Medical Equipment Maintenance Research Articles

Role of metaheuristic algorithms in healthcare: A comprehensive investigation across clinical diagnosis, medical imaging, operations management, and public health

Abstract Metaheuristic algorithms have emerged in recent years as effective computational tools for addressing complex optimization problems in many areas, including healthcare. These algorithms can efficiently search through large solution spaces and locate optimal or near-optimal responses to complex issues. Although metaheuristic algorithms are crucial, previous review studies have not thoroughly investigated their applications in key healthcare areas such as clinical diagnosis and monitoring, medical imaging and processing, healthcare operations and management, as well as public health and emergency response. Numerous studies also failed to highlight the common challenges faced by metaheuristics in these areas. This review thus offers a comprehensive understanding of metaheuristic algorithms in these domains, along with their challenges and future development. It focuses on specific challenges associated with data quality and quantity, privacy and security, the complexity of high-dimensional spaces, and interpretability. We also investigate the capacity of metaheuristics to tackle and mitigate these challenges efficiently. Metaheuristic algorithms have significantly contributed to clinical decision-making by optimizing treatment plans and resource allocation and improving patient outcomes, as demonstrated in the literature. Nevertheless, the improper utilization of metaheuristic algorithms may give rise to various complications within medicine and healthcare despite their numerous benefits. Primary concerns comprise the complexity of the algorithms employed, the challenge in understanding the outcomes, and ethical considerations concerning data confidentiality and the well-being of patients. Advanced metaheuristic algorithms can optimize the scheduling of maintenance for medical equipment, minimizing operational downtime and ensuring continuous access to critical resources.

Using Analytical Hierarchy Process for Medical Equipment Maintenance and Replacement Decision in Malaysia Private Hospitals

Medical equipment is any instrument, appliance, software, or material intended by the manufacturer to be used, alone or in combination for medical purpose. Further, medical equipment maintenance and replacement is a challenging procedure, especially for high-end equipment. This topic has been a long debate as the equipment will increase undesirable failure; where an early maintenance or replacement will result in high investment costs and premature disposal and late maintenance or replacement will lead to malfunctions that can pose serious risks to patient safety and healthcare operations. However, hospitals are unable to decide whether to maintain or replace the equipment especially when the equipment reaches its life and has a high repair cost. A few studies were conducted on the same research topic, but most of the findings emphasized maintenance and replacement methods rather than the criteria contributing to the decision. The criteria to maintain or replace medical equipment play an essential role to ensure the equipment is operating cost-effectively. Hence, the objective of this research is to apply Analytical Hierarchy Process (AHP) approach to prioritize important criteria that influence decision-makers to decide whether to maintain or replace medical equipment. Some of potential criteria for the decision-making include maintenance cost, support, and regulatory compliance. This research utilized a mixed method approach to gather preliminary data from medical equipment experts and surveys to prioritize the criteria. Findings suggested a list of criteria that are influenced in decision-making to maintain or replace the medical equipment. The prioritization of the criteria reveals the downtime, life cycle cost and beyond economical repair (BER) to be the most important criteria.

Biomedical Engineering Education in Nigeria

In the past five decades, Nigeria has witnessed a range of Biomedical Engineering (BME) and technology activities within private and public hospitals, research institutions, and a limited number of universities. These have mainly centred on the procurement, installation, and maintenance of medical equipment and devices. Trained technologists and technicians, equipped with relevant skills and certification, have primarily spearheaded these efforts. Consequently, the country has made a minimal contribution to the global knowledge base in BME research. However, academic programmes leading to degrees and dedicated research in BME have recently emerged within Nigerian universities. This article assesses the current state of BME education in the country, including the milestones achieved, ongoing challenges, and prospects for future development. It draws on a critical analysis of the existing literature on BME practices and education in Nigeria as well as the author’s informed perspective. The findings highlight that BME education in Nigeria is yet to match international standards. To further develop these programmes, it recommends that attention focus on seven key areas that have proven instrumental in the development of similar university programmes in developed nations. Strategies are also proposed to foster collaboration among universities, researchers, the health sector, and government entities that would promote interdisciplinary BME education, ultimately enhancing the healthcare delivery system, and research and development (R&D) in Nigeria.

Evaluation of medical equipment maintenance and skilled manpower requirement among private dental centres in Riyadh, Saudi Arabia: A pilot study.

Adequate equipment maintenance is necessary to ensure efficient dental care facilities and satisfactory medical equipment performance. This study aimed to assess maintenance practices and manpower adequacy in private dental centres (DCs) across Riyadh, Saudi Arabia. A questionnaire was designed to evaluate equipment maintenance and manpower strength based on international and national standards. Thirty-three private DCs were visited in-person with the designed questionnaire to conduct the study. The Chi-square test and t-test were performed. Only 21 dental centres had a scheduled maintenance plan for medical equipment, whereas the rest had no plan. Furthermore, only 22 DCs maintained equipment maintenance records, while 11 DCs did not have any records. Additionally, the study found a lack of trained personnel to handle medical equipment and overall inadequate maintenance practices. Significant differences were observed between the responses for many questions (p< 0.05). These findings increase health risks to both the patient and the user. To address these issues, DC administrators should implement stricter measures to adhere to local DCs standards and hire qualified personnel who can periodically maintain and repair medical equipment.

A Framework for Medical Equipment Maintenance and Replacement in Private Hospitals

A Framework for Medical Equipment Maintenance and Replacement in Private Hospitals

Blockchain-based trusted accountability in the maintenance of medical imaging equipment

Preventative maintenance is imperative for ensuring the longevity and reliability of diagnostic medical imaging equipment. However, conventional maintenance systems face challenges related to centralization, fragmented information, and ineffective tracking mechanisms. In response to these challenges, this research presents a blockchain-based solution that introduces a robust framework for managing preventative maintenance tasks. The proposed solution leverages blockchain technology, smart contracts, IPFS, and timer oracles to promote transparency, accountability, and traceability in maintenance operations. To ensure the integrity and availability of maintenance data while preserving the confidentiality of sensitive information, a detailed system architecture is outlined. Sequence diagrams and algorithms are developed to define the flow and logic of the solution, focusing on automatic fault detection and diagnosis. The smart contracts, which are made publicly available on GitHub, were rigorously tested to guarantee their intended functionality, thus addressing software reliability concerns. Additionally, the solution includes a maintenance incentive mechanism, actively motivating stakeholders to engage in preventative maintenance activities, and establishing accountability. Security testing confirms the absence of vulnerabilities in smart contracts, aligning with the scope of automatic fault detection and diagnosis. Furthermore, potential generalizations of the solution are discussed, and future directions emphasize the importance of continuous improvement and innovation in maintenance practices.

The Role and Function of Surveyors in the Maintenance of Medical Equipment in Hospitals (Literature Review)

This article attempts to delve deeper into the role and function of a surveyor in assessing a healthcare-related element. Through accreditation bodies, a surveyor is expected to be more proactive in carrying out their role and functions. This article employs a literature review by attempting to distill insights from various studies and expert opinions, as well as guidelines published by the Ministry of Health. Through this article, an illustration and a thought on how healthcare equipment in hospitals should be treated are conveyed. As a conclusion from this article, understanding healthcare equipment is crucial, and the role of a surveyor should be optimized. The surveyor's role as a companion and evaluator in this context becomes an essential element in ensuring innovation and the highest standards in healthcare equipment management in hospitals.

Decision-Making Framework for Medical Equipment Maintenance and Replacement in Private Hospitals

The process for medical equipment maintenance and replacement in hospitals is a challenging and demanding procedure. Further, the topic of making decisions to maintain or replace or upgrade medical equipment has been debated for a long time since errors equipment maintenance will increase equipment failure at undesirable times; or if early equipment replacement will result in high investment costs and premature disposal. Therefore, standard operating procedures or guidelines need to be in place to help healthcare facilities conduct a more organized and planned maintenance and replacement process. Many hospitals may already have established replacement guidelines or have implemented asset monitoring systems for this purpose. However, the effectiveness of this system has not yet been systematically evaluated. Several studies have been conducted on the same research topic, but most of the findings emphasize the replacement method rather than the criteria that contributed to the decision. Criteria for replacing medical equipment play an important role in ensuring that the equipment can be used cost-effectively. Thus, this research aims to identify important criteria that need to be considered for medical equipment maintenance and replacement focusing on private hospitals. This research was conducted in three phases: (1) a structured literature review; (2) semi-structured interviews with eleven (11) healthcare experts; and (3) a pairwise comparison survey with 50 biomedical engineers. A decision-making framework was developed based on the findings of these three research phases. The framework developed will provide guidelines for practitioners and academics to understand and make better decisions for medical equipment maintenance and replacement in the context of private hospitals.

A New Approach for Effective Reliability Management of Biomedical Equipment

Within the modern hospitals, an increasingly common problem is the efficient management of the maintenance of biomedical equipment. If effective management of medical equipment maintenance is applied, quality health services could be provided by reducing the downtime of medical equipment as well as by decreasing the recovery time for treatment of patients. Risk based maintenance strategy helps in designing an alternative methodology to minimize the risk by identifying the breakdown pattern and then increasing the reliability. The probability of failures that obstruct the reliability can be influenced by some technical, administrative or management actions. The proposed study is based on the analysis of reliability and availability for maintenance planning on the basis of risk index and fault tree analysis. Maintenance of equipment is prioritized based on the risk which helps in reducing the overall risk of the hospital. Fault tree diagram is also developed to understand the actual scenario where highest priority or risk events are sequentially arranged. Failure probability for different biomedical equipment has been established by applying statistical method. It has been observed that Magnetic Resonance Imaging has the lowest risk index while X-Ray has the highest risk index. Also, maintenance planning has been suggested based on the reduction of risk factor to meet the acceptable criteria and reduce the probability of failure. This approach depicts that reliability of equipment is increased after implementation of maintenance planning proposed which contributes to the availability of the equipment as well as its safe operation.

Service-oriented multi-skilled technician routing and scheduling problem for medical equipment maintenance with sudden breakdown

Motivated by the service-oriented intelligent maintenance activity under the development of the digital economy, we study the operation and maintenance strategies of the Maintenance Scheduling and Technician Routing Problem (MSTRP) for medical equipment implemented by multi-skilled technicians. We consider the maintenance services provided for both preventive maintenance (PM, e.g., periodic maintenance based on the contract schedule) and corrective maintenance (CM, e.g., repair action in the event of a sudden breakdown). As these activities are performed on equipment with various types of requirements at different geographically distributed systems, technicians with diverse qualifications need to build teams and visit the matching maintenance requests. Meanwhile, we consider the maintenance actions concerning the dynamic change in equipment failure rate and establish a flexible maintenance mechanism by balancing the total cost. This paper develops an efficient hybrid heuristic based on a genetic algorithm, variable neighborhood search, and other optimization strategies to solve this multi-period equipment maintenance scheduling and multi-skilled technician routing and scheduling problem. Based on the settings of the studied MSTRP, this paper designs different sizes of testing instances and multi-period explanatory cases before conducting extensive comparative experiments and sensitivity analysis to demonstrate the effectiveness of our proposed dynamic maintenance strategy and optimization method.

Integrated failure analysis using machine learning predictive system for smart management of medical equipment maintenance

The study aims to develop the failure analysis predictive models, which prognosticate first failure event (FFE), failure-to-year ratio (FYR), and failure rectification group (FRG). The construction of predictive models involved nineteen categories of 13,350 units of medical equipment. We proposed thirteen novel features in assessing medical equipment failures. The failure analysis predictive models were categorised into several classes for training and testing the developed models. There was seven supervised machine learning classifiers and performance metrics applied in the experiment. The experiment demonstrates that Support Vector Machine is the best classifier for the FFE predictive model, which achieves an accuracy of 96.9% after hyperparameter optimisation. Furthermore, Decision Tree is the best classifier for FYR, with an accuracy of 83.9%. Meanwhile, the comparative analysis for FRG discovered that Artificial Neural Network achieved the highest accuracy among others with 76.7% accuracy after the hyperparameter optimisation process. Findings from this study indicate that this failure analysis predictive model functions as a main instrument for conducting predictive maintenance in the direction of smart maintenance practices. Through the developed predictive systems, timely maintenance of medical equipment can be performed. This will also assist healthcare service providers in initiating the remanufacturing and refurbishment programme, ensuring efficient medical care delivery. The suggested framework of machine learning-assisted failure analysis for medical equipment maintenance management may provide clinical engineers with guidance for managing the strategic maintenance management for medical equipment.

Medical Equipment Maintenance Management System

Maintenance management is an orderly and systematic approach for planning, organizing, monitoring, and evaluating maintenance activities and their costs. A good maintenance management system coupled with knowledgeable and capable maintenance staff can prevent health and safety problems and environmental damage; yield longer asset life with fewer breakdowns, and result in lower operating costs and a higher quality of life. The medical equipment maintenance could be either preventive or corrective. The medical equipment management professionals ensure that equipment used in the patients care is operational, safe, and properly configured to meet the mission of the medical treatment facility and continue to function effectively in a good working condition. For example, proper maintenance can extend the life of equipment. This is essential for providing good health services and saving the scarce resources. A comprehensive review on the subject of medical devices maintenance management system has been done to give an overview of the development of this system in the hospitals and to shine what could be enhanced and improved in this system to promote the patient's healthcare.

Bluetooth-Based Healthcare Information and Medical Resource Management System.

This paper presents a healthcare information and medical resource management platform utilizing wearable devices, physiological sensors, and an indoor positioning system (IPS). This platform provides medical healthcare information management based on the physiological information collected by wearable devices and Bluetooth data collectors. The Internet of Things (IoT) is constructed for this medical care purpose. The collected data are classified and used to monitor the status of patients in real time with a Secure MQTT mechanism. The measured physiological signals are also used for developing an IPS. When the patient is out of the safety zone, the IPS will send an alert message instantly by pushing the server to remind the caretaker, easing the caretaker's burden and offering extra protection for the patient. The presented system also provides medical resource management with the help of IPS. The medical equipment and devices can be tracked by IPS to tackle some equipment rental problems, such as lost and found. A platform for the medical staff work coordination information exchange and transmission is also developed to expedite the maintenance of medical equipment, providing the shared medical information to healthcare and management staff in a timely and transparent manner. The presented system in this paper will finally reduce the loading of medical staff during the COVID-19 pandemic period.

Finding Scope for Implementing Correct Strategy for Maintenance of Medical Equipment Using Failure Database

Finding Scope for Implementing Correct Strategy for Maintenance of Medical Equipment Using Failure Database

ASSESSMENT OF KNOWLEDGE ON PRESERVATION AND USE OF MEDICAL EQUIPMENT THROUGH SKILL TEST OF MEDICAL STAFF

Introduction: Medical equipment and machinery is an essential means for physicians to diagnose, monitor, care and treat patients correctly and effectively. &#x0D; Objective: Situation of using and preserving some medical equipment at Nhanai hospital in 2019, research is carried out on groups of nurses who directly take care of patients at hospitals. &#x0D; Method: Cut horizontal description. Results: Through analysis of occupational test results of 81 Nursing patients in 2019, we found that the proportion of nurses with the right general knowledge in preserving war 91.3%; Knowledge of using ECG, Electric syringe, Monitor are: 93.8%: 79.1%: 68.1%. Factors related to knowledge of use and storage of equipment are not statistically significant. &#x0D; Conclusion: Regularly organizing training courses on the use and maintenance of medical equipment for nursing in hospitals is very necessary in the coming time.

Medical Equipment Maintenance: Why is Prevention better than cure

A wide range of medical equipment are used within medical institutions for prevention, monitoring, diagnosis and treatment, therefore, forming an integral part of the healthcare pathway. For healthcare providers, the proper functioning of these medical devices is of huge importance because of their role in delivering quality services to patients and considering the associated repair costs. Today, budget restrictions within numerous private and public healthcare facilities present a severe issue of patients being treated on ageing equipment, which are often also defective. This defeats the healthcare system’s primary purpose in offering patients quality care. It also risks the operational efficiency and reputation of such medical facilities.

Virtual and Augmented Reality for Training and Maintenance of a Multiparameter Monitor

Virtual reality (VR) and augmented reality (AR) have experienced a significant boom in recent years regarding their features and utility. They have become reliable tools that are applied in different fields and disciplines (medicine, industry, science, teaching, training, and robotics, among others). In the present research work, these technologies are used as tools for the training and maintenance of medical equipment. An application was developed using flexible programming and design software, such as Vuforia, Unity, SolidWorks, Visual Studio, and hardware such as smartphones and the HTC VIVE glasses. Considering the existing need and based on surveys carried out to medical and hospital technical staff, significant results were obtained about the use of AR and VR in the area of medicine. The use of interactive applications enables autonomous training, which may be executed at any time and it is also user-friendly; in addition, it enables achieving reduced maintenance time and improves the process of acquiring abilities, thus releasing resources for other purposes.

Design of Fine Life Cycle Prediction System for Failure of Medical Equipment

The inquiry process of traditional medical equipment maintenance management is complicated, which seriously affects the efficiency and accuracy of medical equipment maintenance management, and causes a lot of waste of manpower and materials. In order to accurately predict the failure of medical equipment, an accurate prediction system for failure life cycle of medical equipment was designed. The system is divided into four modules: the whole life cycle management module constructs the life cycle data set of medical devices from the three parts of the management in the early stage, the middle and the later stage; the status detection module monitors the main operation data of the medical device components through the normal value of the relevant sensitive data in the whole life cycle management module; the main function of the fault diagnosis module is based on the medical equipment whole life cycle management module. The operation data of equipment is diagnosed by inference machine; the fault prediction module builds a fine prediction system based on least square support vector machine algorithm, and uses AFS ABC algorithm to optimize the model to obtain the optimal model with the regularized parameters and width parameters, and the optimal model is used to predict the medical equipment failure. In order to verify the effectiveness of the design system, comparative experiments are designed to verify. The results show that the designed system can accurately predict the failure of electrocardiogram diagnostic instrument and incubator, and has high support and reliability. Compared with the comparison system, the prediction error of the design system is the smallest and the program running time is the shortest. Therefore, the design system can accurately predict the different failure types and causes of medical devices.&#x0D;

Applying a Data Analytics Approach to Medical Equipment Maintenance Management to Improve the Mean Time Between Failure and Availability

Applying a Data Analytics Approach to Medical Equipment Maintenance Management to Improve the Mean Time Between Failure and Availability

Design and construction of automated mechanical ventilation equipment to assist respiratory failure

This document presents the requirements met for the design, construction and first validation of a mechanical ventilation system to be used in patients with respiratory failure, which in the initial context was due to the COVID-19 pandemic. The design required the use of computer aided drawing software (Computer Aided Design) CAD and the construction required the use of installed capabilities in mechanical, electropneumatic, electronic, biomedical and automation manufacturing of Don Bosco University (El Salvador) institutes and centers. The adjustment, configuration and programming works were in charge of research professors specialized in these disciplines. The elements used for its construction were available in the Salvadoran market, considering the closure of the borders as a government measure in face of the expansion of the pandemic. After the design, manufacture and commissioning stage, measurements of the conditions of the supplied air were made with the help of professionals dedicated to the maintenance of medical equipment and with the approval of internist doctors. The results achieved are those obtained with paramedical equipment and with first aid equipment, for which it has been foreseen that the equipment can be tested in a subsequent instance with the certified medical union.