A survey of simulation techniques in commerce and defence

Despite the developments in Modelling and Simulation (M&S) tools and techniques over the past years, there has been a gap in the M&S research and practice in healthcare on developing a toolkit to assist the modellers and simulation practitioners with selecting an appropriate set of techniques. This study is a preliminary step towards this goal. This paper presents some results from a systematic literature survey on applications of M&S in the commerce and defence domains that could inspire some improvements in the healthcare. Interim results show that in the commercial sector Discrete-Event Simulation (DES) has been the most widely used technique with System Dynamics (SD) in second place. However in the defence sector, SD has gained relatively more attention. SD has been found quite useful for qualitative and soft factors analysis. From both the surveys it becomes clear that there is a growing trend towards using hybrid M&S approaches

Successful implementation of discrete event simulation: the case of an Italian emergency department

This paper focuses on the study of a practical management problem faced by a healthcare {\it emergency department} (ED) located in the north of Italy. The objective of our study was to propose organisational changes in the selected ED, which admits approximately 7000 patients per month, aiming at improving key performance indicators related to patient satisfaction, such as the waiting time. Our study is based on a design thinking process that adopts a {\it discrete event simulation} (DES) model as the main tool for proposing changes. We used the DES model to propose and evaluate the impact of different improving scenarios. The model is based on historical data, on the observation of the current ED situation, and information obtained from the ED staff. The results obtained by the DES model have been compared with those related to the existing ED setting, and then validated by the ED managers. Based on the results we obtained, one of the tested scenarios was selected by the ED for implementation.Comment: 24 pages, 8 figures and 4 table

Patient Experience Informs Health Care Strategies in Irish Hospitals

Patients are central to health care facilities and institutions; therefore, a dire need arises to include feedback of their experience in the decision-making process. Patient experience is increasingly recognised as one of the three pillars of quality in healthcare alongside clinical effectiveness and patient safety. A comprehensive literature review (more than 2500 peer-reviewed articles) has identified five key frameworks for patient experience including: UK Picker Institute Principles and US H-CAHPS. The frameworks have enabled the identification of a potential range of patient experience dimensions and helped in grouping them into nine categories. However, there are still opportunities to address research gaps in developing a unified index to represent patient experience, and offering a practical framework to inform quality improvement strategies in hospitals. An extensive exploratory study is developed to complement the literature review. This study aims to confirm the importance of the identified nine dimensions from patients’ views, explore staff perceptions of patient experience, then compare patients’ views and staff’s perceptions. Semistructured interviews with 77 participants (26 senior staff members and 51patients) across three major acute Irish hospitals are conducted. Five important dimensions are highlighted from patients’ responses such as: staff communication and being treated with respect. While dimensions such as: continuity of care and involving family members are identified as less important. While staff in this study perceive dimensions such as quicker access to care and informing the patient with their status updates as more significant in shaping the patient experience. Both the exploratory study and literature review outcomes have contributed to the design of a patient experience questionnaire which examine dimensions that matter most to patient experience. The questionnaire is included as a component of a multi-method framework that integrated data analytics, simulation modelling, and optimisation. With an ultimate objective to improve patient experience, the proposed framework has been piloted in an Emergency Department of one of the leading and busiest university hospitals in Dublin. Fifty-eight patients responded to the questionnaire and their responses are analysed using a Partial Least Squares (PLS) model. PLS results have identified access to care as a negative predictor to patient experience. Improvement strategies such as increasing the internal capacity of the department are proposed by the management team to improve the Length of Stay (LOS) and provide better access to care. To examine and assess the impact of proposed strategies on LOS, a simulation model has complemented the solution framework. Results have showed that internal capacity of an ED has no direct impact on LOS and does not act as a performance constraint. However, other factors such as increasing downstream department’s capacity and the staffing levels can lead to a reduction in LOS (up to 25%)

Can involving clients in simulation studies help them solve their future problems? A transfer of learning experiment

It is often stated that involving the client in operational research studies increases conceptual learning about a system which can then be applied repeatedly to other, similar, systems. Our study provides a novel measurement approach for behavioural OR studies that aim to analyse the impact of modelling in long term problem solving and decision making. In particular, our approach is the first to operationalise the measurement of transfer of learning from modelling using the concepts of close and far transfer, and overconfidence. We investigate learning in discrete-event simulation (DES) projects through an experimental study. Participants were trained to manage queuing problems by varying the degree to which they were involved in building and using a DES model of a hospital emergency department. They were then asked to transfer learning to a set of analogous problems. Findings demonstrate that transfer of learning from a simulation study is difficult, but possible. However, this learning is only accessible when sufficient time is provided for clients to process the structural behaviour of the model. Overconfidence is also an issue when the clients who were involved in model building attempt to transfer their learning without the aid of a new model. Behavioural OR studies that aim to understand learning from modelling can ultimately improve our modelling interactions with clients; helping to ensure the benefits for a longer term; and enabling modelling efforts to become more sustainable

Curriculum renewal for interprofessional education in health

In this preface we comment on four matters that we think bode well for the future of interprofessional education in Australia. First, there is a growing articulation, nationally and globally, as to the importance of interprofessional education and its contribution to the development of interprofessional and collaborative health practices. These practices are increasingly recognised as central to delivering effective, efficient, safe and sustainable health services. Second, there is a rapidly growing interest and institutional engagement with interprofessional education as part of pre-registration health professional education. This has changed substantially in recent years. Whilst beyond the scope of our current studies, the need for similar developments in continuing professional development (CPD) for health professionals was a consistent topic in our stakeholder consultations. Third, we observe what might be termed a threshold effect occurring in the area of interprofessional education. Projects that address matters relating to IPE are now far more numerous, visible and discussed in terms of their aggregate outcomes. The impact of this momentum is visible across the higher education sector. Finally, we believe that effective collaboration is a critical mediating process through which the rich resources of disciplinary knowledge and capability are joined to add value to existing health service provision. We trust the conceptual and practical contributions and resources presented and discussed in this report contribute to these developments.Office of Learning and Teaching Australi

Using theoretical frameworks of behaviour to understand and improve health care delivery

PhD ThesisThe development of new knowledge about patient care continues to progress at an ever-increasing rate but its transfer into clinical practice can be slow and unpredictable. This doctoral statement provides a critical overview of a substantial programme of work that has explored the utility of theoretical models of behaviour for promoting the uptake of research findings into routine care. Guided by the MRC Framework for the design and evaluation of complex interventions, the supporting publications describe the development and testing of an innovative and systematic approach to intervention design. As well as providing methods for identifying and applying behavioural theory, this work has also set standards for transparency in the intervention development processes. The work demonstrates that psychological theories of behaviour do have an important function for improving healthcare delivery by supporting clinical behaviour change, but important limitations remain. In my critical reflection of this body of work I discuss these challenges, considering in particular the omission of the patient perspective and the dynamic influence of the patient-professional interaction during the clinical encounter. I go on to propose an extended dual-perspective model supported by theory and evidence from other improvement literatures, epistemologies and disciplinary perspectives. The dual perspective model functions at the very core of healthcare delivery and illustrates the interdependency of professional and patient behaviour in determining healthcare decision making and patient outcomes. By formally including the patient perspective the revised model encompasses all three dimensions of the EBM paradigm. I argue for a focus on better understanding of the interactional and relational processes that are generated during the clinical encounter as an essential step forward for implementation and improvement science. The paradigm of patient-centred care is then revisited through the lens of capabilities thinking and is proposed as a vital mechanism for supporting the uptake of appropriate, evidence-based healthcare

Phase-Type Survival Trees to Model a Delayed Discharge and Its Effect in a Stroke Care Unit

The problem of hospital patients’ delayed discharge or ‘bed blocking’ has long been a challenge for healthcare managers and policymakers. It negatively affects the hospital performance metrics and has other severe consequences for the healthcare system, such as affecting patients’ health. In our previous work, we proposed the phase-type survival tree (PHTST)-based analysis to cluster patients into clinically meaningful patient groups and an extension of this approach to examine the relationship between the length of stay in hospitals and the destination on discharge. This paper describes how PHTST-based clustering can be used for modelling delayed discharge and its effects in a stroke care unit, especially the extra beds required, additional cost, and bed blocking. The PHTST length of stay distribution of each group of patients (each PHTST node) is modelled separately as a finite state continuous-time Markov chain using Coxian-phase-type distributions. Delayed discharge patients waiting for discharge are modelled as the Markov chain, called the ‘blocking state’ in a special state. We can use the model to recognise the association between demographic factors and discharge delays and their effects and identify groups of patients who require attention to resolve the most common delays and prevent them from happening again. The approach is illustrated using five years of retrospective data of patients admitted to the Belfast City Hospital with a stroke diagnosis

A Hybrid Modelling Framework for Real-time Decision-support for Urgent and Emergency Healthcare

In healthcare, opportunities to use real-time data to support quick and effective decision-making are expanding rapidly, as data increases in volume, velocity and variety. In parallel, the need for short-term decision-support to improve system resilience is increasingly relevant, with the recent COVID-19 crisis underlining the pressure that our healthcare services are under to deliver safe, effective, quality care in the face of rapidly-shifting parameters. A real-time hybrid model (HM) which combines real-time data, predictions, and simulation, has the potential to support short-term decision-making in healthcare. Considering decision-making as a consequence of situation awareness focuses the HM on what information is needed where, when, how, and by whom with a view toward sustained implementation. However the articulation between real-time decision-support tools and a sociotechnical approach to their development and implementation is currently lacking in the literature. Having identified the need for a conceptual framework to support the development of real-time HMs for short-term decision-support, this research proposed and tested the Integrated Hybrid Analytics Framework (IHAF) through an examination of the stages of a Design Science methodology and insights from the literature examining decision-making in dynamic, sociotechnical systems, data analytics, and simulation. Informed by IHAF, a HM was developed using real-time Emergency Department data, time-series forecasting, and discrete-event simulation. The application started with patient questionnaires to support problem definition and to act as a formative evaluation, and was subsequently evaluated using staff interviews. Evaluation of the application found multiple examples where the objectives of people or sub-systems are not aligned, resulting in inefficiencies and other quality problems, which are characteristic of complex adaptive sociotechnical systems. Synthesis of the literature, the formative evaluation, and the final evaluation found significant themes which can act as antecedents or evaluation criteria for future real-time HM studies in sociotechnical systems, in particular in healthcare. The generic utility of IHAF is emphasised for supporting future applications in similar domains