کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
377712 658817 2015 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Outcome quality assessment by surgical process compliance measures in laparoscopic surgery
ترجمه فارسی عنوان
ارزیابی کیفیت نتیجه توسط اقدامات جراحی در عمل جراحی لاپاروسکوپی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی


• We assess the relation of processes and outcome quality for surgical processes.
• The assessment is performed on 450 training tasks in laparoscopic surgery.
• There is a strong correlation between best practice processes and training outcome.

ObjectiveThe 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 methodsBy 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.ResultsThe 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.ConclusionsWe 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.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Artificial Intelligence in Medicine - Volume 63, Issue 2, February 2015, Pages 85–90
نویسندگان
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