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Showing 5 results for Sepehri
Department of Industrial Engineering, Faculty of Engineering, Tarbiat Modares University, Tehran, Iran.
R Baradaran Kazemzadeh , M Sepehri , F Firouzi Jahantigh ,
Volume 12, Issue 4 (3-2014)
Abstract
Background and purpose: Hospital is the largest and most important executive unit of healthcare system therefore, full consideration of how to assess its quality is of particular importance. A question is always raised as how to evaluate the quality of the services. The current study seeks to provide a fuzzy model for assessing the service quality in this healthcare sector. Material and method: The present cross-sectional study was conducted in two hospitals in Zahedan 2012.Via reviewing the related literature, the dimensions and components of service quality assessment were identified. The SERVQUAL questionnaire for hierarchical analyses was designed and the fuzzy AHP (Analytical Hierarchy Process) model was presented. SPSS v 10.0 and Fuzzy TOPSIS Solver 2013 software were used to analyze data. Results: The findings indicated that the most important dimension for estimating the quality of healthcare services was empathy. Responsiveness, assurance, and tangible assets were the last important factors. The hospitals were compared using fuzzy AHP. According to the calculations, the ranking of the hospitals based on their performance was as follows: Imam Ali hospital with 31% compared to Social Security hospital with 29% had a better performance in service quality. Conclusion: The results revealed that hospitals needed to focus more on empathy, expertise and reliability than providing high quality and satisfactory services. By considering their weaknesses, each of these hospitals can enhance service quality and consequently, provide a better service for patients.
Planning and Management of Patient Flow and Bed Capacities of Cardiac Ward with Mathematical Modeling and Discrete Event Simulation Approach
Master Science Mohsen Afsahi, Dr. Mohammad Mehdi Sepehri, Master Ehsan Ameri,
Volume 14, Issue 1 (6-2015)
Abstract

Background: Deciding on the number of hospital beds is one of the most serious challenges managers face. More hospital beds result in higher running cost although less hospital beds might cause disorder in patients flow.  Minimizing total cost besides maximizing the patients flow in a hospital network, considering the practical limitations is the main objective of this survey.

Materials & Methods: This study had main steps to investigate following: identifying current limitations of changing capacity of each ward, by conducting interview with hospital managers and other personnel of Modares hospital, analyzing cardiac patient flow analysis, simulating current flow, determining practical scenarios and choosing the best among them by mathematical modeling could minimize total cost and maximize patient flow.

Results: 31 practical scenarios have been determined and analyzed by surveying limitations among all existing scenarios. Finally, eight best scenarios had been selected. Results showed that decreasing the number of beds in CCU and increasing the number of beds in Post-CCU can improve patients flow, considering cost limitations.     

Conclusion: A recommended approach in this study can be a general guide for capacity planning with taking practical limitations into consideration. This survey could be useful for the managers who are against the benefits of post CCU  by comparing the patient flow with and without this ward.


Selecting Differentiated Costs between primary PCI and Thrombolytic Therapy using Hybrid of Genetic Algorithm and Decision Tree Approach
Masoumeh Saeedian, Mohammadmehdi Sepehri, Hassan Aghajani, Toktam Khatibi,
Volume 14, Issue 3 (9-2015)
Abstract

Background: Myocardial Infarction (MI) is the most common cause of death in developed and developing countries. Based on World Health Organization prediction, MI will be the leading cause of death in the world up to 2020. The main goal of acute myocardial infarction therapy is reperfusion which is performed by two treatment approaches, although these two methods use for unique complication treatment but they are different in treatment cost and quality; Since the costs of health care is growing, this study aimed at identifying affected differentiated costs among patients with acute MI with the purpose of providing a framework to compare two treatment methods.

Materials and Methods: In presented model in current study, with the purpose of select affecting cost attributes utilized hybrid of Genetic algorithm and decision tree approach as a new method and compare its result using random method.

Results: Study result presented classifies error reduction up to 0.2 compare with random method error. Then, based on selected attributes, presented a framework comparing two treatment methods. Also, in the majority of direct cost and total cost, Primary Angioplasty was cost effective more than Thrombolytic Therapy, but in indirect cost, we achieved some results dissimilar to physicians' expected results such as kidney failure.

Conclusion: Suggested approach in this research can be a guidance to physicians and insurances institutes in acute myocardial infarction treatment policies.


A Developed Method for Handling Uncertainty in Activity - Based Costing for Hospital Services Using Fuzzy Approach
Dr Bakhtiar Ostadi, Reza Mokhtarian Daloie, Dr Mohamad Mahdi Sepehri,
Volume 17, Issue 4 (2-2019)
Abstract
Background: Today, hospitals have faced many requests for quality services, while their costs are increasingly growing as well. These facts; Therefore, necessitate much more attention from hospital mangers in order to reduce healthcare costs. Moreover, the urgent need for a precise costing approach is more evident. Activity-based costing provides useful information on the activities required to achieve services with desirable quality. However, given that the basic information for ABC system is provided under conditions of certainty, the possibility of using this approach in terms of uncertainty would be greatly decreased. This study aims to propose a new framework called FL-ABC.
Materials and Methods: Since, costing processes environment happen under conditions of uncertainty in the hospital, fuzzy logic in the ABC model was used in order to make more accurate estimates of hospital costs and increase the reliability of the results.
Results: This proposed model was used in a hospital lab unit and the results were compared with the standard ABC system. The results showed that the maximum difference in the prescribed costs was 77708951.89 and 67508112.57 IRR in serology and parasitology tests, respectively, mostly due to uncertainty in the assigned costs to each activity.
Conclusion: The FL-ABC system, in terms of taking into account the uncertainty in the parameters of cost, provides more accurate estimates of the cost of activities under conditions of uncertainty which estimates the costs of health care services more accurately.

A Clustering model for gadgets and apps used in patient monitoring in HIOT environment
Mohssen Ghanavatinejad, Mahdieh Tavakoli, Dr Mohamadmehdi Sepehri,
Volume 18, Issue 3 (10-2019)
Abstract 
Background: with increasing demand for treatment, patients are monitored with help of Internet of Things(IOT). Patient's monitoring devices and technologies include heart rate measurement, blood pressure measurement, blood glucose and other vital signs. The purpose of study is to provide a model of clustering patient physical monitoring gadgets and apps in Healthcare Internet of Things (HIOT) environment using data mining techniques, so based on the needs and characteristics of the user, the more appropriate results of choosing technologies acquired.
Materials and methods: This study is a review and functional since its result. The data includes 6 unique features of 60 selected technologies including function, price, connectivity route, power supply, location and type of use that has been extracted from R&D and advertising sites of technologies and also relevant articles. data analysis method is clustering technique and K-medoids algorithm. to identify the most effective features, random forest algorithm has been used.
Results: the proposed clustering model takes into account 6 as inputs and clusters gadgets and apps in accordance with selected characteristics as the model outputs. clustering problem data is clustered in 4 categories.  Silhouette index is 0.45, which indicates the validity of the model. The type of application and then the price had the greatest impact on clustering.
Conclusion: By this model, patients or users can find the most appropriate technology based on the type of disease and other effective features, such as price. So with accurate physical and momentary monitoring, disease progression decrease and prevention of disease will improve.

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