The supply chain management of medical equipment and consumer goods is full of uncertainties and unexpected issues and one of the major challenges of hospitals is the suppliers’ evaluation and selection. study aimed to provide a model for selecting the best supplier in a hospital using a combination of artificial neural network and fuzzy VIKOR. This was a descriptive study conducted in a military hospital in three phases in 2016. The results showed that the most effective factor in supplier selection was ‘quality’ (weight = 0.165). After that, the highest weights were, respectively, related to ‘price’, ‘timely delivery’, ‘packaging and transporting quality’, ‘the supplier's background’ and ‘payment terms’. According to the results of the present study, the most important factor influencing the supplier selection was ‘quality’. Given the direct impact of medical equipment and consumer goods on patients’ recovery and nurses and physicians’ proper functioning and performance, it can be recommended that the hospital managers and the staff of purchasing unit should develop the quality assessment protocol of equipment and supplies and it should be evaluated periodically by nurses, physicians and patients.

Background Improving efficiency of health sector is of particular importance in all countries. To reach this end, it is paramount to measure the efficiency. On the other hand, there are many factors that affect the efficiency of health systems. This study aimed to measure the Technical Efficiency (TE) of health systems in Economic Cooperation Organization (ECO) countries during 2004–10 and to determine the factors affecting their TE. Methods This was a descriptive-analytical and panel study. The required data were gathered using library and field studies, available statistics and international websites through completing data collection forms. In this study, the TE of health systems in 10 ECO countries was measured using their available data and Data Envelopment Analysis (DEA) through two approaches. The first approach used GDP per capita, education and smoking as its inputs and life expectancy and infant mortality rates as the outputs. The second approach, also, used the health expenditures per capita, the number of physicians per thousand people, and the number of hospital beds per thousand people as its inputs and life expectancy and under-5 mortality rates as the outputs. Then, the factors affecting the TE of health systems were determined using the panel data logit model. Excel 2010, Win4Deap 1.1.2 and Stata 11.0 were used to analyze the collected data. Results According to the first approach, the mean TE of health systems was 0.497 and based on the second one it was 0.563. Turkey and Turkmenistan had, respectively, the highest and lowest mean of efficiency. Also, the results of panel data logit model showed that only GDP per capita and health expenditures per capita had significant relationships with the TE of health systems. Conclusion In order to maximize the TE of health systems, health policy-makers should pay special attention to the proper use of healthcare resources according to the people’s needs, the appropriate management of the health system resources, allocating adequate budgets to the health sector, establishing an appropriate referral system to provide better public access to health services according to their income and needs, among many others.

Background: Hospital pharmacy is responsible for controlling and monitoring the medication use process and ensures the timely access to safe, effective and economical use of drugs and medicines for patients and hospital staff. Objectives: This study aimed to optimize the management of studied outpatient pharmacy by developing suitable queuing theory and simulation technique. Patients and Methods: A descriptive-analytical study conducted in a military hospital in Iran, Tehran in 2013. A sample of 220 patients referred to the outpatient pharmacy of the hospital in two shifts, morning and evening, was selected to collect the necessary data to determine the arrival rate, service rate, and other data needed to calculate the patients flow and queuing network performance variables. After the initial analysis of collected data using the software SPSS 18, the pharmacy queuing network performance indicators were calculated for both shifts. Then, based on collected data and to provide appropriate solutions, the queuing system of current situation for both shifts was modeled and simulated using the software ARENA 12 and 4 scenarios were explored. Results: Results showed that the queue characteristics of the studied pharmacy during the situation analysis were very undesirable in both morning and evening shifts. The average numbers of patients in the pharmacy were 19.21 and 14.66 in the morning and evening, respectively. The average times spent in the system by clients were 39 minutes in the morning and 35 minutes in the evening. The system utilization in the morning and evening were, respectively, 25% and 21%. The simulation results showed that reducing the staff in the morning from 2 to 1 in the receiving prescriptions stage didn't change the queue performance indicators. Increasing one staff in filling prescription drugs could cause a decrease of 10 persons in the average queue length and 18 minutes and 14 seconds in the average waiting time. On the other hand, simulation results showed that in the evening, decreasing the staff from 2 to 1 in the delivery of prescription drugs, changed the queue performance indicators very little. Increasing a staff to fill prescription drugs could cause a decrease of 5 persons in the average queue length and 8 minutes and 44 seconds in the average waiting time. Conclusions: The patients' waiting times and the number of patients waiting to receive services in both shifts could be reduced by using multitasking persons and reallocating them to the time-consuming stage of filling prescriptions, using queuing theory and simulation techniques. Keywords: Queuing Theory; Patient Simulation; Pharmacy; Hospitals

Background: Given the impact of politico-economic sanctions on the pharmaceutical supply chain, this study aims to identify practical strategies to improve the resilience of the Iranian supply chain in pharmaceutical procurement under politico-economic sanctions.Methods: This is a qualitative content analysis study conducted in 2018. Semi-structured interviews were conducted using snowball sampling, and saturation was achieved after 18 interviews. Guba and Lincoln's criteria, namely credibility, confirmability, transferability, and dependability, were considered to ensure the validity and transparency of the study. A five-step framework analysis was applied to analyze the data using MAX QDA10.Results: The results led to the identification of nine main themes and 26 subthemes as strategies to improve the resilience of the pharmaceutical chain. According to the thematic map, some of these strategies have an extra-sectoral character: ‘insurance organizations’, ‘strengthening relations with other countries’, ‘mechanization of the distribution system’, and ‘suppliers and manufacturers’. At the same time, some inter-sectoral strategies can help the pharmaceutical chain maintain its resilience: ‘healthcare management and policy’, ‘exploiting local potential’, ‘pricing’, and ‘integrated health information systems.’ As a strategy, ‘Medical community and consumers’ also plays a crucial role in this regard. According to the subthemes, revisions of health management, more supervision, privatization, clinical policies, strategic purchasing, improvement of the referral system, inter-sectoral cooperation, support of indigenous medicines, rational pricing, insurance system, improvement of medical coverage, and development of electronic prescription should be considered by health systems. Sufficient support for indigenous medication and supervision of the distribution system should be considered by the pharmaceutical industry, taking into account the cooperation between consumers and patients.Conclusions: Integration of the pharmaceutical supply chain and modern technologies, more attention to business complexity, economic development, intense competition, rapid changes in customer needs, and appropriate relationship between manufacturers, distributors, prescribers, and insurance organizations as purchasers should be considered by policymakers to improve supply chain resilience.

Background: One common challenge to social systems is achieving equity in financial contributions and preventing financial loss. Because of the large and unpredictable nature of some costs, achieving this goal in the health system presents important and unique problems. The present study investigated the Household Financial Contributions (HFCs) to the health system.

Objective. Medication errors are the most common types of medical errors which considerably endanger the patient safety. This survey aimed to study the factors influencing not reporting on medication errors from the nurses’ viewpoints in Abbasi Hospital of Miandoab, Iran. Methods. This was a cross-sectional, descriptive and analytical study conducted in 2012 in which all nurses () working in different inpatient units were studied using a consensus method. Required data were collected using a questionnaire. Collected data were analyzed through some statistical tests including Independent -test, ANOVA, and chi-square. Results. According to the results, the most important reasons for not reporting on medication errors were related to the managerial factors (), factors related to the process of reporting (), and fear of the consequences of reporting (), respectively. Also, there was a significant relationship between employment status and fear of the Consequences of reporting on medication errors (). Conclusion. This study results showed that managerial factors had the greatest role in the refusal of reporting on medication errors. Therefore, for example, establishing a mechanism to improve quality rather than focus only on finding the culprits and blaming them can result in improving the patient safety.