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Authors: James P. McGlothlin 1 ; Evan Crawford 1 ; Jesse Wyatt 2 ; Carlos Samayoa 2 ; Yana Vaks 2 ; Brenda Bruneau 2 ; Merrick Lopez 2 ; Anthony Moretti 2 ; Michele Wilson 2 and James Pappas 2

Affiliations: 1 Fusion Consulting Inc, United States ; 2 Loma Linda University Health System, United States

Keyword(s): Data Warehousing, Healthcare Analytics, Quality, Pediatric Intensive Care, Business Intelligence.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Business Analytics ; Cardiovascular Technologies ; Computing and Telecommunications in Cardiology ; Data Engineering ; Databases and Datawarehousing ; Decision Support Systems ; Decision Support Systems, Remote Data Analysis ; Health Engineering and Technology Applications ; Health Information Systems ; Healthcare Management Systems ; Knowledge-Based Systems ; Symbolic Systems

Abstract: Major events and surgeries are not the only sources of trauma during a hospital encounter. Many small, less invasive events such as shots, line placements, blood draws, and imaging studies happen throughout a patient’s hospital stay. Many of these less traumatic events have the potential to negatively impact patient outcomes by increasing the risk of hospital-acquired infections through skin invasions and exposure to organisms, reducing the patient experience by causing pain and frustration, increasing cost and causing other complications. The goal of this project is to reduce such events when they are not clinically required. This is an analytics project so this goal is facilitated by making accurate and meaningful information available to the appropriate personnel. This includes timely information to clinicians so they can alter treatment, and retrospective trend analysis to enable and track performance improvement and identify opportunities for additional process improvement.

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Paper citation in several formats:
McGlothlin, J.; Crawford, E.; Wyatt, J.; Samayoa, C.; Vaks, Y.; Bruneau, B.; Lopez, M.; Moretti, A.; Wilson, M. and Pappas, J. (2017). Poke-R - Using Analytics to Reduce Patient. In Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2017) - HEALTHINF; ISBN 978-989-758-213-4; ISSN 2184-4305, SciTePress, pages 362-369. DOI: 10.5220/0006174603620369

@conference{healthinf17,
author={James P. McGlothlin. and Evan Crawford. and Jesse Wyatt. and Carlos Samayoa. and Yana Vaks. and Brenda Bruneau. and Merrick Lopez. and Anthony Moretti. and Michele Wilson. and James Pappas.},
title={Poke-R - Using Analytics to Reduce Patient},
booktitle={Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2017) - HEALTHINF},
year={2017},
pages={362-369},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006174603620369},
isbn={978-989-758-213-4},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2017) - HEALTHINF
TI - Poke-R - Using Analytics to Reduce Patient
SN - 978-989-758-213-4
IS - 2184-4305
AU - McGlothlin, J.
AU - Crawford, E.
AU - Wyatt, J.
AU - Samayoa, C.
AU - Vaks, Y.
AU - Bruneau, B.
AU - Lopez, M.
AU - Moretti, A.
AU - Wilson, M.
AU - Pappas, J.
PY - 2017
SP - 362
EP - 369
DO - 10.5220/0006174603620369
PB - SciTePress