Medical Equipment Maintenance Research Articles

Medical Equipment Aging: Part III—An Aging Model for Maintenance and Replacement Plannings

The first article of this series demonstrated that some medical equipment exhibits clear, progressive deterioration with age, whereas some others do not. The second article showed that although most equipment remains safely and reliably deployed well over its respective depreciation period and the end-of-life or end-of-support dates declared by the respective manufacturers, some equipment needs to be replaced sooner. Because it is not practical to wait for the collection and analysis of large amounts of data to better plan for maintenance and replacement, a simple, quantitative model for equipment aging is introduced in this article to help improve both types of planning. The model was tested on professionals not directly involved in its formulation and applied to 34 equipment types. The results show this aging model can be used by professionals experienced in medical equipment maintenance and management, with only some basic instructions. Furthermore, it can be used to update the traditional “risk-based criteria” for planned maintenance and turning it into a risk management method fully compliant with the ISO 14971 standard.

Research on Construction of Knowledge Base for MRI Equipment Maintenance Based on Knowledge Graph

To improve the level of modern hospital management and establish a scientific and effective medical equipment maintenance guarantee system, this paper proposes the construction of a dynamic interactive fault repair knowledge base system for magnetic resonance imaging (MRI) equipment based on knowledge graph technology. This innovative application of intelligent management for large medical equipment involves collecting and organizing actual maintenance data. The paper constructs the medical equipment maintenance knowledge base, with MRI equipment as a case study, and initially implements functions such as fault information retrieval, technical guidance, and training and learning for MRI equipment. These functions aim to provide an objective decision-making basis for the maintenance and management of large medical equipment, enhance the efficiency of fault repair and maintenance, and elevate the construction level of intelligent hospitals.

АВТОМАТИЗАЦИЯ ПРОГНОЗИРОВАНИЯ НЕИСПРАВНОСТЕЙ МЕДТЕХНИКИ

The study identifies the problems faced by modern medical institutions, in particular, the Meditsina clinic. The management, maintenance, and user operation of medical devices cause these difficulties. To overcome them, it is necessary to revise the system of maintenance and repair of medical equipment, as well as to ensure continuous professional development of the employees responsible for the equipment operation. The paper proposes an information model that includes technical tools for forecasting, such as exponential smoothing. The authors create software implementa-tion of the information system and forecasting module based on the research; test these developments in the working conditions of the medical and preventive institution Meditsina. Thanks to the constructed forecast of the service life of the PHoX Plus analyzer parts, it is possible to adjust the purchase of consumables downwards.

Applying Microsoft Power Platform to Improve Primary Medical Equipment Maintenance Processes.

Post-COVID, our hospital shifted to online systems using Microsoft Power Platform to mitigate errors and delays. SharePoint and Power Apps manage equipment maintenance records and submissions, enhancing immediacy and transparency. Power Automate automates report generation and reminders, improving task completion rates. Power BI visualizes data for streamlined management. Adjustments to real-time reporting enhanced efficiency, reducing manual efforts and improving completion rates.

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.

Implementation of a Multicomponent Program to Improve Effective Use and Maintenance of Medical Equipment in Sri Lankan Hospitals

Abstract Background: Medical equipment (ME) maintenance retains an asset’s original anticipated useful life and preserves its reliability and cost-effectiveness. This study developed and implemented a multicomponent program to improve ME use and maintenance in nine Sri Lankan hospitals from May 2020 to May 2021. Methods: This pre–post implementation study involved an initial baseline assessment of existing ME maintenance systems, the development and implementation of a multicomponent improvement program, and a 3-month postevaluation. Five targets ME were selected for the study: oxygen regulator, electrocardiogram (ECG) machine, suction apparatus, blood pressure apparatus, and mini autoclave. A pretested questionnaire was administered to randomly selected nursing officers (n = 101) and health-care assistants (n = 120) to obtain baseline ME maintenance data. Six focus group discussions and 24 key informant interviews were conducted with key stakeholders to codesign the multicomponent interventions, which included: developing a standard operating procedure targeting preventive maintenance activities; establishing focal points to provide technical and logistic support; staff training; and the introduction of institutional ME maintenance documents. Program effectiveness was assessed at 3 months postimplementation using the seven predefined outcome variables. Results: Baseline assessment identified no ME maintenance programs implemented in any of the hospitals. The highest availability was observed for oxygen regulator (62% to 82.3%) and ECG machine (66.1% to 84.7%). The highest functionality improvement was observed for ECG machine (40.4% to 79.7%). The positive perception of maintenance process of ME achieved the highest (33% to 80%) improvement. Following program implementation, improvements were noted in: the availability (P = 0.00) and functionality (P = 0.00 to P = 0.02) of all selected ME; equipment maintenance processes (P = 0.000); as well as staff knowledge, skills, perceptions, and satisfaction. Conclusions: The program improved the use and maintenance of ME and was widely supported by the key stakeholders. The approach is relevant to other resource-poor hospital settings, as inadequate ME maintenance causes health system inefficiencies.

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.