe sepsis alert system was 3% ( = 148) and 51% ( = 156) from simulated severe sepsis alerts through traditional text paging. Time to alert acknowledgement from the severe sepsis alert system was median 274 min ( = 5) and median 2 min ( = 80) from text paging. The response rate from the EHR-based alert system was insufficient to compare primary measures. However, secondary measures revealed important barriers.

Conclusion: Alert fatigue, interruption, human error, and information overload are barriers to alert and simulation studies in the ICU setting.

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http://dx.doi.org/10.7717/peerj.3083DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5354075PMC

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March 2017
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(Supplied by CrossRef)
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Dziadzko et al.
BMC Medical Informatics and Decision Making 2016
2014 top 10 list of health technology hazards
ECRI-Institute et al.
Health Devices Journal 2013
Distraction: an assessment of smartphone usage in health care work settings
Gill et al.
Risk Management and Healthcare Policy 2012

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