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Promoting continuity of care in nurse-patient assignment: A multiple objective heuristic algorithm
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2023 | Decision Support Systems | Citations: 0
Authors: Jiang, Haoqiang; Gomes, Paulo; Meer, Debra Vander

Abstract: Continuity of care is a critical element for delivering quality of care in inpat ... Expand

Abstract: Continuity of care is a critical element for delivering quality of care in inpatient units, however it has rarely been considered in nurse-patient assignment (NPA) models. The nursing literature suggests that continuity of care helps reduce medical errors and readmissions and increases patient satisfaction. Balancing patient assignments to nursing staff is also critical to avoid overwork and burnout. This study investigates the relationship between continuity of care and workload balance in NPA decisions in hospital inpatient units. We develop an NPA heuristic to guide continuity-care assignment while addressing the trade-off with workload balance. The heuristic prioritizes higher-acuity patients to the objective of continuity of care, while assignment of lower acuity patients seeks to minimize workload imbalance. A discrete event simulation model of an inpatient hospital unit is used to evaluate how the heuristic addresses the tradeoff between the two objectives under distinct work design sce narios. The heuristic enables significant increases in continuity of care for specific patient segments while limiting the impact on workload balance. We discuss implications for theory and managerial practice. Collapse

Semantic filters: discrete event simulation

Topics: accounting legal context decision support system personality decision support

Methods: simulation computational algorithm sensitivity analysis mixed-integer programming experiment
Managing hospital visitor admission during Covid-19: A discrete-event simulation by the data of a German University Hospital
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2022 | HICSS | Citations: 0
Authors: Bartenschlager, Christina; Frey, Ramona; Freitag, Marie; Classen, Johanna-Maria; Messmann, Helmut; Brunner, Jens O.; Temizel, Selin; Römmele, Christoph

Abstract: The Corona pandemic and the associated need for visitor restrictions have define ... Expand

Abstract: The Corona pandemic and the associated need for visitor restrictions have defined an entirely new management task in hospitals: The hospital visitor management. The admission process of hospital visitors and the implementation of associated infection-prevention strategies such as the delivery of face masks thereby pose major challenges. In this work, we evaluate both implemented and planned admission processes in a German University Hospital based on a discrete-event simulation model and provide distinct recommendations for hospital visitor management with special consideration of digitalization, antigen testing, waiting times, space and staff utilization. We find the extraordinary potential of digitalization with a reduction of visitor waiting and service times of up to 90 percent, the significant burden for personnel and room capacity, in terms of antigen testing, especially, and the need for visitor restrictions in terms of a maximum number of visitors per inpatient. Collapse

Semantic filters: discrete event simulation

Topics: decision making pandemic

Methods: simulation discrete event simulation qualitative interview
Deep Reinforcement Learning Techniques For Solving Hybrid Flow Shop Scheduling Problems: Proximal Policy Optimization (PPO) and Asynchronous Advantage Actor-Critic (A3C)
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2022 | HICSS | Citations: 0
Authors: Nahhas, Abdulrahman; Kharitonov, Andrey; Turowski, Klaus

Abstract: Well-studied scheduling practices are fundamental for the successful support of ... Expand

Abstract: Well-studied scheduling practices are fundamental for the successful support of core business processes in any manufacturing environment. Particularly, the Hybrid Flow Shop (HFS) scheduling problems are present in many manufacturing environments. The current advances in the field of Deep Reinforcement Learning (DRL) attracted the attention of both practitioners and academics to investigate their adoption beyond synthetic game-like applications. Therefore, we present an approach that is based on DRL techniques in conjunction with a discrete event simulation model to solve a real-world four-stage HFS scheduling problem. The main narrative behind the presented concepts is to expose a DRL agent to a gamelike environment using an indirect encoding. Two types of DRL techniques namely, Proximal Policy Optimization (PPO) and Asynchronous Advantage Actor-Critic (A3C), are evaluated for solving problems of different complexity. The computational results suggest that the DRL agents successfully learn appropriate policies for solving the investigated problem. In addition, the investigation shows that the agent can adjust their policies when we expose them to a different problem. We further evaluate the approach to solving problem instances published in the literature to establish a comparison. Collapse

Semantic filters: discrete event simulation

Topics: manufacturing information system Google+

Methods: computational algorithm experiment simulation discrete event simulation literature study
Leveraging Electronic Health Records to improve Patient Appointment Scheduling: A design-oriented Approach

2022 | International Conference on Information Systems | Citations: 0
Authors: Rottmann, Janine; Stein, Nikolai

Abstract: As demand for healthcare services continues to increase, hospitals are under co ... Expand

Abstract: As demand for healthcare services continues to increase, hospitals are under constant economic pressure to better manage patient appointments. It is common practice in clinical routine to schedule appointments based on average service times, resulting in overtime and waiting times for clinicians and patients. To address this problem, we propose a data-driven decision support system for scheduling patient appointments that accounts for variable service times. We take advantage of the growing amount of patient-and treatment-specific data collected in hospitals. Using a simulation study, we evaluate the decision support system on the practical example of a Gastroenterology facility. Our results demonstrate improved appointment scheduling efficiency compared to the approach currently in use. Data-driven Patient Appointment Schedulingin clinical practice, appointments are scheduled one at a time, with average service times. This approach could be justified in practice if delays caused by excessively long appointments were compensated at the end of the day by appointments ending earlier. However, a recent study by Mandelbaum et al. (2020) refuted this assumption and showed that accounting for service time variability in the AS process leads to a significant reduction in overtime and waiting times. This finding motivates us to further investigate how accounting for service time variability affects AS efficiency.Previous literature has presented various approaches to address different imponderables in the AS process. Among other complicating factors such as patient and provider preferences, punctuality, cancellations, and no-shows, stochastic service times pose a major challenge for patient AS (Gupta and Denton, 2008). This also applies to the collaborating Gastroenterology facility, which is why we focus on uncertain service times in this article. Previous studies have frequently addressed service time variability in patient AS, and despite the difficulty of this endeavor, progress has been made in addressing this problem. It has been repeatedly demonstrated that individual service times can be estimated based on a priori information regarding patient-and treatment-specific data (Gañan-Cardenas, Jiménez, et al., 2022; Jiao et al., 2020; Podboy and Scheinker, 2020. Furthermore, several studies have found that a more accurate estimate of service times has a positive impact on AS efficiency (Bentayeb et al., 2019; Safdar et al., 2021; Srinivas and Salah, 2021. However, in previous studies, this has only been demonstrated for rule-based AS strategies, where the residual global uncertainty in service time estimates was not accounted for in the model. We address this research gap by developing a decision support system that accounts for global uncertainty in individual service time estimates. To structure our work and emphasize its focus, we address the following research questions:RQ1 What are the design elements of a data-driven decision support system for patient AS? RQ2 How does the proposed decision support system compare to AS approaches currently in use?Addressing these questions, the following section provides an overview of the current state of research in patient AS. After introducing the design-oriented research methodology, we describe the individual design elements of the decision support system. Subsequently, we evaluate each individual module of the decision support system in a discrete event simulation that replicates the processes at the collaborating Gastroenterology facility. We conclude our study with a summary of our findings and an outlook for further research. Collapse

Semantic filters: discrete event simulation

Topics: decision support system electronic health record shapley additive explanation artificial intelligence accounting

Methods: design artifact simulation design science discrete event simulation machine learning
Simulation-Based Electronic Health Record Usability Evaluation: A Proof of Concept

2022 | International Conference on Information Systems | Citations: 0
Authors: Srivastava, Ankita; Delen, Dursun

Abstract: Poor usability of Electronic Health Records (EHR) solutions is directly associa ... Expand

Abstract: Poor usability of Electronic Health Records (EHR) solutions is directly associated with physician burnout. While the survey and observational methods have been utilized widely in the usability evaluation of EHRs, it does not seem to be helping with the continuous improvement of EHR design and user satisfaction. We address this gap by presenting a discrete event simulation-based model that can add objectivity to the extant EHR usability methods. Evaluating EHR usability from the perspective of operations and workflow can help vendors design and develop better systems. This short paper presents a proof-of-concept simulation model with assumed task-time distributions. Our main research question is how we can use simulation techniques to objectively evaluate EHR usability? The simulation model results in terms of resource (clinician) utilization metrics can serve as a proxy to evaluate the efficiency component of the EHR usability at the departmental level. Collapse

Semantic filters: discrete event simulation

Topics: usability

Methods: simulation design artifact usability testing discrete event simulation qualitative interview
Language and User Requirements for Business Process Simulation – A Systematic Literature Review

2022 | Americas Conference on Information Systems | Citations: 0
Authors: Weber, Niklas; Rosenthal, Kristina

Abstract: Simulating a business process aims at analyzing the process's dynamic behavior ... Expand

Abstract: Simulating a business process aims at analyzing the process's dynamic behavior without having to execute the process. In research and practice of Business Process Management, simulating business processes has been a continuing focus since the 1990s -widely acknowledged as essential technique for quantitative process analysis. Despite its relevance, a differentiated understanding of requirements towards process modeling languages for creating simulation models and user requirements for simulation approaches and tools is missing at present. Based on a systematic and purposeful sampling of prior work combining different search strategies, the present study compiles and synthesizes 113 prior research contributions on business process simulation. Categorizing 56 language and user requirements results in an organizing overview that informs future design research on simulation approaches and tools that benefit (prospective) users of BPS. Collapse

Semantic filters: discrete event simulation

Topics: database system user requirement business process management knowledge base

Methods: simulation literature study business process modeling language modeling language agent based simulation
Multi-agent optimization of the intermodal terminal main parameters by using AnyLogic simulation platform: Case study on the Ningbo-Zhoushan Port
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2021 | International Journal of Information Management | Citations: 0
Authors: Muravev, Dmitri; Hu, Hao; Rakhmangulov, Aleksandr; Mishkurov, Pavel

Abstract: Due to numerous uncertainties such as bad weather conditions, frequent changes i ... Expand

Abstract: Due to numerous uncertainties such as bad weather conditions, frequent changes in the schedules of vessels, breakdowns of equipment, port managers are aiming at providing adaptive and flexible strategic planning of their facilities, especially intermodal terminals. In this research, we investigate a two-stage optimization of intermodal terminals main parameters via using AnyLogic simulation platform. We have developed a set of hybrid simulation models to optimize the main parameters of intermodal terminals which are also called dry ports. To make an express evaluation of the preliminary implementation of dry ports, we have developed an agent-based system dynamics simulation model to achieve the stable state of the main parameters of intermodal terminals. To clarify the obtained averaged benefits of the main dry ports parameters while the port managers make key decisions on the investments into implementation of intermodal terminals, we have developed an agent-based discrete-event simulation model of a seaport – a dry port system. We show that the combination of the agent-based modeling with other simulation approaches simplifies the process of designing simulation models and increases their visibility. The developed set of models allows us to compute the balanced values of the parameters, while an effective operation of a seaport – intermodal terminal system is achieved. On the basis of the provided case study on one of the busiest ports in China, we prove the adequacy and validity of the developed simulation models. Due to the lack of systematic approach to optimization of the main parameters of intermodal terminals in logistic industry, our findings set herein could improve the decision-making process related to the selection of strategic facility planning in the field of intermodal terminals. Collapse

Semantic filters: discrete event simulation

Topics: logistics management systems operations conversational agent operational management online learning system

Methods: simulation system dynamics case study discrete event simulation experiment
Business Process Simulation on Procedural Graphical Process Models
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2021 | Business & Information Systems Engineering | Citations: 0
Authors: Rosenthal, Kristina; Ternes, Benjamin; Strecker, Stefan

Abstract: Business process simulation marks an essential technique for analyzing business ... Expand

Abstract: Business process simulation marks an essential technique for analyzing business processes and for reasoning about process improvement. With first contributions dating back to the mid-1990s, computerized business process simulation has been a continuing research focus and is widely acknowledged as foundational to Business Process Management research and practice. Reviewing contributions to the field published between 1990 and 2018, the authors assess the state of research on business process simulation and develop an organizing overview of research contributions discussing simulation approaches, tool support, results visualization, use context, application purposes, and adoption barriers. Findings inform future research on business process simulation by discussing paths for behavioral research on the use of business process simulation, user requirements, and adoption barriers as well as complementary paths for design science research addressing limitations of present approaches and simulation tool support. Collapse

Semantic filters: discrete event simulation

Topics: business process management system support database system business process management system user requirement

Methods: simulation modeling language business process modeling design science business process model and notation
Creating Competitive Advantage in E-Business Value Chains by Using Excess Capacity via IT-enabled Marketplaces
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2020 | ACM SIGMIS Database | Citations: 0
Authors: Häckel, Björn; Übelhör, Jochen; Voit, Christian

Abstract: Innovations through the "business process as a service" (BPaaS) concept have sha ... Expand

Abstract: Innovations through the "business process as a service" (BPaaS) concept have shaped new business opportunities for service providers. Technological progress allows business process service providers (BPSPs) to offer a wide range of digitized and standardized services to business clients. Within this business model, capacity planning is a major challenge for BPSPs, as costs are the decisive factor in the competitive business environment of digital service provision. Accordingly, BPSPs must tackle inefficiencies in capacity planning resulting from both idle capacity and lost revenue caused by volatile demand. However, recent technological developments offering dynamic integration and information capabilities may help, as they enable the exchange of excess capacity between business partners. We examine the corresponding potential of IT-enabled excess capacity markets to create competitive advantage in e-business value chains by analyzing a BPSP's capacity-related optimization problem. We build an analytical model based on queuing theory and evaluate it through a discreteevent simulation applying a possible application scenario. By solving the optimization problem, we identified a remarkable cost advantage in using excess capacity as a first competitive advantage. Building on this cost advantage, we furthermore identified differentiation advantages realizable without raising prices. Both findings highlight the relevance of further research on this topic. Collapse

Semantic filters: discrete event simulation

Topics: competitive advantage authorization business process management service quality electronic business

Methods: simulation optimization model experiment discrete event simulation design science
Evolving Neural Networks to Solve a Two-Stage Hybrid Flow Shop Scheduling Problem with Family Setup Times

2020 | HICSS | Citations: 0
Authors: Lang, Sebastian; Behrendt, Fabian; Reggelin, Tobias; Nahhas, Abdulrahman

Abstract: We present a novel strategy to solve a two-stage hybrid flow shop scheduling pro ... Expand

Abstract: We present a novel strategy to solve a two-stage hybrid flow shop scheduling problem with family setup times. The problem is derived from an industrial case. Our strategy involves the application of NeuroEvolution of Augmenting Topologies - a genetic algorithm, which generates arbitrary neural networks being able to estimate job sequences. The algorithm is coupled with a discrete-event simulation model, which evaluates different network configurations and provides training signals. We compare the performance and computational efficiency of the proposed concept with other solution approaches. Our investigations indicate that NeuroEvolution of Augmenting Topologies can possibly compete with state-of-the-art approaches in terms of solution quality and outperform them in terms of computational efficiency. Collapse

Semantic filters: discrete event simulation

Topics: website open source logistics management manufacturing information system information system use

Methods: artificial neural network experiment machine learning simulation computational algorithm

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Found 79 articles

Promoting continuity of care in nurse-patient assignment: A multiple objective heuristic algorithm

Managing hospital visitor admission during Covid-19: A discrete-event simulation by the data of a German University Hospital

Deep Reinforcement Learning Techniques For Solving Hybrid Flow Shop Scheduling Problems: Proximal Policy Optimization (PPO) and Asynchronous Advantage Actor-Critic (A3C)

Leveraging Electronic Health Records to improve Patient Appointment Scheduling: A design-oriented Approach

Simulation-Based Electronic Health Record Usability Evaluation: A Proof of Concept

Language and User Requirements for Business Process Simulation – A Systematic Literature Review

Multi-agent optimization of the intermodal terminal main parameters by using AnyLogic simulation platform: Case study on the Ningbo-Zhoushan Port

Business Process Simulation on Procedural Graphical Process Models

Creating Competitive Advantage in E-Business Value Chains by Using Excess Capacity via IT-enabled Marketplaces

Evolving Neural Networks to Solve a Two-Stage Hybrid Flow Shop Scheduling Problem with Family Setup Times