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Objective: To analyse and continually improve existing issues in the quality improvement process of medical linear accelerators (LINACs) and enhance the quality control management of LINACs. Methods: Data were collected from eight LINACs (sourced from three manufacturers) at Zhejiang Cancer Hospital using Excel diaries between January 2019 and December 2020. The data description and analysis were performed using the analytic hierarchy process, SPSSAU and Excel software, and mean-time-to-repair (MTTR)/mean-time-between-failure (MTBF) metrics. Continuous quality improvement was executed using the quality control circle (QCC) quality management method. Results: After quality improvement, the risk frequency of 'LINAC down' events decreased by 43.63% and downtime was reduced by 40.45%. The weight of downtime risk improved by 73.69%. The MTTR recovery value increased by 31.90%, and MTBF reliability increased by 2.97 h. The simulation results demonstrated that the proposed quality improvement measures could effectively decrease the frequency and duration of downtimes, consequently extending the normal operational time of LINACs. Conclusion: Transitioning from instant repair to preventative maintenance can enhance the operational efficiency of equipment and yield economic benefits for hospitals. The QCC method and the event risk evaluation model are effective in reducing the downtime of LINACs and improving their quality control management.

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The difficulties of management were the key barriers to the promotion of decentralized wastewater treatment in remote areas. In this study, a novel decentralized Circulating Oxygenation Biofilm Equipment (COBE) and its remote management potential based on mathematical modeling were investigated. The COBE is an integrated biofilm reactor that employs drippage aeration and enables oxygenation, filtration, and effluent processes to be controlled, thus providing convenience for controlling. The model for the COBE describing drippage aeration, comprehensive ammonia-related microbes, and corncob carbon source release process was studied to uncover the impacts of operational conditions on decentralized wastewater treatment in the COBE system. The equipment regulation parameter (circulating oxygenation ratio) was found to be linearly correlated with the oxygen mass transfer coefficient. This discovery enabled highly accurate prediction of COD, NH4-N, and TN concentrations in the equipment effluent at various scenarios. The comprehensive ammonia oxidation biological model indicated that the model could duplicate the actual situation of the succession of ammonia metabolizing related microorganisms. Comammox and ammonia-oxidizing archaea (AOA) dominated ammonia metabolism in this equipment rather than conventional ammonium-oxidizing bacteria (AOB). This study could contribute to the Internet of Things system construction of decentralized wastewater treatment equipment, and provide a solution for timely decentralized equipment management in remote areas.

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Objective:To construct a rationality evaluation system for medical equipment allocation to providing a basis for procurement and rational allocation of medical equipment.Methods:Focusing on the theme of"rationality allocation of medical equipment"and the research objective of"development of an evaluation system",a questionnaire consultation was conducted on relevant personnel in medical institutions in nine provinces and municipalities nationwide by way of wjx.cnas.The relevant research on the construction of the rationality evaluation system for medical equipment allocation in tertiary hospitals from August 2017 to August 2022 was retrieved from China National Knowledge Infrastructure,Wanfang Data Knowledge Service Platform,VIP Chinese Science and Technology Journal Database,and China Biomedical Literature Database.The index system was constructed by literature study and improved Delphi method,and the index weight was calculated by Analytic Hierarchy Process(AHP)to determine the evaluation system of rationality of medical equipment allocation.Results:The established evaluation system for the rationality of medical equipment allocation included four primary indicators of allocation reasons and conditions,cost factors,benefit factors,and management factors,as well as 17 secondary indicators.Conclusion:The establishment of the evaluation system for the reasonableness of allocation of medical equipment can help the allocation of medical equipment be carried out more objectively and efficiently and provide a basis for scientific procurement and reasonable allocation of medical equipment.

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Objective:Based on the construction of intelligent intensive care unit(ICU)in hospital,to analyze the effectiveness of intelligent ICU life support equipment in clinical decision-making assistance.Methods:The functional modules of the ICU ward interaction system,equipment management system,risk response system and intelligent ward round system were designed to collect information and data of life support equipment in diagnosis and treatment,nursing,operation and technical support in real time to provide medical auxiliary decision-making basis for the improvement of diagnosis,treatment and nursing measures for critically ill patients.115 life-support equipment in clinical use in 3 hospitals including Zhujiajiao People's Hospital of Qingpu District,Shanghai from July 1,2018 to December 31,2022 were selected,the traditional assisted decision-making management mode(referred to as traditional mode,83 sets)and intelligent assisted decision-making management mode(referred to as intelligent mode,89 sets,including 57 units of the traditional mode and 32 newly added units)were adopted respectively.The management level and management effect of life support equipment of the two management modes were compared.Results:The data collection time of the equipment of intelligent mode was(5.67±2.80)min,which was less than that of the traditional mode,the accuracy and completeness of data acquisition,as well as the effective resolution rate of equipment deployment and use,monitoring and alarm,equipment failure and emergency response were(99.02±1.14)%,(94.35±3.46)%,(98.78±0.90)%,(98.99±0.91)%,(88.26±5.31)% and(90.23±5.54)%,respectively,which were higher than those of the traditional mode,the difference between was statistically significant(t=6.504,6.474,3.574,7.620,6.784,4.522,3.719,P<0.05).The effective utilization rates of diagnostic decisions for treatment,care and rehabilitation of intelligent mode equipment were(93.83±3.12)%,(94.99±2.47)% and(91.44±4.62)%,respectively,the comprehensive scores of respiratory function support equipment,circulatory function support equipment,blood purification support equipment and emergency monitoring support equipment were(92.97±4.35)points,(94.34±2.95)points,(93.01±2.44)points and(94.11±1.89)points,respectively,which were higher than those of the traditional mode,the difference was statistically significant(t=4.169,4.875,5.159,4.069,3.033,2.757,6.893,P<0.05).Conclusion:Based on the construction of intelligent ICU,it can improve the quality of life support equipment operation data collection,solve the equipment operation problems in a timely manner,provide an effective basis for the decision-making of diagnosis and treatment,nursing and rehabilitation of critically ill patients,and improve the clinical service level of equipment.

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Background: Medical equipment are vital items to deliver quality services in health facilities and the role of medical equipment is a well-founded reality. It is mainly used in many diverse settings in hospitals to diagnose, treat illnesses; support disabled and intervened acute and chronic cases. Effective maintenance and proper management are major utilization issues to provide quality services while saving scarce resources. However, managing medical equipment, especially, the utilization phase of medical equipment, was not well studied in this general hospital. Objective: This study aims to assess the utilization of medical devices in Tulu Bolo General Hospital. Methods: The study was conducted from December 25, 2021 to February 9, 2022. Data sources included health professionals and document archives in the hospital. Data collection method includes questionnaires and observations checklists. A census of 165 health workers was conducted, with a response rate 94.5%. Data was entered into epi-data; version 3.1, then analyzed by SPSS version 23 and presented using descriptive statistics. Results: Procurement, storage, and utilization were found to be 53.47%, 56.57%, and 45.88%, respectively. Only 114 (57.3%) of the 199 pieces of medical equipment discovered were functional. Pearson correlation indicated that procurement and utilization of medical equipment are related to a higher proportion of non-functional devices (P = 0.000, B1 = 1.47, OR = 4.349, and CI 95% = 2.047-9.241) and nonfunctional medical equipment (B2 = 0.790, OR = 2.203, and CI 95% = 1.065-4.556) for procurement and utilization, respectively. Conclusion: Procurement, storage, and utilization of available medical equipment in Tulu Bolo Hospital were low. While health sectors operating in a resource-limited were assumed to have a big shortage of medical technologies, procurement, storage, and utilization of the limited available medical equipment need the attention of health program managers.

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Substantial investments into laboratories, notably sophisticated equipment, have been made over time to detect emerging diseases close to their source. Diagnostic capacity has expanded as a result, but challenges have emerged. The Equipment Management and Sustainability Survey was sent to the Veterinary Services of 182 countries in mid-2019. We measured the status of forty types of laboratory equipment used in veterinary diagnostic laboratories. Of the 68,455 items reported from 227 laboratories in 136 countries, 22% (14,894/68,455) were improperly maintained, and 46% (29,957/65,490) were improperly calibrated. Notable differences were observed across World Bank income levels and regions, raising concerns about equipment reliability and the results they produce. Our results will advise partners and donors on how best to support low-resource veterinary laboratories to improve sustainability and fulfill their mandate toward pandemic prevention and preparedness, as well as encourage equipment manufacturers to spur innovation and develop more sustainable products that meet end-users' needs.

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Machine learning methods can establish complex nonlinear relationships between input and response variables for stadium fire risk assessment. However, the output of machine learning models is considered very difficult due to their complex "black box" structure, which hinders their application in stadium fire risk assessment. The SHapley Additive exPlanations (SHAP) method makes a local approximation to the predictions of any regression or classification model so as to be faithful and interpretable, and assigns significant values (SHAP value) to each input variable for a given prediction. In this study, we designed an indicator attribute threshold interval to classify and quantify different fire risk category data, and then used a random forest model combined with SHAP strategy in order to establish a stadium fire risk assessment model. The main objective is to analyze the impact analysis of each risk characteristic on four different risk assessment models, so as to find the complex nonlinear relationship between risk characteristics and stadium fire risk. This helps managers to be able to make appropriate fire safety management and smart decisions before an incident occurs and in a targeted manner to reduce the incidence of fires. The experimental results show that the established interpretable random forest model provides 83% accuracy, 86% precision, and 85% recall for the stadium fire risk test dataset. The study also shows that the low level of data makes it difficult to identify the range of decision boundaries for Critical mode and Hazardous mode.

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Objective To design a mobile intelligent inventory system for medical equipment to solve the problems of medical equipment management in efficiency and accuracy due to manual inventory.Methods A mobile intelligent inventory system for medical equipment was designed with radio frequency identification(RFID)technology,optical character recognition technology and wireless network technology,which was composed of a photo acquisition device,an inventory workstation,a wireless router,a mobile cart,a RFID barcode printer and a mobile power source.The photo acquisition device realized equipment image collection with a photography App in the cell phone or tablet computer;the inventory workstation consisted of an offline inventory system and an equipment nameplate recognition system,which built inventory tasks with Tomcat Web service and identified equipment nameplate information through feature-based learning algorithms;the RFID barcode printer controlled label printing by an offline inventory system embedded into its driver.Results The system developed executed medical equipment inventory and labeling simultaneously,which established electronic file for each piece of equipment to realize accounts corresponding to the equipment accurately.Conclusion The inventory system developed enhances the efficiency of medical equipment inventory,standardizes the flow of medical equipment ledger management and provides support for life-cycle management of medical equipment.[Chinese Medical Equipment Journal,2023,44(11):45-49]

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The problems existing in the management of medical equipment in the General hospital of the Ethiopian Defense Forces were introduced,and some suggestions were put forward from domestic aid units,equipment suppliers,aid medical teams and assisted hospitals.The management efficiency of aid-Ethiopia medical equipment and the medical service capacity of the assisted hospitals were enhanced greatly.References were provided for the medical equipment management during foreign aid missions.[Chinese Medical Equipment Journal,2023,44(11):95-99]

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The Elekta Synergy Linear Accelerator in some hospital from 2012 to 2022 were retrospectively analyzed in terms of operation,failure time distribution and failure of each system.Some countermeasures were put forward accordingly to decrease the failure rate and strengthen the training of relevant personnel's operation and maintenance.References were provided for effective management and operation of medical linear accelerators.

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Introduction To establish a centralized inventory management system for the efficient functioning of all healthcare facilities, e-Upkaran (equipment management and maintenance system) was launched in 2015 in the state of Rajasthan. This study is conducted to assess the functioning of e-Upkaran in Rajasthan. Methods The assessment of the e-Upkaran system for primary and secondary healthcare centers was carried out using a systematic review of the literature and a multi-indicator stakeholder questionnaire. The benefits evaluation framework focused on the system quality, information and service quality, use and user satisfaction, and net benefits utilized for the assessment. A review of the literature was done to highlight the importance of computerized medical equipment management and maintenance systems and appraise the challenges and benefits associated with such systems as compared to the traditional pen-paper register. Information was gathered based on available documents, field observation, and data obtained from specific hospital staff, including the bioengineers and other users of e-Upkaran. Results The finding of this study suggests that e-Upkaran efficiently improves documentation, reporting, maintenance, and management of medical equipment. It is more efficient than the traditional paper-pen system. It is designed to minimize downtime and maintain equipment in good operating condition and has potential benefits in terms of improving information quality, use, and net benefit. The cost of service ratio is within the benchmark value. This system has also considerably reduced out-of-pocket expenditure. Computer proficiency and the workload of other e-health programs pose a challenge in the implementation of this program. Conclusion The e-Upkaran system is competent in terms of improving information quality, use, and net benefit. Other Indian states could also adopt this system to improve their biomedical equipment management and maintenance system.

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Recently, COVID-19 has infected a lot of people around the world. The healthcare systems are overwhelmed because of this virus. The intensive care unit (ICU) as a part of the healthcare sector has faced several challenges due to the poor information quality provided by current ICUs' medical equipment management. IoT has raised the ability for vital data transfer in the healthcare sector of the new century. However, most of the existing paradigms have adopted IoT technology to track patients' health statuses. Therefore, there is a lack of understanding on how to utilize such technology for ICUs' medical equipment management. This paper proposes a novel IoT-based paradigm called IoT Based Paradigm for Medical Equipment Management Systems (IoT MEMS) to manage medical equipment of ICUs efficiently. It employs IoT technology to enhance the information flow between medical equipment management systems (THIS) and ICUs during the COVID-19 outbreak to ensure the highest level of transparency and fairness in reallocating medical equipment. We described in detail the theoretical and practical aspects of IoT MEMS. Adopting IoT MEMS will enhance hospital capacity and capability in mitigating COVID-19 efficiently. It will also positively influence the information quality of (THIS) and strengthen trust and transparency among the stakeholders.

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BACKGROUND: This study aims to explore the information chain management model of large instrument and equipment inter-working in the operating room (OR) led by information nurses. METHODS: Through the chain management process of large instruments and equipment in the OR, which was based on information nurses, the management model of inter-working and integrating information chain was established, the key links were controlled, and the whole life cycle management of instruments and equipment from expected procurement to scrapping treatment was realized. Using the cluster sampling method, 1562 surgical patients were selected. Among these patients, 749 patients were assigned to the control group before the running mode, and 813 patients were assigned to the observation group after the running mode. The related indexes for large instrument and equipment management in the department before and after the running mode were compared. RESULTS: In the observation group, the average time of equipment registration was (22.05 ± 2.36), the cost was reduced by 2220 yuan/year, and the satisfaction rate of the nursing staff was 97.62%. These were significantly better, when compared to the control group (P < 0.05). Furthermore, the awareness rate of the whole staff for equipment repair application was 95.12%, and the arrival time of maintenance personnel and the examination and approval time of equipment management were greatly shortened (P < 0.05). CONCLUSION: The integrated management model of large instrument and equipment interworking in the OR based on chain flow realizes the whole life cycle management of instruments and equipment, which is essential to improve management efficiency.

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With the technology development in Internet of Things (IoT) area, it is good to try to use IoT and cloud computing technologies to improve the efficiency of medical equipment management. This article described using CT as sample to do the data capture and data analysis with the IoT technology. The positive result got shows the benefit of the exploring.

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OBJECTIVE: Aiming at the different characteristics of the various stages of medical equipment life cycle in hospital, research on the targeted and meticulous management mode. METHODS: Divides the whole life cycle of medical equipment in hospital into four phases, which are the selection demonstration period, purchase acceptance period, maintenance period, and retirement disposal period, and comparison with human fetal period, infant stage, adult stage and old age. RESULTS: With the meticulous management mode, the service quality of medical equipment in hospital has been improved, and the service benefits have been enhanced. CONCLUSIONS: According to the respective characteristics of different stages, the corresponding meticulous management mode is implemented to make the management more scientific and standardized, and the operation is safer and more reliable, which escorts the whole life cycle of medical equipment in hospital.

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With the continuous improvement of the hospital diagnosis and treatment level and the continuous renewal of medical equipment in China, the mismatch between medical equipment management personnel training and the introduction of medical equipment, the development of medical technology and the requirements of modern hospital management is increasingly prominent. This article is based on a current situation survey of medical equipment and management personnel at all levels of hospitals in Shanghai. It discusses joint with professional colleges and universities, and gives suggestions about needs, objectives and practice of personnel training. It provides references to improve the personnel training of medical equipment.

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With the technology development in Internet of Things (IoT) area, it is good to try to use IoT and cloud computing technologies to improve the efficiency of medical equipment management. This article described using CT as sample to do the data capture and data analysis with the IoT technology. The positive result got shows the benefit of the exploring.

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OBJECTIVE@#Aiming at the different characteristics of the various stages of medical equipment life cycle in hospital, research on the targeted and meticulous management mode.@*METHODS@#Divides the whole life cycle of medical equipment in hospital into four phases, which are the selection demonstration period, purchase acceptance period, maintenance period, and retirement disposal period, and comparison with human fetal period, infant stage, adult stage and old age.@*RESULTS@#With the meticulous management mode, the service quality of medical equipment in hospital has been improved, and the service benefits have been enhanced.@*CONCLUSIONS@#According to the respective characteristics of different stages, the corresponding meticulous management mode is implemented to make the management more scientific and standardized, and the operation is safer and more reliable, which escorts the whole life cycle of medical equipment in hospital.

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With the continuous improvement of the hospital diagnosis and treatment level and the continuous renewal of medical equipment in China, the mismatch between medical equipment management personnel training and the introduction of medical equipment, the development of medical technology and the requirements of modern hospital management is increasingly prominent. This article is based on a current situation survey of medical equipment and management personnel at all levels of hospitals in Shanghai. It discusses joint with professional colleges and universities, and gives suggestions about needs, objectives and practice of personnel training. It provides references to improve the personnel training of medical equipment.

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Starting from the research on the whole life cycle management of medical equipment, based on the development and application of HRP management system, according to the characteristics of medical device management, this paper studies the specific implementation method of medical device life cycle management based on HRP system. Then, it provides an asset management solution of decision, management and operation for the decision, management and executive layer of the hospital.

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