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BACKGROUND: The earliest days of the COVID-19 pandemic in Canada were marked by a significant surge in COVID-19 cases and COVID-19-related deaths among residents of long-term care facilities (LTCFs). As part of Canada's response to the COVID-19 pandemic, Canadian Armed Forces (CAF) personnel were mobilized for an initial emergency domestic deployment to the hardest-hit LTCFs (Operation LASER LTCF) to support the remaining civilian staff in ensuring the continued delivery of care to residents. Akin to what was observed following past CAF international humanitarian missions, there was an expected increased risk of exposure to multiple stressors that may be psychologically traumatic and potentially morally injurious in nature (ie, related to core values, eg, witnessing human suffering). Emerging data from health care workers exposed to the unprecedented medical challenges and dilemmas of the early pandemic stages also indicated that such experiences were associated with increased risk of adverse mental health outcomes. OBJECTIVE: This study aims to identify and quantify the individual-, group-, and organizational-level risk and resilience factors associated with moral distress, moral injury, and traditional mental health and well-being outcomes of Operation LASER LTCF CAF personnel. This paper aimed to document the methodology, implementation procedures, and participation metrics. METHODS: A multimethod research initiative was conducted consisting of 2 primary data collection studies (a quantitative survey and qualitative interviews). The quantitative arm was a complete enumeration survey with web-based, self-report questionnaires administered at 3 time points (3, 6, and 12 mo after deployment). The qualitative arm consisted of individual, web-based interviews with a focus on understanding the nuanced lived experiences of individuals participating in the Operation LASER LTCF deployment. RESULTS: CAF personnel deployed to Operation LASER LTCF (N=2595) were invited to participate in the study. Data collection is now complete. Overall, of the 2595 deployed personnel, 1088 (41.93%), 582 (22.43%), and 497 (19.15%) responded to the survey at time point 1 (3 mo), time point 2 (6 mo), and time point 3 (12 mo) after deployment, respectively. The target sample size for the qualitative interviews was set at approximately 50 considering resourcing and data saturation. Interest in participating in qualitative interviews surpassed expectations, with >200 individuals expressing interest; this allowed for purposive sampling across key characteristics, including gender, rank, Operation LASER LTCF role, and province. In total, 53 interviews were conducted. CONCLUSIONS: The data generated through this research have the potential to inform and promote better understanding of the well-being and mental health of Operation LASER LTCF personnel over time; identify general and Operation LASER LTCF-specific risk and protective factors; provide necessary support to the military personnel who served in this mission; and inform preparation and interventions for future missions, especially those more domestic and humanitarian in nature. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/44299.
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Integrated logistics support (ILS) is of great significance for maintaining equipment operational capability in the whole lifecycle. Numerous segments and complex product objects exist in the process of equipment ILS, which gives ILS data multi-source, heterogeneous, and multidimensional characteristics. The present ILS data cannot satisfy the demand for efficient utilization. Therefore, the unified modeling of ILS data is extremely urgent and significant. In this paper, a unified data modeling method is proposed to solve the consistent and comprehensive expression problem of ILS data. Firstly, a four-tier unified data modeling framework is constructed based on the analysis of ILS data characteristics. Secondly, the Core unified data model, Domain unified data model, and Instantiated unified data model are built successively. Then, the expressions of ILS data in the three dimensions of time, product, and activity are analyzed. Thirdly, the Lifecycle ILS unified data model is constructed, and the multidimensional information retrieval methods are discussed. Based on these, different systems in the equipment ILS process can share a set of data models and provide ILS designers with relevant data through different views. Finally, the practical ILS data models are constructed based on the developed unified data modeling software prototype, which verifies the feasibility of the proposed method.
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Armazenamento e Recuperação da Informação , SoftwareRESUMO
Novel coronavirus pneumonia (NCP), known as COVID-19 for short, is a new infectious disease that spreads rapidly. Since the outbreak of the epidemic, the global epidemic situation is still grim. It is necessary for a comprehensive grade triple-A hospital to strictly control the transmission risk in the hospital and ensure the life and health safety of medical staff, other patients and accompanying staff, in addition to fulfilling its responsibility of treating COVID-19 patients. In this context, unprecedented challenges have been posed to the routine work flow of the hospital, including personnel management, system construction, supply and logistics support, and infection control. The paper summarizes the experience in hospital logistics support management, aiming at exploring strategies for coping with the COVID-19 epidemic.
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Objective To analyze the drug consumption of the joint logistics support force during field training in Yunnan, summarize the drug use characteristics of medical staff, and analyze the drug use rules, so as to provide the basis for modular drug support. Methods The basic information and drug use of the personnel in an institution of the joint logistics support force during the resident training period from April to June 2020 were collected and sorted out. The drug use indicators were calculated by using the defined daily dose (DDD) as the unit, including: daily drug dose (DDDs), daily drug dose cost (DDDc), drug use intensity (DUI), drug utilization rate (DUR) and drug ranking ratio (R) were used to describe drug use characteristics. Results During the resident training period, the amount of musculoskeletal system drugs was large, and the number of users was large. The dosage of cardiovascular system drugs, digestive system drugs and hormone drugs was large, but the number of users was small. Sensory organ drugs, dermatological drugs, heat-clearing agents (Chinese patent medicine) and respiratory system drugs were small in dosages, but the number of users was large. Ranked by DDDs, the top 3 drugs with the highest dosage were Yunnan Baiyao plaster, Yunnan Baiyao Band-Aid and Loratadine Tablets. Ranked by DDDc, the largest daily cost was Budesonide and Formoterol Fumarate Powder for Inhalation. As age increases, the intensity of drug use increased; The intensity of drug use in women was greater than that in men. The intensity of drug use was different for different categories personnel. Conclusion Musculoskeletal system drugs are important drugs for field training. The task personnel should formulate a list of medicines for basic diseases based on their own medication for basic diseases and the duration of the task, and submit it to the medicinal material guarantee department to ensure the carrying drugs. The factors affecting modular drug support in field training include: task type, region, solar term, duration and personnel composition, etc.
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This article discusses the problems of logistical support for road maintenance to manage road accidents in Vhembe district municipalities. A budget deficit model was used to explain the level of inadequate logistics support to manage operations and maintenance of municipal roads as a preventative measure against road accident and disaster risks. A hypothetical road maintenance deficit model informed by current literature on road maintenance was used to explain how cost of road maintenance increases exponentially if initial maintenance was not undertaken when the facility was newly constructed to draw the link between road maintenance and the risk of road accidents. Inadequate logistical support to address road maintenance backlogs in Vhembe district municipalities has been on the increase over the last 10 years. Current studies show that inadequate road maintenance can lead to the development of potholes - a major cause of road accidents and damages to motor vehicles. Literature on logistics support emphasises a comprehensive approach to road maintenance to provide a balance between funding, routine maintenance, quality of materials used for maintenance, use of stipulated specifications, the required maintenance technology, innovations and employment of qualified service providers to ensure quality roads and reduction of accidents on municipal roads.
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Objective: To optimize the support relationship between units for military medical material supply and the supported units, so as to promote the rational utilization and allocation of units for military medical material supply in a region. Methods: The methods of Delphi and integer programming of operation research were adopted to construct optimal model based on the basic principles of joint logistics support. Results: Optimal distribution models were established based on the primary channel supply and fixed units position. The model was used to optimize the medical support relation in a certain region. Conclusion: The application of the optimal model suggests that the model is feasible. Decision support system developed based on the optimal model combined with geographic information system provide theoretical evidence and information tool for the adjustment of medical material support relation in a region.