IISE Transactions on Healthcare Systems Engineering最新文献_第10页

Simulation-optimization of automated material handling systems in a healthcare facility 医疗机构中自动化物料处理系统的仿真优化

IISE Transactions on Healthcare Systems Engineering Pub Date : 2020-06-17 DOI: 10.1080/24725579.2021.1882622

Amogh Bhosekar, T. Işik, S. Eksioglu, Kade Gilstrap, R. Allen

{"title":"Simulation-optimization of automated material handling systems in a healthcare facility","authors":"Amogh Bhosekar, T. Işik, S. Eksioglu, Kade Gilstrap, R. Allen","doi":"10.1080/24725579.2021.1882622","DOIUrl":"https://doi.org/10.1080/24725579.2021.1882622","url":null,"abstract":"Abstract Automated material handling systems are used in healthcare facilities to optimize material flow, minimize workforce requirements, reduce risk of contamination, and reduce work injuries. This paper develops a case study using data from Greenville Memorial Hospital (GMH) in South Carolina, USA. The case study is focused on the delivery of surgical case carts to operating rooms at GMH via Automated Guided Vehicles (AGVs). This study proposes a framework that integrates data analysis with system simulation and optimization. The study addresses the following research questions: (1) Redesign of the pathways: Do performance measures, such as travel time and task completion time, improve after a redesign of AGV pathways? (2) Operational fleet sizing: Do performance measures, such as travel time and task completion time, improve when the number of AGVs used daily is controlled by the volume of surgical cases? If this is true, then how many AGVs should be used daily? To address research question (1), we compare two AGV pathway designs via an extensive sensitivity analysis. To address research question (2), we use a simulation-optimization model to evaluate the performance of the system for different fleet sizes. Finally, we conduct a pilot study at GMH to validate the results of our analysis. This study indicates that the proposed solution, which uses a smaller fleet of AGVs than currently used at GMH, leads to significant reductions in congestion and travel times, and increased utilization of AGVs.","PeriodicalId":37744,"journal":{"name":"IISE Transactions on Healthcare Systems Engineering","volume":"11 1","pages":"316 - 337"},"PeriodicalIF":0.0,"publicationDate":"2020-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24725579.2021.1882622","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41601583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Robust logistic regression tree for subgroup identification in healthcare outcome modeling 医疗结果建模中用于亚组识别的稳健逻辑回归树

IISE Transactions on Healthcare Systems Engineering Pub Date : 2020-05-07 DOI: 10.1080/24725579.2020.1759161

Doowon Choi, L. Zeng

引用次数: 2

Staffing decisions in a tele-ICU: dedicated versus flexible resources 远程icu的人员配置决策:专用资源vs灵活资源

IISE Transactions on Healthcare Systems Engineering Pub Date : 2020-04-15 DOI: 10.1080/24725579.2020.1749911

Xuanjing Li, Dacheng Liu, Muer Yang, M. Fry, Xiaolei Xie

{"title":"Staffing decisions in a tele-ICU: dedicated versus flexible resources","authors":"Xuanjing Li, Dacheng Liu, Muer Yang, M. Fry, Xiaolei Xie","doi":"10.1080/24725579.2020.1749911","DOIUrl":"https://doi.org/10.1080/24725579.2020.1749911","url":null,"abstract":"Abstract In a tele-ICU center with flexible staff scheduling, interruptions to tasks with lower priority are common, often prolonging the processing time of these tasks. Dedicated staff scheduling, however, can reduce such interruptions. While dedicated staff scheduling is generally perceived to be less efficient than flexible systems according to traditional queueing theory, the reductions in interruptions call this result into question. To investigate when dedicated staff scheduling could be more efficient than flexible systems for tele-ICUs, we build a discrete-event simulation model to analyze the operational process of admissions and interventions at a real tele-ICU center. Our simulation results show that if the dedicated nurse (intensivist) can process admissions at least 31% (26%) faster than the flexible nurse (intensivist), the dedicated staff scheduling will be preferred. Thus, the tele-ICU administrators should choose the scheduling approach (flexible versus dedicated) based on how often interruptions are likely to occur and their anticipated effect on prolonging the medical staff’s processing times of the interrupted tasks. Our simulation model can also help tele-ICU administrators determine a suitable staffing level by providing the estimated waiting times of admissions and interventions under varying staffing levels.","PeriodicalId":37744,"journal":{"name":"IISE Transactions on Healthcare Systems Engineering","volume":"10 1","pages":"172 - 183"},"PeriodicalIF":0.0,"publicationDate":"2020-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24725579.2020.1749911","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45562943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Network modeling and Internet of things for smart and connected health systems—a case study for smart heart health monitoring and management 智能和互联健康系统的网络建模和物联网——智能心脏健康监测和管理的案例研究

IISE Transactions on Healthcare Systems Engineering Pub Date : 2020-04-06 DOI: 10.1080/24725579.2020.1741738

Hui Yang, Chen Kan, Alexander Krall, D. Finke

{"title":"Network modeling and Internet of things for smart and connected health systems—a case study for smart heart health monitoring and management","authors":"Hui Yang, Chen Kan, Alexander Krall, D. Finke","doi":"10.1080/24725579.2020.1741738","DOIUrl":"https://doi.org/10.1080/24725579.2020.1741738","url":null,"abstract":"Abstract Heart disease is a leading cause of death in the US. Recent advances in the Internet of Things (IoT) provide a great opportunity to realize smart and connected health systems through IoT monitoring and sensor-based data analytics of cardiac disorders. However, big data arising from the large-scale IoT system pose a significant challenge for efficient and effective sensory information processing and decision making. Very little has been done to glean pertinent information about the disease-altered cardiac activity in the context of large-scale IoT network. In this study, we propose a parallel computing framework for multi-level network modeling and monitoring of cardiac dynamics to realize the potential of IoT-enabled smart health management. Specifically, dissimilarities among cardiac signals are firstly characterized among heartbeats for an individual patient, as well as among representative heartbeats for different patients. Then, a stochastic learning approach is developed to optimize the embedding of cardiac signals into a beat-to-beat network model, as well as a patient-to-patient network model. Further, we develop a parallel computing algorithm to improve the computational efficiency. Finally, a statistical process monitoring scheme is designed to harness network features for real-time monitoring and anomaly detection of cardiac activities. Experimental results show the proposed methodology has strong potential to realize a smart and interconnected system for cardiac health management in the context of large-scale IoT network.","PeriodicalId":37744,"journal":{"name":"IISE Transactions on Healthcare Systems Engineering","volume":"10 1","pages":"159 - 171"},"PeriodicalIF":0.0,"publicationDate":"2020-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24725579.2020.1741738","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48360551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 16

Hybrid ordering policies for platelet inventory management under demand uncertainty 需求不确定条件下血小板库存管理的混合订货策略

IISE Transactions on Healthcare Systems Engineering Pub Date : 2020-04-02 DOI: 10.1080/24725579.2019.1686718

S. Rajendran, S. Srinivas

{"title":"Hybrid ordering policies for platelet inventory management under demand uncertainty","authors":"S. Rajendran, S. Srinivas","doi":"10.1080/24725579.2019.1686718","DOIUrl":"https://doi.org/10.1080/24725579.2019.1686718","url":null,"abstract":"Abstract Hospitals are imposed with the challenge of developing efficient blood inventory management tools due to its limited supply and uncertain demand. Besides, the short shelf-life of blood further complicates the task of its inventory administration. Since lifesaving blood is required as frequent as once in two seconds and blood donations are falling short of patient needs, hospitals maintain a high inventory level that leads to excess blood (especially platelet) wastage. In this study, we propose two new variants of review policies for platelet inventory management at hospitals, namely, and which aim to achieve a trade-off solution between shortage and wastage. The proposed hybrid policies are compared against two well-performing ordering policies in the literature, for real-life hospital settings by considering unique characteristics such as weekday/weekend demand fluctuation and varying shelf-life of platelet units received. Experimental results and statistical analysis show a significant improvement in the performance measures using the proposed policies. The models can serve as a decision support system by assisting healthcare practitioners in determining the best order quantities, given the hospital characteristics.","PeriodicalId":37744,"journal":{"name":"IISE Transactions on Healthcare Systems Engineering","volume":"10 1","pages":"113 - 126"},"PeriodicalIF":0.0,"publicationDate":"2020-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24725579.2019.1686718","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43861358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 23

Secure decentralized decisions to enhance coordination in consolidated hospital systems 确保权力下放决策，以加强合并医院系统的协调

IISE Transactions on Healthcare Systems Engineering Pub Date : 2020-04-02 DOI: 10.1080/24725579.2019.1680582

Adrien Badré, Shima Mohebbi, Leili Soltanisehat

{"title":"Secure decentralized decisions to enhance coordination in consolidated hospital systems","authors":"Adrien Badré, Shima Mohebbi, Leili Soltanisehat","doi":"10.1080/24725579.2019.1680582","DOIUrl":"https://doi.org/10.1080/24725579.2019.1680582","url":null,"abstract":"Abstract Shared decision making has become a crucial solution to build a consolidated healthcare system. While there is some research in the healthcare literature discussing the advantages and disadvantages of shared decision making, its efficiency has not been addressed quantitatively. In this paper, we propose a Decentralized Patients Assignment System (DPAS) as a universal decentralized decision making architecture. It utilizes the blockchain technology, machine learning, and integer programing to enhance coordination among healthcare providers and patients in consolidated hospital systems. To test the efficiency of the proposed DPAS, a prototype system is developed using an Agent-based model and Ethereum and is compared to the current practice of central referral systems in consolidated hospital systems. The agent-based model consists of four agents including patients, physicians, hospitals, and miners interacting within a decentralized system. The proposed system highlights the importance of interoperability and consensus among healthcare agents in the decision making process. The results demonstrate the DPAS efficiency in decreasing computational time and rejection rates for patients transfer.","PeriodicalId":37744,"journal":{"name":"IISE Transactions on Healthcare Systems Engineering","volume":"10 1","pages":"112 - 99"},"PeriodicalIF":0.0,"publicationDate":"2020-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24725579.2019.1680582","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46506721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Virtual reality based hybrid simulation for functional endoscopic sinus surgery 基于虚拟现实的鼻窦内窥镜手术混合仿真

IISE Transactions on Healthcare Systems Engineering Pub Date : 2020-04-02 DOI: 10.1080/24725579.2019.1692263

Saurabh Jain, Seunghan Lee, Samuel R. Barber, Eugene H Chang, Y. Son

{"title":"Virtual reality based hybrid simulation for functional endoscopic sinus surgery","authors":"Saurabh Jain, Seunghan Lee, Samuel R. Barber, Eugene H Chang, Y. Son","doi":"10.1080/24725579.2019.1692263","DOIUrl":"https://doi.org/10.1080/24725579.2019.1692263","url":null,"abstract":"Abstract Advances in Virtual Reality (VR) technology warrants the improvement of the training system to replicate surgical procedures. The VR-based training system has proved to be useful for surgical training by decreasing operative time and increasing patient safety. For example, Functional Endoscopic Sinus Surgery (FESS) is challenging due to the confined operating space surrounded by critical structures such as the eye, brain, and major blood vessels. Image-guided surgery in FESS enables the use of real-time navigation of surgical instruments to preoperative imaging. This paper demonstrates the development of a surgical simulator which facilitates trainees in three-fold. First, the identification and segmentation of critical structures in head and neck become achievable through the VR-based simulator. Second, the simulator supports to rehearse the surgical steps on a model of patient-specific anatomy. Finally, experiencing VR cues during surgical training facilitates faster recognition of anatomical landmarks. Standard computed tomography (CT) medical imaging data were utilized to develop a VR-based hybrid simulation. The validation study reveals that haptic feedback and visual/audio cues in the simulator supports the enhancement of operational accuracy and efficiency. Moreover, the proposed system works as a training tool, which will reduce patient morbidity and mortality.","PeriodicalId":37744,"journal":{"name":"IISE Transactions on Healthcare Systems Engineering","volume":"10 1","pages":"127 - 141"},"PeriodicalIF":0.0,"publicationDate":"2020-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24725579.2019.1692263","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42293473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Missing information imputation for disease-dedicated social networks with heterogeneous auxiliary data 基于异构辅助数据的疾病专用社交网络缺失信息的归算

IISE Transactions on Healthcare Systems Engineering Pub Date : 2020-01-30 DOI: 10.1080/24725579.2020.1716115

Xu Liu, Jingrui He, Wanli Min, Hongxia Yang

{"title":"Missing information imputation for disease-dedicated social networks with heterogeneous auxiliary data","authors":"Xu Liu, Jingrui He, Wanli Min, Hongxia Yang","doi":"10.1080/24725579.2020.1716115","DOIUrl":"https://doi.org/10.1080/24725579.2020.1716115","url":null,"abstract":"Abstract Many high impact applications suffer from missing information. For example, disease-dedicated social networks provide additional resources to glimpse into patients’ daily life related to disease management. However, due to the voluntary nature of such social networks, the information reported by patients is often incomplete, making the following data analytics tasks particularly challenging. On the other hand, in addition to the target data that we aim to analyze, we may also have other related data at our disposal. For example, to analyze disease-dedicated social networks, auxiliary clinical data (with potentially non-overlapping patients), as well as the users’ online social relationship might provide additional information for estimating the missing information. Therefore, the key question we aim to answer in this paper is how we can leverage the heterogeneous auxiliary data for the sake of missing information imputation. To answer this question, we focus on diabetes-dedicated social networks, and we aim to estimate the missing information from patients’ self-reported biomarker measurements. In particular, we propose a hypergraph structure to model the relationship among users and user-generated content (posts). Based on the hypergraph structure, we further introduce an optimization framework to estimate the missing biomarker measurements using heterogeneous auxiliary data. To solve the optimization framework, we design iterative algorithms to find the local optimal solution. Experimental results on both synthetic and real data sets (including a data set collected from a diabetes-dedicated social network) demonstrate the effectiveness of the proposed algorithms.","PeriodicalId":37744,"journal":{"name":"IISE Transactions on Healthcare Systems Engineering","volume":"10 1","pages":"87 - 98"},"PeriodicalIF":0.0,"publicationDate":"2020-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24725579.2020.1716115","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45143983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Managing virtual appointments in chronic care 管理慢性病护理中的虚拟预约

IISE Transactions on Healthcare Systems Engineering Pub Date : 2020-01-02 DOI: 10.1080/24725579.2019.1638849

A. Bayram, S. Deo, S. Iravani, K. Smilowitz

{"title":"Managing virtual appointments in chronic care","authors":"A. Bayram, S. Deo, S. Iravani, K. Smilowitz","doi":"10.1080/24725579.2019.1638849","DOIUrl":"https://doi.org/10.1080/24725579.2019.1638849","url":null,"abstract":"Abstract Virtual appointments between patients and healthcare providers can offer a cost-effective alternative to traditional office appointments for managing chronic conditions. Virtual appointments increase contact with the physician by either substituting or complementing office appointments, leading to improved health outcomes. The true value of virtual appointments cannot be realized until they are truly integrated with the office appointment systems. In this study, we introduce a capacity allocation model to study the use of virtual appointments in a chronic care setting. Specifically, we develop a finite horizon stochastic dynamic program to determine which patients to schedule for office and virtual appointments that maximizes aggregate health benefits across a cohort of patients. Optimal policy characterization for this problem is challenging. We find that, under certain conditions, a myopic heuristic, where the sickest patients are scheduled for office appointments and the next sickest patients are scheduled for virtual appointments, is optimal. We show that the myopic heuristic performs well even in more general settings. Our findings further show that virtual appointments serve a dual purpose: they may reduce the number of office appointments and may trigger follow-up office appointments.","PeriodicalId":37744,"journal":{"name":"IISE Transactions on Healthcare Systems Engineering","volume":"10 1","pages":"1 - 17"},"PeriodicalIF":0.0,"publicationDate":"2020-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24725579.2019.1638849","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41682551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Design of experiments and discrete-event simulation to study oncology nurse workload 肿瘤护士工作量研究的实验设计与离散事件模拟

IISE Transactions on Healthcare Systems Engineering Pub Date : 2020-01-02 DOI: 10.1080/24725579.2019.1680581

C. Baril, V. Gascon, Jonathan Miller

{"title":"Design of experiments and discrete-event simulation to study oncology nurse workload","authors":"C. Baril, V. Gascon, Jonathan Miller","doi":"10.1080/24725579.2019.1680581","DOIUrl":"https://doi.org/10.1080/24725579.2019.1680581","url":null,"abstract":"Abstract Due to the increasing number of cases of cancer, medical clinics specialized in cancer treatments must operate differently to meet demand. Besides growth in demand, research on cancer treatment has led to more complex chemotherapy protocols. The literature lists more than 170 chemotherapy protocols. However, in practice only a few are administered. In oncology, nurse-patients ratios and the treatment protocol to administer have an impact on nurse workload. The nurse-patients ratio is usually one nurse for four patients (1:4); meaning that the nurse administers treatments to four patients simultaneously. Delivering a chemotherapy treatment requires that the nurse performs different tasks according to the protocol. This research studies nurse workload related to the administration of chemotherapy treatments. Both physical and mental nurse workload are studied. We present an original quantitative approach based on discrete event simulation to measure nurse workload. It demonstrates that all protocols do not result in similar workloads. Our study shows that both physical and mental nurse workload should be taken into account in determining the nurse-patient ratio for the administration of chemotherapy treatment.","PeriodicalId":37744,"journal":{"name":"IISE Transactions on Healthcare Systems Engineering","volume":"10 1","pages":"74 - 86"},"PeriodicalIF":0.0,"publicationDate":"2020-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24725579.2019.1680581","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48479732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9