Phone: +44 (0)161 306 3429 [Blue text indicates changes]EJOR RR3 Paper 4.16.docx 2 AbstractThe literature suggests that increasing stakeholder engagement has a positive impact on projects using discrete-event simulation in healthcare. This suggests projects should strive to involve the stakeholders in as much of the project as possible, through facilitated workshops. A notable gap in stakeholder involvement is the model coding stage, in which a conceptual model is turned into a discrete-event simulation model running on a computer. This paper investigates how and under what circumstances model coding might also be conducted in facilitated workshops, in particular through the use of the Business Process Model and Notation (BPMN) modelling standard. This work arose from a series of modelling projects with two hospitals, one in Italy and the other in the UK.The paper describes how BPMN can contribute, with a case in which model coding was achieved in a facilitated workshop and a second in which it was not but which highlights further barriers to this in some contexts. These barriers arise from the detail necessary for requisite modelling regarding i) the level of complexity of the model and ii) challenges in data access and analysis to populate the model. The relationship between the technical capabilities of tools available and the impact of these barriers is also discussed.We believe this is the first time that discrete-event simulation model coding in a facilitated workshop in healthcare has been described, and we provide a clear view of the further barriers.To indicate when facilitated model coding is currently achievable, we suggest a contextual matrix.

Stakeholder engagement in simulation projects is important, especially in healthcare where there is a plurality of stakeholder opinions, objectives and power. One promising approach for increasing engagement is facilitated modelling. Currently, the complexity of producing a simulation model means that the 'model coding' stage is performed without the involvement of stakeholders, interrupting the possibility of a fully-facilitated project. Early work demonstrated that with currently-available software tools we can represent a simple healthcare process using Business Process Model and Notation (BPMN) and generate a simulation model automatically. However, for more complex processes, BPMN currently has a number of limitations, namely the ability to represent queues and data-driven decision points. To address these limitations, we propose a conceptual design for an extension to BPMN (BPMN4SIM) using Model Driven Architecture. Application to an elderly emergency care pathway in a UK hospital shows that BPMN4SIM is able to represent a more-complex business process.

Purpose – The purpose of this paper is to provide a method for analysing and improving the operational performance of business processes (BPs). Design/methodology/approach – The method employs two standards, Business Process Modelling Notation (BPMN 2.0) and Business Processes Simulation (BPSim 1.0), to measure key performance indicators (KPIs) of BPs and test for potential improvements. The BP is first modelled in BPMN 2.0. Operational performance can then be measured using BPSim 1.0. The process simulation also enables execution of reliable “what-if” analysis, allowing improvements of the actual processes under study. To confirm the validity of the method the authors provide an application to the healthcare domain, in which the authors conduct several simulation experiments. The case study examines a standardised patient arrival and treatment process in an orthopaedic-emergency room of a public hospital. Findings – The method permits detection of process criticalities, as well as identifying the best corrective actions by means of the “what-if” analysis. The paper discusses both management and research implications of the method. Originality/value – The study responds to current calls for holistic and sustainable approaches to business process management (BPM). It provides step-by-step process modelling and simulation that serve as a “virtual laboratory” to test potential improvements and verify their impact on operational performance, without the risk of error that would be involved in ex-novo simulation programming.