Literature DB >> 25739791

Outcome quality assessment by surgical process compliance measures in laparoscopic surgery.

Sandra Schumann1, Ulf Bühligen2, Thomas Neumuth3.   

Abstract

OBJECTIVE: The effective and efficient assessment, management, and evolution of surgical processes are intrinsic to excellent patient care. Hence, in addition to economic interests, the quality of the outcome is of great importance. Process benchmarking examines the compliance of an intraoperative surgical process to another process that is considered as best practice. The objective of this work is to assess the relationship between the course and the outcome of surgical processes of the study.
MATERIALS AND METHODS: By assessing 450 skill practices on rapid prototyping models in minimally invasive surgery training, we extracted descriptions of surgical processes and examined the hypothesis that a significant relationship exists between the course of a surgical process and the quality of its outcome.
RESULTS: The results showed a significant correlation with Person correlation coefficients >0.05 between the quality of process outcome and process compliance for simple and complex suturing tasks in the study.
CONCLUSIONS: We conclude that high process compliance supports good quality outcomes and, therefore, excellent patient care. We also showed that a deviation from best training processes led to a decreased outcome quality. This is relevant for identifying requirements for surgical processes, for generating feedback for the surgeon with regard to human factors and for inducing changes in the workflow in order to improve the outcome quality.
Copyright © 2014 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Best practice; Computer-assisted surgery [E02.950.875]; Distance measures; Process benchmarking; Process compliance; Quality of outcome; Surgical process model; Workflow [L01.906.893]

Mesh:

Year:  2015        PMID: 25739791     DOI: 10.1016/j.artmed.2014.10.008

Source DB:  PubMed          Journal:  Artif Intell Med        ISSN: 0933-3657            Impact factor:   5.326


  5 in total

1.  Surgical skills: Can learning curves be computed from recordings of surgical activities?

Authors:  Germain Forestier; Laurent Riffaud; François Petitjean; Pierre-Louis Henaux; Pierre Jannin
Journal:  Int J Comput Assist Radiol Surg       Date:  2018-03-03       Impact factor: 2.924

2.  Surgical data science: The new knowledge domain.

Authors:  S Swaroop Vedula; Gregory D Hager
Journal:  Innov Surg Sci       Date:  2017-04-20

Review 3.  Surgical process modeling.

Authors:  Thomas Neumuth
Journal:  Innov Surg Sci       Date:  2017-05-20

4.  Convolutional-de-convolutional neural networks for recognition of surgical workflow.

Authors:  Yu-Wen Chen; Ju Zhang; Peng Wang; Zheng-Yu Hu; Kun-Hua Zhong
Journal:  Front Comput Neurosci       Date:  2022-09-07       Impact factor: 3.387

5.  Generic surgical process model for minimally invasive liver treatment methods.

Authors:  Maryam Gholinejad; Egidius Pelanis; Davit Aghayan; Åsmund Avdem Fretland; Bjørn Edwin; Turkan Terkivatan; Ole Jakob Elle; Arjo J Loeve; Jenny Dankelman
Journal:  Sci Rep       Date:  2022-10-06       Impact factor: 4.996

  5 in total

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