Application of Digital Twin and Heuristic Computer Reasoning to Workflow Management: Gastroenterology Outpatient Centers Study

Author:

Garbey Marc,Joerger Guillaume,Furr Shannon

Abstract

AbstractThe workflow in a large medical procedural suite is characterized by high variability of input and suboptimum throughput. Today, Electronic Health Record systems do not address the problem of workflow efficiency: there is still high frustration from medical staff who lack real-time awareness and need to act in response of events based on their personal experiences rather than anticipating. In a medical procedural suite, there are many nonlinear coupling mechanisms between individual tasks that could wrong and therefore is difficult for any individual to control the workflow in real-time or optimize it in the long run. We propose a system approach by creating a digital twin of the procedural suite that assimilates Electronic Health Record data and supports the process of making rational, data-driven, decisions to optimize the workflow on a continuous basis. In this paper, we focus on long term improvements of gastroenterology outpatient centers as a prototype example and use six months of data acquisition in two different clinical sites to validate the artificial intelligence algorithms.

Publisher

Cold Spring Harbor Laboratory

Reference44 articles.

1. Patient Safety and Quality, An Evidence-Based Handbook for Nurses, Editor: Ronda G Hughes, PhD, MHS, RN . Rockville (MD): Agency for Healthcare Research and Quality (US); 2008 Apr. Publication No.: 08-0043

2. The association of workflow interruptions and hospital doctors' workload: a prospective observational study

3. An intelligent decision support system for the operating theater: a case study;IEEE Transactions on Automation Science and Engineering,2014

4. Using lean manufacturing and machine learning for improving medicines procurement and dispatching in a hospital, 29th International Conference on Flexible Automation and Intelligent Manufacturing, ScienceDirect;Procedia Manufacturing,2019

5. Improving healthcare operations management with machine learning;Nat Mach Intell,2020

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