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Prioritize Medical Equipment Replacement Using Analytical Hierarchy Process

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IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE) e-issn: ,p-ISSN: , Volume 10, Issue 3 Ver. II (May Jun. 2015), PP Prioritize Medical Equipment
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IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE) e-issn: ,p-ISSN: , Volume 10, Issue 3 Ver. II (May Jun. 2015), PP Prioritize Medical Equipment Replacement Using Analytical Hierarchy Process Mohammed Faisal1, Amr Sharawi2 1 (Biomedical Engineering and systems, Faculty of Engineering/ Cairo University, Egypt) 2 (Professor in Biomedical Engineering and systems, Faculty of Engineering/ Cairo University, Egypt) Abstract: Engineering Department in hospitals need to take decision for Health Care Technology assessment which includes purchase, maintenance, use, and replacement. In this paper we proposed a analytical hierarchy processes -group decision making (AHP-GDM) model to prioritize the medical equipment for replacement. The model structure includes 11 quantitative and qualitative factors descending as main and sub criteria which can affect of the replacement decision. Each device should be assessed with respect to every covering criterion.and the devices ranking with respect to the criteria independent of other devices. the final score for each devices was calculated as replacement priority index(rpi). the model was applied for 30 devices in ICU where devices with higher RPI take a higher priority for replacement according for available budget in hospital and Devices with lower RPI take a lower priority for replacement. This model can be integrated as an automated system for medical devices replacement in health care facilities. Keywords: AHP, Criteria, Replacement, Medical Equipment I. Introduction Advanced technology systems in hospitals requires high efforts of planning and management in purchase, maintenance, use and replacement or disposal, in order to Enables devices to do their functioning correctly to keep patient safety and prevents unexpected stop of devices would increase the downtime and maintenance repair cost.in order to enhancement customer clinical service and medical staff satisfaction. In Egyptian country, there is a lack of actual, scientific, and inclusive assessment of medical equipment replacement decision. This is to the fact that replacement decisions of medical equipment are mainly based on inadequate reliable information and poor analysis of relative costs, age and condition of equipment, utilization levels, expected future service provision and benefits from new technologies. There are few study proposed many techniques that have been developed to used for medical equipment replacement. most of these techniques only consider few factors, while several factors are difficult to considered. A simple model used to identify and ranking of medical equipment for replacement was developed [1] another method was proposed a medical equipment replacement score system (MERS) as automated system designed based on technical, safety and mission critical rules, where weight and score have been assigned for each criteria. final score was calculated where the device which has higher scores has a high priorities to replacement [2]. developed an automated software program was proposed to identify equipment need of replacement, the system designed based on the factual, safety, technical, financial criteria and Rules have been developed to assist which equipment should be replacement. which produces relative replacement number (RRN) for each device[3]. The fuzzy inference model was proposed to determined the equipment that need replace. The model considers both quantitative and quantitative factors that actually influence in replacement decisions[4]. Fault Tree analysis (FTA) proposed to model the replacement decisions based on a set of indicators include the hazards and alerts, vendor support, cost, and the useful life ratio that on the replacement decision. and the proposed model priority equipment that should be replaced [5]. In this paper we proposed a analytical hierarchy processes AHP model to prioritize the medical equipment for replacement [6]. The Analytic Hierarchy Process (AHP) consider as a multi-criteria decision making (MCDM) method, which is a flexible decision making tool for multiple criteria problems[6]. and its simplicity and its ability to deal with both quantitative and qualitative data[7]. The AHP is a decision support method that can be used to resolve the complicated problems decision. It consist of a hierarchical structure of objectives, main criteria, sub criteria, and alternatives. a set of pairwise comparisons are used to get the weights values of importance of criteria, and the relative measures were applied to compared to alternatives with each other criterion. if the comparisons are not exactly consistent, should be used the mathematical way for improving consistency. DOI: / Page There are several studies have proven the effectiveness AHP method in health technology assessment, cite some of them: apply AHP method to support of selecting neonatal ventilators during purchase procedure for a new women s health hospital. Where the model can be updated or adapted to different medical technologies whenever needed [8]. Another study explained use of AHP to support the quality assessment for the purchase of pacemakers and implantable defibrillators and prove that the method is actual more suitable for this procedure. the AHP model permit us for make evaluation it is reliable [9]. In [10] AHP model was proposed to prioritize medical devices according to the condition device in equipment management system in health care facilities. The model gives a actual evaluation of a total risk of the device by consideration of its different failure modes and evaluate their frequency, delectability and consequences,this strategy is simple to implement and can decrease the device failure rate. Also application of AHP to purchase a new CT scanner according of user demands for use in a health care facilities. the AHP method describe how was appropriate to enhancement its effectiveness for application in healthcare facilities. The study also has a wider effect for manufacturing of medical devices as it describes a precise and effective method to selection of user demands and to benefit of it during development of new devices [11]. The objective of this paper to develop heath care technology assessment,so we proposed AHP model for medical equipment replacement aims to enhancement heath care technology assessment in replacement processes, proposed model is ranking procedure for prioritizing criteria that may have for the replacement decisions of medical equipment that are in critical condition in a health care facilities to help the hospital administrative level management assessment in developed country. our model considers using two types of comparisons, relative and absolute measurements, and both quantitative and qualitative criteria, estimated in an objective method, for include many of the criteria that actually influence replacement decisions in the healthcare facilities. II. AHP Group Decision Making Aggregation Methods: The AHP Group Decision Making process use to combine the individual judgments in a group into a group's judgment and to construct a group preference from the individual preferences. Consider an AHP group decision making problem. Let K={β 1, β 2,..., β m } be the set of decision makers, and W={w 1, w 1,,..., w m } be the weight vector of m decision makers, where β k 0,k =1,2,...,m, k=1 β k =1 Let A k = (a k ij ) nxn be the judgment matrix provided by the decision maker d k (k=1,2,...,m). based on the above described, two most useful methods for AHP-group decision making can be used[12] [13] one of this method which be used in this paper the aggregation of individual judgments (AIJ), where in this method the decision makers use the weighted geometric mean method to aggregate individual judgement matrices to obtain a collective judgement matrix, A G = (a k ij ) nxn (1) where A G = (a G ij ) (2) G where a ij = m (a k ij ) β k k=1 (3) The Eigen value method (EVM) is : AV = λ max V ; e T V = 1; (4) Where A : the comparison matrix V : the priorities vector λ max : the maximal eigenvalue Then, using EVM to derive a collective priority vector w G = (w G 1, w G 2,, w G T n ) from A G to order the alternatives. the pairwise comparisons in a judgment matrix should be consistent,this happens when the the consistency ratio (CR) is less than 0.1[6]. The CR is give as the follows : CI CR = (5) RCI Where RCI the Random Consistency index value which given by saaty [6]. DOI: / Page And λ CI = max n n 1 Where λ max : the maximal eigenvalue, n : is the criteria number. (6) III. Methodology A. AHP Model Structure prioritization medical equipment for replacement consider as a multi criteria decision making( MCDM) problem and we use the Analytical Hierarchy Process (AHP) to solve it. The structure of our proposed AHP model consist of three steps: Step1: identified the goal which is prioritization of medical devices replacement. step2: evaluation of devices criteria which must be identified and placed at the second level of the hierarchy. Step 3: The alternatives (medical devices) placed in third level of the hierarchy structure. To assign a score value for every device included in a model, two type of comparison would be used : Relative measurement and absolute measurement method. Relative measurement method is applied for pairwise comparison each criterion with other criteria in order to determining their weights priority with respect to our goal (prioritization of medical equipment for replacement ). If we have large number of devices then, the pairwise comparison for all criteria seen as impossible. furthermore, medical equipment are added or removed from the database dynamically with over time. So,to resolve this problem, we used an absolute measurement method for ranking the medical equipment. Each device was compared with each criterion used for evaluation and assigning a score for each device, and give a device score corresponding to its description grade without comparing with other devices. The criterion description and associated grades should be defined advance. The grade are the expectation categories of a criterion. For example, the device function could be take one of the next categories : life support, diagnosis, treatment and analysis. The grades of description criterion are qualitative,so, should be assigned an score value denote to its importance with respect to the criterion. quantify the description grades an important step, to evaluation of device with respect to criterion by assigned the score of descriptive grade, which contribute in the prioritization of devices replacement in a model. we suggest to applied the relative measurement method for pairwise compare the description grades with respect to their criterion for obtain more accurate score values for the description grade of criterion. using this method it acceptable to avoid assigning arbitrary score for the device grade and give the more consistent scores values for devices. consequently each device is assessed independently of other devices, so each device grade should be assigned an score value indicating its importance with respect to the criterion. The devices are evaluation with each criterion and is assigned the suitable description grade which determined in the our model. After determine the description and score for all criteria, the proposed model is ready to evaluation the devices. where each device is compared for each criterion and determine their score value. The next steps show the summary of the proposed model : determine the effective and independent criteria and sub-criteria for evaluation devices. using relative measurement method to calculate the weights values for all criteria and sub-criteria. prepare description grades for each criterion and calculate their score value by using relative measurement method. the equipment are evaluation with respect to each criterion and is set the suitable score using absolute measurement method; Calculate the total score for each device as follows: m TS i = j=1 w i s ij =1 (7) TS i : is the total score for the i-th device. i =1,...,n, n : is the total number of devices. j =1,...,m, m is the number of criteria. w j is the weight of the-j criterion, and the s ij is the score value of the-i device with respect to the-j criterion, n Where w i = 1 j=1 Finally, Priority devices according to their total scores value. The proposed hierarchy structure contains of seven criteria are identified at the top level, where Some of these divided to sub-criteria.the hierarchy structure for prioritization of medical equipment replacement shows in Figure.1 DOI: / Page Figure.1: Hierarchy Structure For Prioritization Devices Of Replacement B. Identification of Criteria : 1. availability(sa): availability is the more important indicator in develop country for replacement decision making.in our model proposed the vendor support criterion to include : a) Vendor support (VS) : This criterion include warranty, maintenance contracts, documentation, and training.the device can stay long time in service but then begin to reach the end of manufacturer service supported life and thus need to be replaced,devices that were no longer service supported should have highest priority for replacement. b) Alternative service support(ass): Reach the end of manufacturer service supported life Departments often prefer to keep existing equipment for back-up manufacturer support availability of spare parts can expand the usage of medical equipment a long time.where the parts availability indicator reflects Stop working of any medical equipment 2. Performance : There are many factor that indicator for equipment performance,in our model failure rate and efficiency coefficient used as a proposed indicator factors. a) Failure rate (FR): The Failure rate consider as a number of repairs per year,and it was calculated as a total number of repairs/(age of device(number of years being considered)) [3]. b) Efficiency coefficient(ce) : We defined Efficiency coefficient as EC = 1 2 t d t o ( 8) where t d is downtime, t o is operation time 3. Maintenance cost (MC) Maintenance cost is the total cost value of maintenance and repair for each device compared with its purchase cost. The maintenance costs over the past three years should not exceeding 25% of the purchase cost of a device [14]. 4. Age In our model this indicator criterion include the tow sub criteria : a) Device Age (DA) : The life span was identified for all equipment and compared to their actual age. b) Technology Age(TA) : Technology Age is the time period since the appearance of the device in market DOI: / Page 5. Equipment Function(EF) : The equipment function or application can have a high effect on decision replaced. Life support devices, regardless of need, always, classified as more important than the other devices in the replacement process. equipment function classified to the following categories: Life support devices, Therapeutic devices, Diagnostic devices and analytical support devices 6. Operation Operation describe the ability of a device in process of care delivery in hospital [15]. in our model Operation depends on usage rate (UR) and availability of similar or alternative devices. a) Backup Equipment (BE) : With decreasing the number of backup and similar equipment available in the hospital. The state of device in the delivery of health care becomes more critical, particularly When it is in a high level of use and there is no similar device in the hospital. Presence many similar devices does not mean high Backup Equipment, the request per unit time of these equipment is also significant. in case there were many similar equipment in a hospital but Using heavily, and if the device is fails, it has a less opportunity that others can be used as alternative. Therefore, Backup Equipment can be defined in term of the number of similar or backup equipment that required for per unit time. b) Usage Rate (UR) : The usage rate is the length time of device operating in hospital as the average of working hours (hours per day,days per week or weeks per year). we considered the average working device hours per day in our model. 7. : The (CA) criteria indicator for the medical staff satisfaction, where medical staff members need to using high new technological devices to improve the efficiency and the effectiveness performance. C. Weighting and scoring calculation for all Criteria The questionnaire was prepared to obtain the comparative matrics of all criteria for getting weight grade scores of alternatives(devices), Using saaty scale 1-9 to building pairwise comparative matrix [6]. we form a set of four decision makers working in this field where their chosen based on of their knowledge (clinical engineering, technicians, and physicians ). Each decision maker was made pairwise comparison matrices between main criteria was done to obtain the preferential degrees weights used a relative measurement method, this method also used to provide the preferential degrees weights for the sub criteria. and pairwise comparison matrices by using the Absolute measurement method was applied to prioritize devices replacement. Therefore, from each decision maker, we have one comparison matrix for main criteria weights in addition to four comparison matrices of the sub criteria,eleven comparison matrices for getting scoring for each criteria in model. therefore we became have four comparison matrices to main criteria and 16 comparison matrix to sub-criteria for priority weights, and 44 comparison metrics for all criteria in order to calculate the scoring for each criterion. Aggregation each Individual decision maker comparison matrices to get the group comparison matrix and then calculate the priorities weights and score value. this process done by used one of most useful methods for AHP-group decision making as we explained previous. D. Replacement Priority After calculate weights and score criteria based on previous methodology by using matlab program, now the model is ready to priority Alternative (devices). Each device should be evaluation with respect to all criterion, and assigned an suitable score. Finally, by apply Equation (1) we obtain the total score for each device,then normalization the total score value as a replacement priority index by use the follow equation: Score Value Minimum Value Normalization score value = (9) Max Value Minimum Value. IV. Results According to the AHP - Group Decision Making(AHP-GDM), we applying the aggregation of individual judgments( AIJ) method which was explain previously to calculate weights criteria as follow: Lets ( GI, GII, GIII and GIIII) the pairwise comparison matrices of the four group decision makers resulting of evaluation main criteria to get its weights priority. DOI: / Page Table.1 Pairwaise Comparative Matrix For Priorities Weights Performance Maintenance Age Function Operational Table.2 Pairwaise Comparative Matrix For Priorities Weights GII Performance Maintenance Age Function Operational Table 3 Pairwaise Comparative Matrix For Priorities Weights GIII Performance Maintenance Age Function Operational Table 4 Pairwaise Comparative Matrix For Priorities Weights GIIII Performance Maintenance Age Function Operational Then Aggregation the previous four comparison matrix By applying the weighted geometric mean method (WGMM) Equation (3) Where, β i the experts weights,we assign the equal weights for all expert where β 1 =0.25, β 2 =0.25, β 3 =0.25, β 4 =0.25. Then,from WGMM we get the Group comparative matrix as show in Table 5. Table 5 Group comparative matrix and priorities weights and Consistency ratio for main criteria Performance Maintenance Age Function Operational By applying the eigenvector method (EGVM) on the previous Group comparative matrix to obtain the group Judgments priorities weights. The weights resulting and Consistency index(cr) from this process are present in the Table.6. GI D
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