Hierarchical Decision-making using a New Mathematical Model based on the Best-worst Method

Decision-making processes in different organizations often have a hierarchical and multilevel structure with various criteria and sub-criteria. The application of hierarchical decision-making has been increased in recent years in many different areas. Researchers have used different hierarchical decision-making methods through mathematical modeling. The best-worst method (BWM) is a multi-criteria evaluation methodology based on pairwise comparisons. In this paper, we introduce a new hierarchical BWM (HBWM) which consists of seven steps. In this new approach, the weights of the criteria and sub-criteria are obtained by using a novel integrated mathematical model. To analyze the proposed model, two numerical examples are provided. To show the performance of the introduced approach, a comparison is also made between the results of the HBWM and BWM methodologies. The analysis demonstrates that HBWM can effectively determine the weights of criteria and sub-criteria through an integrated model

Anaplastic Kinase-Positive Large T-cell Lymphoma Simultaneous with Tuberculosis in a Child: a Case Report

Anaplastic lymphoma kinase-positive (ALK+) large T-cell lymphoma (ALCL) is a rare type of lymphoma and it involves lymph nodes, but in some rare situations, it involves lungs, firstly. There are very rare cases in the world that have this type of disorder complicated with tuberculosis (TB). In this report, we present a boy who was referred to our hospital with TB and ALK+ALCL

Hierarchical Decision-making using a New Mathematical Model based on the Best-worst Method

Decision-making processes in different organizations often have a hierarchical and multilevel structure with various criteria and sub-criteria. The application of hierarchical decision-making has been increased in recent years in many different areas. Researchers have used different hierarchical decision-making methods through mathematical modeling. The best-worst method (BWM) is a multi-criteria evaluation methodology based on pairwise comparisons. In this paper, we introduce a new hierarchical BWM (HBWM) which consists of seven steps. In this new approach, the weights of the criteria and sub-criteria are obtained by using a novel integrated mathematical model. To analyze the proposed model, two numerical examples are provided. To show the performance of the introduced approach, a comparison is also made between the results of the HBWM and BWM methodologies. The analysis demonstrates that HBWM can effectively determine the weights of criteria and sub-criteria through an integrated model

A novel DEA model for hospital performance evaluation based on the measurement of efficiency, effectiveness and productivity

Hospitals are the most important and costly component of the healthcare system. Therefore, hospital performance evaluation (HPE) is an important issue for the managers of these centres. This paper presents a new approach for HPE that can be used to calculate the efficiency, effectiveness, and productivity of hospitals simultaneously. Efficiency refers to the ratio of inputs and outputs, effectiveness refers to the extent to which outputs align with predetermined goals, and productivity refers to the sum of both efficiency and effectiveness. To this end, a Data Envelopment Analysis (DEA) model is developed to simultaneously measure the efficiency, effectiveness, and productivity (DEA-EEP) of hospitals. DEA is a linear programming technique that in its traditional form, calculates the performance of similar decisionmaking units (DMUs) that have both inputs and outputs. In this study, the inputs are the number of health workers, the number of other staff, and the number of patient beds; while the outputs are the bed occupancy rate and the bed turnover rate. A target value is set for each output to measure the effectiveness of hospitals. The advantage of the developed model is the ability to provide a solution for non-productive units so that they can improve their performance by changing their inputs and outputs. In the case study, data of 11 hospitals in Tehran were evaluated for a 3-year period. Based on the results, some hospitals experienced an upward trend in the period, but the efficiency, effectiveness, and productivity scores of most hospitals fluctuated and did not have a growing trend. This indicates that although most hospitals sought to improve the quality of their services, they needed to take more serious steps

A novel DEA model for hospital performance evaluation based on the measurement of efficiency, effectiveness, and productivity

Hospitals are the most important and costly component of the healthcare system. Therefore, hospital performance evaluation (HPE) is an important issue for the managers of these centres. This paper presents a new approach for HPE that can be used to calculate the efficiency, effectiveness, and productivity of hospitals simultaneously. Efficiency refers to the ratio of inputs and outputs, effectiveness refers to the extent to which outputs align with predetermined goals, and productivity refers to the sum of both efficiency and effectiveness. To this end, a Data Envelopment Analysis (DEA) model is developed to simultaneously measure the efficiency, effectiveness, and productivity (DEA-EEP) of hospitals. DEA is a linear programming technique that in its traditional form, calculates the performance of similar decision-making units (DMUs) that have both inputs and outputs. In this study, the inputs are the number of health workers, the number of other staff, and the number of patient beds; while the outputs are the bed occupancy rate and the bed turnover rate. A target value is set for each output to measure the effectiveness of hospitals. The advantage of the developed model is the ability to provide a solution for non-productive units so that they can improve their performance by changing their inputs and outputs. In the case study, data of 11 hospitals in Tehran were evaluated for a 3-year period. Based on the results, some hospitals experienced an upward trend in the period, but the efficiency, effectiveness, and productivity scores of most hospitals fluctuated and did not have a growing trend. This indicates that although most hospitals sought to improve the quality of their services, they needed to take more serious steps

Effect of Polyvinyl Siloxane Viscosity on Accuracy of Dental Implant Impressions

Objectives: The aim of this study was to compare the accuracy of dental implant impressions obtained by a combination of different impression techniques and viscosities of polyvinyl siloxane (PVS). Materials and Methods: Four parallel fixtures were placed between mental foramina in a master model of lower dental arch. Three different viscosities (putty/light body, medium body/light body, and monophase: heavy body) and direct and indirect techniques (six groups) were used, and seven impressions were obtained from each group (n=42). To measure the accuracy of impressions, drift, horizontal, and vertical angles of the implants, as well as the hex rotation of the implants in casts were evaluated using a digitizer device (1μm accuracy), in comparison with master arch. Data were analyzed using five-factor two-way ANOVA and Tukey’s post-hoc test. Results: The accuracy of impressions was assessed and the results showed that direct technique was not significantly different from indirect technique (P>0.05). Also, there were no significant differences between the mentioned viscosities except for the horizontal angle (P=0.006). Conclusions: Viscosity of impression materials is of high significance for the accuracy of dental impressions.