Literature DB >> 26736239

An artificial system for selecting the optimal surgical team.

Nahid Saberi, Mohsen Mahvash, Marco Zenati.   

Abstract

We introduce an intelligent system to optimize a team composition based on the team's historical outcomes and apply this system to compose a surgical team. The system relies on a record of the procedures performed in the past. The optimal team composition is the one with the lowest probability of unfavorable outcome. We use the theory of probability and the inclusion exclusion principle to model the probability of team outcome for a given composition. A probability value is assigned to each person of database and the probability of a team composition is calculated from them. The model allows to determine the probability of all possible team compositions even if there is no recoded procedure for some team compositions. From an analytical perspective, assembling an optimal team is equivalent to minimizing the overlap of team members who have a recurring tendency to be involved with procedures of unfavorable results. A conceptual example shows the accuracy of the proposed system on obtaining the optimal team.

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Year:  2015        PMID: 26736239      PMCID: PMC5069698          DOI: 10.1109/EMBC.2015.7318339

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  4 in total

1.  The Department of Veterans Affairs' NSQIP: the first national, validated, outcome-based, risk-adjusted, and peer-controlled program for the measurement and enhancement of the quality of surgical care. National VA Surgical Quality Improvement Program.

Authors:  S F Khuri; J Daley; W Henderson; K Hur; J Demakis; J B Aust; V Chong; P J Fabri; J O Gibbs; F Grover; K Hammermeister; G Irvin; G McDonald; E Passaro; L Phillips; F Scamman; J Spencer; J F Stremple
Journal:  Ann Surg       Date:  1998-10       Impact factor: 12.969

2.  Social structures in the operating theatre: how contradicting rationalities and trust affect work.

Authors:  Christofer Rydenfält; Gerd Johansson; Per Anders Larsson; Kristina Akerman; Per Odenrick
Journal:  J Adv Nurs       Date:  2011-07-20       Impact factor: 3.187

3.  Disruptions in surgical flow and their relationship to surgical errors: an exploratory investigation.

Authors:  Douglas A Wiegmann; Andrew W ElBardissi; Joseph A Dearani; Richard C Daly; Thoralf M Sundt
Journal:  Surgery       Date:  2007-11       Impact factor: 3.982

4.  Surgical team behaviors and patient outcomes.

Authors:  Karen Mazzocco; Diana B Petitti; Kenneth T Fong; Doug Bonacum; John Brookey; Suzanne Graham; Robert E Lasky; J Bryan Sexton; Eric J Thomas
Journal:  Am J Surg       Date:  2008-09-11       Impact factor: 2.565

  4 in total
  1 in total

1.  Toward Improving Surgical Outcomes by Incorporating Cognitive Load Measurement into Process-Driven Guidance.

Authors:  George S Avrunin; Lori A Clarke; Heather M Conboy; Leon J Osterweil; Roger D Dias; Steven J Yule; Julian M Goldman; Marco A Zenati
Journal:  Softw Eng Healthc Syst SEHS IEEE ACM Int Workshop       Date:  2018-05
  1 in total

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