Literature DB >> 24962645

Improved workflow modelling using role activity diagram-based modelling with application to a radiology service case study.

Nagesh Shukla1, John E Keast2, Darek Ceglarek3.   

Abstract

The modelling of complex workflows is an important problem-solving technique within healthcare settings. However, currently most of the workflow models use a simplified flow chart of patient flow obtained using on-site observations, group-based debates and brainstorming sessions, together with historic patient data. This paper presents a systematic and semi-automatic methodology for knowledge acquisition with detailed process representation using sequential interviews of people in the key roles involved in the service delivery process. The proposed methodology allows the modelling of roles, interactions, actions, and decisions involved in the service delivery process. This approach is based on protocol generation and analysis techniques such as: (i) initial protocol generation based on qualitative interviews of radiology staff, (ii) extraction of key features of the service delivery process, (iii) discovering the relationships among the key features extracted, and, (iv) a graphical representation of the final structured model of the service delivery process. The methodology is demonstrated through a case study of a magnetic resonance (MR) scanning service-delivery process in the radiology department of a large hospital. A set of guidelines is also presented in this paper to visually analyze the resulting process model for identifying process vulnerabilities. A comparative analysis of different workflow models is also conducted.
Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Healthcare process modelling; Radiology; Workflow

Mesh:

Year:  2014        PMID: 24962645     DOI: 10.1016/j.cmpb.2014.05.005

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  2 in total

1.  Modelling Granular Process Flow Information to Reduce Bottlenecks in the Emergency Department.

Authors:  Marian Amissah; Sudakshina Lahiri
Journal:  Healthcare (Basel)       Date:  2022-05-19

2.  Lean Management Improves the Process Efficiency of Controlled Ovarian Stimulation Monitoring in IVF Treatment.

Authors:  R Muharam; F Firman
Journal:  J Healthc Eng       Date:  2022-03-16       Impact factor: 2.682

  2 in total

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