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This paper addresses the management of patients' transportation requests within a hospital, a very challenging problem where requests must be scheduled among the available porters so that patients arrive at their destination timely and the resources invested in patient transport are kept as low as possible. Transportation requests arrive during the day in an unpredictable manner, so they need to be scheduled in real-time. To ensure that the requests are scheduled in the best possible manner, one should also reconsider the decisions made on pending requests that have not yet been completed, a process that will be referred to as rescheduling. This paper proposes several policies to trigger and execute the rescheduling of pending requests and three approaches (a mathematical formulation, a constructive heuristic, and a local search heuristic) to solve each rescheduling problem. A simulation tool is proposed to assess the performance of the rescheduling strategies and the proposed scheduling methods to tackle instances inspired by a real mid-size hospital. Compared to a heuristic that mimics the way requests are currently handled in our partner hospital, the best combination of scheduling method and rescheduling strategy produces an average 5.7 minutes reduction in response time and a 13% reduction in the percentage of late requests. Furthermore, since the total distance walked by porters is substantially reduced, our experiments demonstrate that it is possible to reduce the number of porters - and therefore the operating costs - without reducing the current level of service.

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BACKGROUND: Over the past 2 years, the COVID-19 pandemic has placed enormous pressure on the health care industry. There has been an increase in demand and, at the same time, a shortage of supplies. This has shown that supply chain management in the health care industry cannot be taken for granted. Furthermore, the health care industry is also facing other major challenges, such as the current labor market shortage. In the literature, the Internet of Things (IoT) is highlighted as an effective tool to build a more resilient and efficient supply chain that can manage these challenges. Although using IoT in supply chain management has been extensively examined in other types of supply chains, its use in the health care supply chain has largely been overlooked. Given that the health care supply chain, compared to others, is more complex and is under growing pressure, a more in-depth understanding of the opportunities brought by IoT is necessary. OBJECTIVE: This study aims to address this research gap by identifying and ranking the drivers of and barriers to implementing IoT in the health care supply chain. METHODS: We conducted a 2-stage study. In the first, exploratory stage, a total of 12 semistructured interviews were conducted to identify drivers and barriers. In the second, confirmatory stage, a total of 26 health care supply chain professionals were asked in a survey to rank the drivers and barriers. RESULTS: The results show that there are multiple financial, operational, strategy-related, and supply chain-related drivers for implementing IoT. Similarly, there are various financial, strategy-related, supply chain-related, technology-related, and user-related barriers. The findings also show that supply chain-related drivers (eg, increased transparency, traceability, and collaboration with suppliers) are the strongest drivers, while financial barriers (eg, high implementation costs and difficulties in building a business case) are the biggest barriers to overcome. CONCLUSIONS: The findings of this study add to the limited literature regarding IoT in the health care supply chain by empirically identifying the most important drivers and barriers to IoT implementation. The ranking of drivers and barriers provides guidance for practitioners and health care provider leaders intending to implement IoT in the health care supply chain.

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Decontamination centres provide sterilisation services (sort, disinfect, package, and sterilise) for reusable surgical instruments that have a vital impact on patient safety. The market trend is to increase the level of automation in the decontamination process, to increase productivity, and reduce the risk of human error and musculoskeletal injuries. The goal of this research is to study the use of automated guided vehicles (AGVs) in sterilisation departments, to improve safety and efficiency. A generic simulation model is created based on data gathering of various decontamination centres and is validated for a specific centre to analyse various aspects of applying AGVs to automate the internal transfer. Centre's potential to increase capacity through AGV application is analysed and a Design of Experiments is conducted to identify the most promising implementation scenarios. Results show reductions in treatment time and work in process, while ,maintaining the accessibility of medical instruments, and ensuring worker safety.

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Public-private partnerships in emerging countries are gradually considered a tool for growth development. One particular public-private partnership is that of outsourcing logistics in the healthcare sector. These partnerships provide several benefits for both private and public sectors but are generally associated with numerous risks that must be evaluated and subsequently managed. The aim in this paper is to develop a risk evaluation approach to rank risks when decision makers' judgment is taken into consideration and where traditional risk evaluation techniques become less applicable. The proposed approach makes use of fuzzy multi-criteria decision analysis methods since they are efficient techniques to rank alternatives based on selected evaluation criteria and can accommodate human judgment and preferences. The approach treats predetermined risks like alternatives, and evaluation criteria are represented by areas of impact of the risks. To validate the approach, we applied it to a real case of logistics outsourcing to private service providers in a Moroccan public pharmaceutical supply chain. The ranking results obtained show that the two methods lead to some differences in ranking but are highly correlated. The obtained results support healthcare policy makers in setting priorities to effectively deploy preventive and mitigation efforts.

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PURPOSE: This study was conducted to characterize the vaccination practices and challenges of family medicine physicians in Los Angeles County, California. METHODS: The Los Angeles Academy of Family Physicians (LA AFP) sent out electronic surveys to all of their active members (N = 1121) between December 2017 and January 2018, and asked them to answer questions about themselves, their practice, their patient population, and their immunization practices and challenges. We then analyzed the results through basic statistical calculations and Pearson's chi-squared tests. RESULTS: Seventy-four people (6.6%) responded to the survey, and 75% of responders stated that they administer all Advisory Committee on Immunization Practices (ACIP) recommended vaccines. The lowest vaccine administration rates were for the high-dose influenza vaccine, which 66.2% (n = 49) of respondents reported to administer, followed by the meningococcal B vaccine (68.9%; n = 51). The respondents who belonged to practices with more than 11 providers, were part of a large hospital or healthcare system, had electronic medical records (EMRs), and used the California Immunization Registry (CAIR) were more likely to report to vaccinate. The number one responding physician-reported challenge to vaccination was limited time and resources to address patient resistance followed by vaccine cost and lack of infrastructure to store vaccines. CONCLUSIONS: In this pilot study, structural and logistical challenges appeared to make the biggest impact on adult vaccination for the responding family medicine physicians. Solutions addressing these challenges will help improve the adult immunization rates.

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