Zahra Shavandi; Seyed Mojtaba Sajadi; Roya Siolatan
Abstract
Introduction: One of the major indicators for evaluating the quality of services in medical centers is the waiting time for patients. If the treatment process is prolonged, it can give rise the patients to leave the system before the end of the treatment process and with personal consent. The purpose ...
Read More
Introduction: One of the major indicators for evaluating the quality of services in medical centers is the waiting time for patients. If the treatment process is prolonged, it can give rise the patients to leave the system before the end of the treatment process and with personal consent. The purpose of this research was to evaluate the service process of a treatment center and improve the treatment process through discrete-event simulation to reduce patient waiting time and reduce the number of patients with discharging by personal satisfaction despite the doctor's advice (DAMA: Discharged against Medical Advice).Methods: This was a descriptive study involving patients referred to Khatam Al-Anbia hospital in Tehran, Iran, in the fall of 2018. Data collection tools were as questionnaires, and face-to-face and telephone interviews with experts and researchers. Content for data collection formats included the patient's arrival time, and the start and end time of receiving services in various departments and units. In the next step, the data were modeled, different scenarios were analyzed, and the best scenario was selected from them.Results: In the seven proposed studied scenarios, the seventh scenario, which was a combination of the other six proposed scenarios, improved the treatment system. In this scenario, it was observed that the cost of value added with a slight increase from 399807373 in the initial model to 401561100 in the seventh scenario, with a significant decrease in the waiting cost from 2494256 currency units in the initial model to 16472202 currency units in the seventh scenario. Other proposed scenarios were more effective in reducing the total cost, from 649228933 monetary units in the initial model to 418033302 monetary units in the seventh scenario, which ultimately led to proper classification of workflow and improvement of performance indicators studied.Conclusion: The results reveal that by changing the resources and beds allocated to patients (optimal amount), it is possible to provide better services to patients, eliminate their dissatisfaction, and reduce the number of DAMA patients, waiting time of patients, and the losses in the service process.
Ahmad Kamali; Seyed Mojtaba Sajjadi; Fariborz jolai
Abstract
Introduction: Decision making about the location of emergency medical centers, to facilitate quick respond to requests for emergency medical services, is a complex issue for managers of emergency medical services. This research aimed to reduce the response time to emergency medical services requests, ...
Read More
Introduction: Decision making about the location of emergency medical centers, to facilitate quick respond to requests for emergency medical services, is a complex issue for managers of emergency medical services. This research aimed to reduce the response time to emergency medical services requests, using a combination of optimization and simulation methods for placement of emergency bases.Methods: This was a descriptive research. A number of locations in the districts one, three, five, and six of Isfahan City, Iran, were defined as the locations of emergency medical bases, according to criteria such as population density, and the rate of request calls for emergency medical services. Then, the final locations of bases were determined among these possible locations. After determining factors such as the impact of traffic conditions on response time, demand rate, and operating costs, different scenarios were analyzed using Arena software, and the best scenario was selected.Results: The mean time of response to emergency requests reached nine minutes, with the implementation of the selected scenario, which was close to the international standard of eight minutes.Conclusion: The results of this research show that without spending a lot of money to create and equip additional bases, different requests can be answered in the shortest possible time. The method presented in this study can be used to solve placement problems of other emergency services such as firefighting stations.
Abbas Maleki; Seyed Mojtaba Sajadi; Babak Rezaee
Volume 11, Issue 1 , May 2014, , Pages 4-16
Abstract
Introduction: Local emergency ward is designated to provision of treatment services for patients which is closely related to salvaging people’s lives. The main purpose is to apply simulation and improved treatment process procedure for appropriate designation of environment, resources and funds ...
Read More
Introduction: Local emergency ward is designated to provision of treatment services for patients which is closely related to salvaging people’s lives. The main purpose is to apply simulation and improved treatment process procedure for appropriate designation of environment, resources and funds in the emergency ward and improvement of functional indexes. Methods: This is an applied-developmental study conducted during a one month period in 2012 on the patients referring to the emergency ward of Arak hospital and all the data were gathered through either observations or questionnaires consistent with the format of the Ministry of Healthcare. Both face content validity and stability of data were determined using the 93percent Cronbach's alpha factor. Non-probability purposive sampling is carried out with no prototypes to the number of 70350 case. The data analysis was conducted via Easy Fit software whereas simulation modeling was performed through Arena software. Results: Four different scenarios were simulated in this study using the Arena software, the results of which are presented both quantitatively and comparatively with respect to the functional indexes. The first scenario is considered as the prototype with a cost index of nearly 44 million units of of money and 37 percent care in the resuscitation ward, according to which the other three scenarios were designed and conducted. Conclusion: The results of this research show that the improved model would lead to more appropriate classification of work procedure and improvement of functional indexes in an emergency ward as compared with the previous model. Also, appropriate alteration in the number of resources and beds may improve the provision of services to the patients and resolve their dissatisfactions. Keywords: Computer Simulation; Emergency Department; Treatment
