فهرست مطالب

  • Volume:7 Issue: 2, 2018
  • تاریخ انتشار: 1397/02/11
  • تعداد عناوین: 8
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  • Masoumeh Saeedian, MohammadMehdi Sepehri *, Pejman Shadpour, Ammar Jalalimanesh, Sheida Hayatbakhsh Pages 1-20
    Background

    Operating room (OR) is one of the main hospital parts and management of time and cost are very important in this essential unit. Also, due to the close relationship with other departments, improving its service quality and performance, significantly increases the efficiency of hospital. OR is a complex system in which each lack of coordination effects on all hospital departments. So it is important to identify and categorize the factors that caused loss of OR orchestration and analyze the cost and delay times that imposed by this loss of orchestrations.

    Method

    Computer simulation is a useful technique for modelling system and its behavior. OR is a complex system which has lots of agents interacting with each other, so the agent based simulation method is a suitable technique for modelling OR agents, relationships, defining loss of orchestrations and analyzing the results on the system performance.

    Results

    By identifying OR non-orchestration factors, the most frequencies are related to the lack of recovery beds, emergency surgery, surgeon delay, lack of patient transferor, prolongation of other surgical procedures, anesthesia and pediatric surgery; and the less frequencies are for Clinical changes in the patient status, inadequate testing, and patient's cancellation or lack of readiness. Also, the most delayed and lost time were due to the inadequacy of patient tests, anesthesia and pediatric surgery, prolongation of other surgical procedures, and lack of recovery beds.

    Conclusion

    Surgery procedure is not just a surgical technique, but has many aspects that should be addressed and resolved. The results indicated that the most effective factor in hospital delay and costs is the shortage of resources and lack of planning, which can be improved by interconnecting communication and on-time information sharing.

    Keywords: Simulation, Operating room, delay time, Cost management
  • Measuring Performance, Estimating Most Productive Scale Size, and Benchmarking of Hospitals Using DEA Approach: A Case Study in Iran
    Pejman Peykani, Emran Mohammadi, Fatemeh Sadat Seyed Esmaeili Pages 21-41
    Background and Objectives

    The goal of current study is to evaluate the performance of hospitals and their departments. This manuscript aimed at estimation of the most productive scale size (MPSS), returns to scale (RTS), and benchmarking for inefficient hospitals and their departments.

    Methods

    The radial and non-radial data envelopment analysis (DEA) approaches under variable returns to scale (VRS) assumption are applied for performance assessment of hospitals. Also, the MPSS model in DEA is employed to identify hospital with optimal scale size. Furthermore, the benchmarking for inefficient decision making units (DMUs) is introduced using the slack based measure (SBM) model.

    Results

    In this manuscript, the DEA approaches are implemented at macro and micro levels in health care. At macro level, the performance of 15 Iranian hospitals is assessed and at micro level, the performance of 15 departments of one hospital is evaluated. It should be noted that the number of staff, the number of beds, location & infrastructures, and equipment & facilities were considered as the input variables and number of patients and number of surgeries were selected as output variables. According to the results, six hospitals at macro level and seven hospital departments at micro level were efficient. As a result, these hospitals and departments can be considered as a benchmark for other DMUs. Notably, only four hospitals at macro level and four hospital departments at micro level have the most productive scale size.

    Conclusions

    The current study presents a functional pattern to managers at macro and micro levels in health care systems to better planning for capacity development and resource saving.

    Keywords: Hospital Performance Evaluation, Data Envelopment Analysis (DEA), Health care, Most productive scale size (MPSS), Returns to Scale (RTS)
  • An Assessment of Chemotherapy Drugs with Incomplete Information using the Analytic Hierarchy Process and Choquet Integral
    Maryam Bagherifard, Nazanin Maleki, MohammadReza Gholamian* Pages 42-61
    Background and Objectives

    Obviously, cancer is one of the most prevalent deadly health problems that have seriously impacted societies. Although experts have been able to treat many patients, choosing the right therapeutic strategy and right medication for patients is still a challenge. Chemotherapy is one of the most common therapeutic strategies for cancer, which could be combined with radiotherapy or surgery. Since various chemotherapy drugs are available, depending on different criteria, oncologists may prescribe one chemotherapy medication or another.

    Methods

    Analytic Hierarchy Process (AHP) as one of the most effective decision-making methods, is applied in this paper. AHP relies on pairwise comparison matrix (PCM) that offers preferential relationships between alternatives. However, due to inaccurate and uncertain information, the revised geometric mean method (RGM) is applied in PCM. Also, considering the importance of interactions between criteria in the investigated issue, Choquet integral was employed for ranking alternatives.

    Findings

    Antimetabolites with weight 0.473868421 is the most preferred alternative. Plant alkaloids with weight 0.232740616, Alkylating agents with weight 0.17723893 and Anti-Tumor Antibiotics with weight 0.11819451, are alternative priorities for a chemotherapy drug, respectively.

    Conclusion

    In this paper, 10 questionnaires have been completed by oncologists in the hospital. According to the received results, Antimetabolites are the most preferred alternative among other chemotherapy drugs.

    Keywords: Multi-criteria decision making, Analytic Hierarchy Process, Revised geometric mean method, Choquet fuzzy integral, Chemotherapy
  • An augmented data envelopment analysis approach for designing a health service network
    Mahdyeh Shiri, Fardin Ahmadizar* Pages 62-80
    Background

    In the healthcare systems, health centers are taken into consideration as the most important sector due to providing health care services to people. In this respect, the assessing of this center is of great importance. Therefore, there is a need for a performance evaluation system to evaluate both efficiency and effectiveness of human resource, processes, and programs of health centers to improve the competitive power.

    Methods

     To measure the efficiency and productivity of Decision Making Units (DMUs), Data Envelopment Analysis (DEA), which is a nonparametric technique, is considered as the most common tool and can be applied to compare the performance of health centers. However, being DMUs homogenous is one of the underlying assumptions of DEA which prevent us from devising this technique because health centers provide different services, and thus, they are incommensurable. To overcome this barrier, a novel DEA technique is developed to select the best locations for health centers of Iran’s healthcare system.

    Results

    A practical case study, that is designing the health service network for urban residents’ health center (towns) in Fars province, is incorporated into the proposed technique. Finally, the candidate locations for health centers are ranked in terms of efficiency using novel DEA technique, and then, the sensitivity analysis is conducted on final results.

    Conclusion

     The obtained results imply the high performance of the proposed technique in the ranking of efficient health centers in health care systems. Moreover, this technique introduces a comprehensive performance evaluation tool for health centers and also aids managers and decision-makers to more accurately plan for selecting the best candidate location for health centers along with saving the resources.

    Keywords: Health service network design, Healthcare Systems, health centers, Data Envelopment Analysis
  • Evaluation of the Effect of Cognitive-behavioral Therapy on Adherence to Treatment and General Health in HIV Positive Patients.
    Bahram Mirzaeian, HamidReza Talebi, Yarali Doosti Pages 81-93

    The aim of this study was to evaluate the effect of cognitive-behavioral therapy on adherence to treatment and general health of HIV positive patients. In a quasi-experimental design, 30 HIV positive patients referred to Imam Khomeini Hospital for treatment were randomly selected, and then, they were randomly assigned into two groups of the experiment (n = 15) and control (n = 15). Pre-test was performed for both groups before intervention. The experimental group received 12 sessions of cognitive-behavioral therapy, 1 session per week, but the control group did not receive any intervention. Then, both groups completed post-test and finally, both groups completed the research questionnaires after 3 months (3 months follow-up). Data were collected using the General Health Questionnaire (GHQ 28) and Modanlou Adherence to Treatment Questionnaire. The collected data were analyzed by covariance analysis. The results showed a significant difference between experimental and control groups in terms of adherence to treatment and general health in the pre-test, post-test and follow-up stages (P <0.05). The results of this study suggest that cognitive-behavioral therapy can improve adherence to treatment and general health in HIV positive patients.

    Keywords: HIV positive, cognitive-behavioral therapy, Adherence to treatment, General health
  • Delaram Chaghazardy, Seyed Hessameddin Zegordi*, Hassan Aghajani Pages 94-111
    Background and Objectives

    Appointment scheduling systems are applied in a broad variety of healthcare environments to reduce costs, increase resource utilization, and facilitate patients’ access to care. This study strives to present efficient scheduling models for the Echocardiography Department of Tehran Heart Center (THC). These models seek to optimize both patient and hospital utility by maximizing the weighted number of performed echos and minimizing overtime.

    Methods

    There are two major problems in developing such models: shift scheduling problem and capacity allocation problem.In this paper, two mixed integer linear programming models are presented based on two different sets of assumptions. The first model is developed according to the current routines of the hospital.In this model, it is assumed that the assignment of specialists to echocardiography laboratories in different shifts is predetermined. Thus this model merely allocates the available capacity of specialists and labs to different types of patients. However, the second model is more comprehensive, as it schedules the shifts of the specialists and allocates the capacity to the patients simultaneously.

    Results

    The efficiency of the proposed models is evaluated using the real data of the Echocardiography Department of THC. The results showed that both models increased the utility (12.35% and 19.14%, respectively) in comparison with the current status of the department. The first model improved the performance of the department significantly through better utilization of resources; however, the second model improved the performance much more than the first one through creating more capacity and utilizing the capacity efficiently.

    Conclusion

    Although both models showed significant improvements, the second model was found to be more efficient. The reason is that the first model assumes the specialists' shift assignment to be predetermined, while the second model finds the best shift assignment itself.

    Keywords: echocardiography, Appointment scheduling, Resource Utilization, Shift scheduling, Capacity allocation, optimization, mathematical model
  • Zahra Mohammadnazari, Seyed Farid Ghannadpour* Pages 112-127
    Background and objective

    One of the most prominent factors in the success of medical systems is finding a proper location to build hospitals and other medical care centers. On the other hand, sustainable development is illustrated an important concept for both private and public sectors which focuses on three aspects of development: social, environmental and economical. Hence in order to find the best location, taking in to account sustainable criteria, can pave the path of meeting triple bottom line requirements in the field of hospitals construction.

    Methods

    Focus in this paper is on identifying the best location for the hospital construction with the help of best-worst method to find weights of each criteria and then The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to rank the possible locations. After applying TOPSIS method, with the use of additive utility function we analyze the initial ranking. In the next step Mathematical formulation has been applied in order to find the proper locations to open hospital. The objective functions consist of two equations; the first one is minimizing the opening cost and penalty cost (because of the fact that the proximity of hospitals to patients are of high importance); the second one is related to maximizing the utilities obtained from las step.   Results and

    conclusion

    according to the case study which was implemented in Tehran, the best locations for hospital construction considering penalty cost, construction cost and utilities of each hospital to offer better service, have been identified.

    Keywords: best location, healthcare management, sustainable development, best-worst method, TOPSIS, Multi-objective Programming
  • A study of the Relationship Between Job Satisfaction, Job Motivation and Organizational Commitment Among Employees of Ministry of Health, Treatment and Medical Education (MHTME)
    Ali Ebraze, Fahimeh Rabbanikhah, Amir Kazemi, Maryam Safarnavadeh, AmirHossein Eskandari, Reza Moradi * Pages 128-139
    Background and Objective

    Today, it is crucial that organizations pay special attention to their human resources in order to achieve maximum effectiveness, performance and efficiency. Employees’ attitude regarding their jobs, is what affects their performance and effectiveness at work more than any other factor. Due to the importance of employees’ attitude and perception in improving efficiency and achieving organizational goals, the aim of the current study is to investigate the correlation between job satisfaction, job motivation and organizational commitment among employees of Ministry of Health, Treatment and Medical Education (MHTME).

    methods

    This is a descriptive – analytical study which was carried out using cross-sectional approach in 2017. The statistical sample included 327 employees of MHTME which were selected using Stratified sampling and suitable sample size. Data gathering tools include Job Descriptive Index (JDI), Lodahl – Kushner Job Motivation Inventory and Organizational Commitment Inventory of Allen and Mayer. Data were then entered into SPSS-20 software and analyzed using independent T-Test, ANOVA, Person Correlation and Regression Tests.

    Findings

    Job satisfaction and motivation had a direct significant correlation with organizational commitment (P < 0.05). The results of regression analysis also indicated that organizational commitment can be proper predicted based on job satisfaction and motivation.

    Conclusion

    According to the results of this study, it is suggested that human resource managers use proper employee selection, timely incentives based on real performance evaluations, promote employees based on their abilities. Holding motivational seminars and creating appropriate job advancement opportunities increase satisfaction and motivation and therefore organizational commitment among their employees.

    Keywords: Job Satisfaction, job motivation, organizational commitment, Efficiency, Employees, Ministry of health, Treatment, Medical Education (MHTME)