NDLI: A comparison of alerting strategies for hemorrhage identification during prehospital emergency transport

Content Provider	IEEE Xplore Digital Library
Author	Jianbo Liu Reisner, A.T. Edla, S. Reifman, J.
Copyright Year	2014
Description	Author affiliation: Dept. of Defense, USAMRMC, Fort Detrick, MD, USA (Jianbo Liu) \|\| BHSAI, USAMRMC, Fort Detrick, MD, USA (Reisner, A.T.; Edla, S.; Reifman, J.)
Abstract	Early and accurate identification of physiological abnormalities is one feature of intelligent decision support. The ideal analytic strategy for identifying pathological states would be highly sensitive and highly specific, with minimal latency. In the field of manufacturing, there are well-established analytic strategies for statistical process control, whereby aberrancies in a manufacturing process are detected by monitoring and analyzing the process output. These include simple thresholding, the sequential probability ratio test (SPRT), risk-adjusted SPRT, and the cumulative sum method. In this report, we applied these strategies to continuously monitored prehospital vital-sign data from trauma patients during their helicopter transport to level I trauma centers, seeking to determine whether one strategy would be superior. We found that different configurations of each alerting strategy yielded widely different performances in terms of sensitivity, specificity, and average time to alert. Yet, comparing the different investigational analytic strategies, we observed substantial overlap among their different configurations, without any one analytic strategy yielding distinctly superior performance. In conclusion, performance did not depend as much on the specific analytic strategy as much as the configuration of each strategy. This implies that any analytic strategy must be carefully configured to yield the optimal performance (i.e., the optimal balance between sensitivity, specificity, and latency) for a specific use case. Conversely, this also implies that an alerting strategy optimized for one use case (e.g., long prehospital transport times) may not necessarily yield performance data that are optimized for another clinical application (e.g., short prehospital transport times, intensive care units, etc.).
Sponsorship	IEEE Eng. Med. Biol. Soc.
Starting Page	2670
Ending Page	2673
File Size	751959
Page Count	4
File Format	PDF
ISBN	9781424479290
ISSN	1557170X
DOI	10.1109/EMBC.2014.6944172
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-08-26
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Biomedical monitoring Sensitivity Accuracy Hemorrhaging Process control Monitoring Medical diagnostic imaging
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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