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Topic | Technique/area of concern | Geographic area | Medical device | Articles/year | Outcomes | Research gap/future work |
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Risk management (prioritization) | Fuzzy AHP | Portugal | Five selected medical devices | [42]/2020 | Priority for renewing medical device categorized to low, medium, high and urgent for replacement | Only selected medical devices are included, and the most significant criteria are not specified. |
Limited no. of age in service |
RCM | Malaysia | Medical device | [43]/2019 | Breakdown factors are divided into three which is maintenance services type, environmental and human factors | RCM method is widely used but requires sufficient data to complete the process |
Mathematical model | Mexico | 16 selected medical devices | [44]/2020 | The result determines the annual number and priority for PM. Type of equipment (highest priority), location (lowest priority) | The model applies to selected 16 medical devices |
South Africa | Infusion pump and ventilator | [20]/2013 | The findings conclude age does not affect the survival of equipment due to the limited number of 5 years in service | Limited data for ventilators and only five years in age. |
Model not possible to be analysed to other devices due to insufficient data |
United States, France | Medical device | [14]/2010 | Biomedical equipment is classified into the high, medium, and low category | Current maintenance strategies are effective but lack the evidence of being efficient |
AHP | Jakarta | Medical device | [12]/2019 | The highest maintenance priority is an excimer laser, followed by a retinal laser and others | The most significant parameters which influence the result is not specified |
Canada | Medical device | [45]/2011 | Maintenance is prioritized with scores. Higher score for high priority in maintenance management program | A higher score requires further investigation |
Logistic regression predictor model | Romania | Three selected medical devices | [46]/2017 | Maintenance intervals are prioritized and developed based on risk group from low to high | No standard exists for assessing risk, and the tool uses current practices to establish a baseline |
AHP, TOPSIS, and MILP | Tunisia, Africa | Medical device | [47]/2017 | The maintenance strategies framework is developed and divided into time-based, condition-based and corrective maintenance | The framework shall be enhanced to a mathematical model |
PVST | Istanbul, Turkey | 16 selected medical devices | [6]/2016 | The preventive maintenance schedule is developed for older technology and predictive maintenance for newer technology | A future study is required to investigate failures of other medical devices excluded from this study. |
QFD | Italy | Four selected medical devices | [48], | A comprehensive framework for PM priority is developed. The most important criteria are function, maintenance requirement, and others | Data was collected in 2012. The framework is tested only once during scheduled PM. |
[49]/2015 |
Risk management (failure and risk analysis) | FFMEA | India | Ventilator | [50]/2020 | Nine failure modes for ventilators are ranked based on the risk criteria from remote, low to very high | Application of fuzzy FMEA limited to ventilator |
Budapest, Hungary | Medical device | [51]/2016 | Comparison between FMEA and FFMEA technique concludes FMEA is more accurate by involving different expert impacts weights | Difficulties in collecting each expert opinion for each risk as to the number of risks increases |
Canada | Five selected medical devices | [52]/2015 | Framework for prioritization and budget allocation for maintenance are developed. A maintenance strategy is proposed from low to very high priority | Development of a risk-based maintenance software based on the suggested comprehensive framework |
Six sigma, Pareto analysis | India | Ventilator | [53]/2020 | Common failures are identified, which are flow sensor, expiratory valve, calibration, battery, display and oxygen sensor | Automated real-time proactive RCA shall be enhanced to prevent failures |
RCM and FMEA | United Arab Emirates | Four selected medical devices | [54]/2020 | Results examine the relationship between the current practice of PM, failure mode, and RCM action is identified based on failure modes | Failure data for only 1 year. |
Lack of maintenance cost data and limitation to run RCM pilot project in the hospital |
FMEA, Pareto analysis and 5 whys | Kenya, Belgium | Three selected medical devices | [55]/2018 | Daily, weekly, monthly tasks and maintenance protocols are developed based on the failures identified | Only focuses on cobalt-60 radiotherapy machines and limitations to evaluate the effectiveness of proposed strategies on operation and maintenance |
FMEA | Italy | Medical device | [56]/2015 | One leading company in the development of medical devices is selected, and the process/risk connected to the design of new devices are evaluated | Technique shall be applied to other leading companies and develop a more manageable approach to overcome FMEA limitation |
Sierra Leonne, Africa | Anesthesia machine | [57]/2014 | Five failures mode are identified, which are resource availability, environmental, staff knowledge and attitudes, workload, and staffing | The sample size is small, with only two hospitals involved, and it is not convincing whether the findings are applicable to other settings |
China | Medical device | [58]/2014 | Potential failures in human reliability of medical devices are evaluated with numerical values of risk factors | Propose to apply the model to different medical device design |
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Performance prediction for medical device using machine learning | Machine learning (artificial neural network and fuzzy logic classifier) | Sarajevo, Bosnia, and Herzegovina | Infant incubator | [29]/2020 | Performance is predicted, and decision tree has the best properties compared to the other four algorithms with 98.5% accuracy based on performance output error | Model is applicable for infant incubators only with two years dataset period |
Machine learning (artificial neural network) | Sarajevo, Bosnia, and Herzegovina | Infusion and perfusor pumps | [31]/2020 | Feedforward neural network with ten neurons in a single hidden layer has an accuracy of 98.06% for perfusion pumps, 98.83% for infusion pumps, and 98.41% for both | Research shall be extended by introducing new parameters such as maintenance history and spare parts replacement to enhance accuracy |
Performance prediction for medical device using machine learning–cont’d | Machine learning | Bosnia and Herzegovina | Defibrillator | [32]/2019 | Performance is predicted, and random forest has the best properties compared to the other four algorithms with 100% accuracy | Model is applicable for defibrillator only with three years dataset period |
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Medical devices management system (MDMS) (marketing strategies) | AHP (questionnaire) | Iran | Medical device | [34]/2019 | Research on marketing strategies concludes most essential barriers are a managerial and strategic barrier | Fuzzy AHP technique shall be applied to examine the compatibility with human verbal and vague expressions |
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MDMS (management system) | Qualitative approach (interview) | Iran | Medical device | [4]/2019 | Factors influencing medical device management systems are categorized into seven themes (resources preventive maintenance, design, implementation, etc.), with 19 subthemes | The themes subjected for further research in Iran or other countries to improve quality |
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MDMS (service quality) | AHP | Iran | Medical device | [36]/2019 | 4 Iranian public hospitals are ranked based on four criteria to evaluate hospital service quality | More hospital selection would provide a better benchmark |
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MDMS (service quality) | Qualitative approach (questionnaire) | Ghana, West Africa | Medical device | [35]/2019 | Adequacy of healthcare resources is the most decisive factor compared to the other four service quality factors on patient satisfaction | Shall be enhanced to the district or regional hospital instead of a teaching hospital |
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MDMS (management system) | Literature review | Iran | Medical device | [8]/2018 | Eighty-nine factors affected medical equipment maintenance management: Resources, education, service, quality, inspection, etc. | Some factors overlapped with each other |
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MDMS (maintenance strategies) | MCDM | Morocco | Medical device | [2]/2018 | Maintenance strategies conclude risk (29%) as an essential criterion, followed by equipment function (14%). | Data collection is lacking and investigating external contributors such as heavy use and misuse and environmental factors on hidden failure event |
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MDMS (replacement plan) | — | Lebanon | 35 selected medical devices | [37]/2016 | A replacement plan is proposed with ranked criteria and sub-criteria depending on the urgency | Integration between hardware and software using Internet shall be executed to generate data on lifespan |
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MDMS (documentation) | — | Bangladesh | Ventilator | [59]/2015 | Risk factor reduction and standard operating procedure (SOP) is developed. Concludes lack of adequately educated, and trained clinical engineers to be solved | Service contract with vendors for maintenance shall be developed |
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MDMS (utilization and human resources) | Qualitative approach (questionnaire) | India | Diagnostic medical device | [10]/2015 | 23% of the devices are underutilised | The sample size was small and limited to diagnostic devices in the histopathology lab in 2012 |
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MDMS (quality assurance) | — | Bucharest, Romania | Radiant warmer, and infusion pump | [38]/2013 | Risk and score for both devices are addressed with five different criteria as guidance in managing quality assurance program | Limited to only two types of medical devices. Maintenance software in the database shall be developed |
MDMS (management system/Software) | — | Jordan | Medical device | [60]/2012 | Presents a software system (EQUI-MEDCOMP) using microsoft visual basic (version 6) designed to improve maintenance management | Parameters used in the dataset are limited to 5 factors; other factors shall also be considered |
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MDMS (quality control) | — | China | 9 selected medical devices | [39]/2010 | A six-dimension risk model is proposed, and a quality control system is established | Quality control shall be enhanced to more types of medical devices |
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