A method to select the best maintenance strategy for critical devices is proposed.The method proposes a risk-based framework including experts' opinions.The proposed approach handles both qualitative and quantitative data.Existing criteria related to prioritization of medical devices have been revisited.New relevant criteria have been defined. Medical equipment such as infant incubator, infusion pump, CT scanner, etc. should be maintained properly to meet adequate standards of reliability in healthcare services. This paper proposes a new comprehensive risk-based prioritization framework for selecting the best maintenance strategy. The framework encompasses three steps. In the first step, a fuzzy failure modes and effects analysis (FFMEA) method is applied by considering several risk assessment factors. In the second step, seven miscellaneous dimensions such as use-related hazards, age, and utilization are applied to consider all aspects of hazards and risks in prioritization of medical devices. Finally, a simple method is introduced in the third step in order to find the most suitable maintenance strategy for each device according to the scores produced by the previous steps. A numerical example illustrates the proposed approach and shows that, through the method introduced in this paper, managers can easily classify medical devices for maintenance activities according to their criticality scores. Implementation of this framework could increase the availability of high risk machines in healthcare industries. Moreover, this framework can be applied in other critical industries such as aviation by modifying some criteria and dimensions.

A comprehensive fuzzy risk-based maintenance framework for prioritization of medical devices

Blind source separation assumes that the acquired signal is composed of a weighted sum of a number of basic components corresponding to a number of limited sources. This work poses the problem of ECG signal diagnosis in the form of a blind source separation problem. In particular, a large number of ECG signals undergo two of the most commonly used blind source separation techniques, namely, principal component analysis (PCA) and independent component analysis (ICA), so that the basic components underlying this complex signal can be identified. Given that such techniques are sensitive to signal shift, a simple transformation is used that computes the magnitude of the Fourier transformation of ECG signals. This allows the phase components corresponding to such shifts to be removed. Using the magnitude of the projection of a given ECG signal onto these basic components as features, it was shown that accurate arrhythmia detection and classification were possible. The proposed strategies were applied to a large number of independent 3s intervals of ECG signals consisting of 320 training samples and 160 test samples from the MIT-BIH database. The samples equally represent five different ECG signal types, including normal, ventricular couplet, ventricular tachycardia, ventricular bigeminy and ventricular fibrillation. The intervals analysed were windowed using either a rectangular or a Hamming window. The methods demonstrated a detection rate of sensitivity 98% at specificity of 100% using nearest neighbour classification of features from ICA and a rectangular window. Lower classification rates were obtained using the same classifier with features from either PCA or ICA and a rectangular window. The results demonstrate the potential of the new method for clinical use.

Characterisation of electrocardiogram signals based on blind source separation.

Preprocessing stage for denoising is a crucial task in image analysis in general, and in computer-aided diagnosis using medical images in particular. Standard acquisition of Magnetic Resonance Images MRI presents statistical Rician noise which degrades the performance of the image analysis. This paper presents a new technique to reduce Rician noise of brain MRI. The new method for noise filtering is achieved in the discrete Wavelet Packets Transform WPT domain. Four methodologies for thresholding the detail coefficients in the same 2D WPT domain have been experimented considering two scenarios with and without a previous adaptive Wiener filtering in the spatial domain. Best quantitative and qualitative results have been obtained by the new method presented in this work specifically tailored for brain MRI, which is adaptive to each subband and dependent on the data. It has been compared with other traditional methods considering the Signal to Noise Ratio SNR, Normalized Cross Correlation NCC and execution time ∼ 0.1 s/slice. A complete dataset of structural T1-w brain MRI of the BrainWeb database has been used for experiments. An important aspect is that these experiments with synthetic images proved that the common prior adaptive Wiener filtering often used by many authors is a dispensable procedure.

Rician noise attenuation in the wavelet packet transformed domain for brain MRI

Operations research (OR) is a discipline that uses advanced analytical methods (e.g. simulation, optimisation, decision analysis) to better understand complex systems and aid in decision-making. Herein, we present a scoping review of the use of OR to analyse issues in global health, with an emphasis on health equity and research impact. A systematic search of five databases was designed to identify relevant published literature. A global overview of 1099 studies highlights the geographic distribution of OR and common OR methods used. From this collection of literature, a narrative description of the use of OR across four main application areas of global health – health systems and operations, clinical medicine, public health and health innovation – is also presented. The theme of health equity is then explored in detail through a subset of 44 studies. Health equity is a critical element of global health that cuts across all four application areas, and is an issue particularly amenable to analysis through OR. Finally, we present seven select cases of OR analyses that have been implemented or have influenced decision-making in global health policy or practice. Based on these cases, we identify three key drivers for success in bridging the gap between OR and global health policy, namely international collaboration with stakeholders, use of contextually appropriate data, and varied communication outlets for research findings. Such cases, however, represent a very small proportion of the literature found. Poor availability of representative and quality data, and a lack of collaboration between those who develop OR models and stakeholders in the contexts where OR analyses are intended to serve, were found to be common challenges for effective OR modelling in global health.

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Operations research in global health: a scoping review with a focus on the themes of health equity and impact.

Aim:To assess how the adjacencies of functionally different areas within operating rooms (ORs) can influence the circulating nurse’s (CN) workflow patterns and disruptionsBackground:The CN plays a

The Impact of Operating Room Layout on Circulating Nurse’s Work Patterns and Flow Disruptions: A Behavioral Mapping Study:

Operating theatre (OT) is one of the most critical departments within the hospital. In developing countries, no allocation of sufficient areas for OT, that results in sharing of many services in the same area while ignoring others. Facilities layout planning (FLP) is widely used in industrial engineering for designing block layout plans as it considers the assignment of services to the proper locations. Hence, FLP can solve management and hospital design problems, reduce nursing staff effort and improve overall healthcare environment. The problem presented in this study is an optimization one, which maximizes the subjective closeness rating between different services in the OT considering international standards. Some heuristic approaches have been developed for solving FLP problem; the most successful were based on graph theoretic concepts. This paper proposes a solution by generating an OT layout design based on the graph theoretic approach. It is divided into two sub-problems; the first one is the adjacency problem that defines the desirability of locating pair of spaces adjacent to each other. The second one is the block layout problem which was solved by using manual traditional qualitative technique (the spiral technique). The output of the technique was several possible designs and a layout score that was calculated for each design. This allows for selecting the most appropriate design for each end user. Computing the layout score, before and after reallocation of the OT spaces, resulted in an increase by 18.5% in the first hospital. For the second hospital, more services had to be added in addition to the reallocation process, this resulted in an increase in the layout score by 45%.

Improving operating theatre design using facilities layout planning

In developing countries, hospitals often suffer from insufficient funds and the lack of qualified technical personnel. This leads to a number of problems, among which is the improper and irregular maintenance of medical equipment. This situation calls for an effective approach to prioritize maintenance jobs based on certain importance criteria to make the best use of the available budget. In this article, we adopt the notion that medical equipment maintenance should be prioritized based on their risk level. Existing risk classification models express risk in terms of equipment function, maintenance requirements, and physical risk. They overlook other important factors such as the operational conditions of equipment. Other models have failed to classify critical devices as high risk because they did not incorporate the criticality of equipment as part of the global mission of the hospital. We argue that because hospitals in developing countries rarely implement coherent management standards, same level-of-care hospitals are not technologically equal. This research proposes a new risk assessment model based on fuzzy logic. Because fuzzy logic is closer to the human way of thinking, it is expected to improve the way devices are prioritized. The proposed model was tested on 136 different medical devices in 4 hospitals. Results show that, in certain cases, the same equipment type may have different risk scores depending on the operating conditions within the hospital. Meanwhile, some mission-critical equipment such as steam sterilizers, electrosurgical units, and hematology analyzers attain higher risk levels than obtained by existing models. We attribute this improvement to the fact that risk scores are now dynamic rather than static.

A Fuzzy Logic Model for Medical Equipment Risk Classification

Along the medical equipment life cycle, hospitals need to take decisions on medical equipment acquisition, maintenance, use and replacement on the basis of complete and reliable information. In this paper, the authors focus on the replacement criteria in developing countries where there is a lack of scientific, realistic and comprehensive assessment. In the proposed model, we use Fault Tree analysis (FTA) to model the replacement process using a set of indicators that impact directly or indirectly the replacement decision. We include the vendor support as a fundamental technical indicator in the analysis. This model considers the replacement decision as a final and undesirable event. Using probability theory, the medical equipment status is classified into 4 groups. According to the final event score, the replacement decision is approved or not. Neonatal Intensive Care Unit (NICU) equipment of 8 different types, along three years, are utilized to investigate the proposed model. Our model proposes a priority list of equipment that should be replaced. The type and number of equipment to be purchased is determined according to the available budget. The results show that 15% of equipment should be replaced, 33% need to be tested, 33% are under surveillance and 19% could be maintained.

A simple quantitative model for replacement of medical equipment proposed to developing countries

Medical equipment management life cycle considers various stages ranging from planning to disposal or replacement Replacement decision is critical and essential stage of medical equipment A variety of criteria contributes to make an intelligent replacement decision We enhance the Fault Tree Analysis (FTA) model for replacement of medical equipment, considering a combination of technical, financial, and safety criteria The considered criteria are; hazard and alerts, cost, useful life, and vendor support Throughout this model, we classify medical equipment life status into four groups; replacement, test, surveillance and keep According to the final event score, the replacement decision is approved or not Neonatal Intensive Care Unit (NICU) equipment of 12 different types for 3 hospitals, along three years, is utilized to investigate the proposed model Our model proposes a priority list of equipment that should be replaced According to the analysis to the proposed factors, the useful life factor is found to be the dominant factor In addition, a high correlation between vendor performance and expended costs is realized

The effect of useful life and vendor performance on replacement decision of medical equipment

Clinical Engineering (CE) department activities include acquisition, maintenance of medical instrumentation, health technology assessment, medical informatics, and risk management In this work the authors focus on maintenance activities in developing countries where there is a lack of acquisition planning, assessment, budgeting planning, and critical equipment breakdown In the past decade there has been an explosion in the use of system dynamics modeling in healthcare In this paper a system dynamics based model for medical equipment maintenance is designed; it incorporates 8 key variables that influence the progress of medical equipment maintenance This model shows the effect of changing a key variable on the others This model is intended to maximize the quality and to minimize the cost and time of medical equipment maintenance This is developed in a causal loop diagram, which is a cause and effect diagram iThink software has been used in the development of this model, together with vensim in the development of the causal loop diagram The results show that the critical variables for maintenance are the defect rate, breakdown rate, and maintenance cost In conclusion the medical equipment maintenance cost determines the decision for acquiring new equipment The type and number of equipment to be acquired is determined according to the available budget

Bassem K. Ouda

Papers

Improving operating theatre design using facilities layout planning

A Fuzzy Logic Model for Medical Equipment Risk Classification

A simple quantitative model for replacement of medical equipment proposed to developing countries

The effect of useful life and vendor performance on replacement decision of medical equipment

A system dynamics based model for medical equipment maintenance procedure planning in developing countries