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Reducing informal payments (IPs) for health services has always been a top priority for health policymakers all over the world. As the newest attempts to reduce IPs, Iran’s Government applied a set of reforms in the health care system in 2014 called “Health Sector Evolution Plan” (HSEP). The purpose of this paper is to investigate the prevalence and nature of IPs one year after implementing this plan.

This descriptive and cross-sectional study was a nationwide survey on Iran's health sector informal payments carried out in 2016. To do this, a sample of 1,112 Iranain households was selected from all over the country using a multistage cluster-stratified sampling method. The prevalence and nature of IPs were determined through conducting face-to-face interviews using a standard questionnaire.

One year after implementing the HSEP, about 27.7 percent of sampled Iranians had at least one experience of IPs for health services. The prevalences of compulsory and voluntary IPs were 21.4 and 11.5 percent, respectively. IPs were reported by 26.1 and 12.5 percent in the inpatient and outpatient services, respectively.

According to the results, compulsory IPs are still prevalent in both the outpatient and inpatient services of Iran’s health system and it seems that the HSEP has not been completely successful in achieving the goal of eradicating IPs. It can be said that the HSEP has been the first step toward eradicating IPs in Iran and should not be the last one. The study provides useful results of the prevalence and nature of IPs after implementing the HSEP, which should be considered in designing the next steps.

Informal payments (IPs) for healthcare are a serious obstacle to equitable access and universal health coverage in developing countries. Policy makers need to know more about the hidden nature of informal patient payments (IPPs) before any policy adoption and implementation. The purpose of this paper is to systematically review the main factors affecting IPPs.

This systematic review was conducted in 2018 using the standard guideline of PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses. All English original articles on the determinants of IPPs published in the scientific journals, whose full text was available through Scopus, PubMed and Web of Science databases, which were given consideration for review.

The results showed that IPPs were greatly dependent on the characteristics of healthcare consumers, providers, healthcare system and services. Among healthcare consumers’ characteristics affecting IPPs, the income, age, education, gender, employment and health status were more cited factors, respectively. Among healthcare providers’ characteristics affecting IPPs, the providers’ experience, reputation, and salary satisfaction were better known, respectively. Among healthcare services features, the hospitalization, service specialty and the level of treatment urgency were more noted, respectively.

Policy making against IPs in the health sector requires precise attention to all components of healthcare market, including healthcare consumers, providers, healthcare system and services characteristics.

There is not enough comprehensive evidence on factors affecting hospital costs and revenue (HCR). The main objective of the current study is to identify and classify factors affecting HCR integrating experts' opinions and literature review.

First, a restricted literature review is conducted to identify the factors affecting HCR. In the second step, the targeted semi-structured interviews are conducted with 15 experts to identify, validate and classify the latent factors.

In addition to the factors identified through the literature review, 22 new important factors were added by the experts as the determinants of HCR, which were not pointed out in previous studies. The final model presented for the factors affecting HCR contains seven main groups, 22 subgroups and 70 variables.

Factors affecting HCR will provide valuable contributions for hospital budgeting, and financial and strategic planning, and they will offer an effective horizon for future research on cost-cutting strategies.

This study aims to identify and prioritize barriers to the implementation of medical equipment (ME) marketing strategies using the analytic hierarchy process (AHP).

This was an applied, cross-sectional and descriptive-analytic study conducted in 2017 in Iran. The study population included 30 medical equipment experts working in the Ministry of Health and Medical Education. A researcher made pair-wise comparison questionnaire was used for collecting the required data. The validity and reliability of this questionnaire were confirmed through getting five related experts’ opinions and inconsistency ratio (IR = 0.04). The AHP technique and Expert Choice 10.0 software were used to prioritize the barriers to the implementation of ME marketing strategies.

The results showed that among four categories of barriers to the implementation of ME marketing strategies, “managerial and strategic barriers” (FW = 0.339) and “structural barriers” (FW = 0.139) were the most important and the least important barriers, respectively.

This study, for the first time, has identified and prioritized barriers to the implementation of medical equipment marketing strategies using the AHP.

Appropriate logistic planning for the pharmaceutical supply chain can significantly improve many financial and performance aspects. To this aim, a multi-objective optimization model is proposed in this paper that considers different types of pharmaceuticals, different vehicles with determining capacities and multi-period logistic planning. This model can be updated based on new information about resources and newly identified requests.

The main objective function of the proposed model in this paper is minimizing the unsatisfied prioritized requests for pharmaceuticals in the network. Besides, the total transportation activities of different types of vehicles and related costs are considered as other objectives. Therefore, these objectives are optimized hierarchically in the proposed model using the Lexicographic method. This method finds the best value for the first objective function. Then, it tries to optimize the second objective function while maintaining the optimality of the first objective function. The third objective function is optimized based on the optimality of other objective functions, as well. A non-dominated sorting genetic algorithm II-multi-objective particle swarm optimization heuristic method is designed for this aim.

The performances of the proposed model were analyzed in different cases and its results for different problems were shown within the framework of a case study. Besides, the sensitivity analysis of results shows the logical behavior of the proposed model against various factors.

The proposed methodology can be applied to find the best logistic plan in real situations.

In this paper, the authors have tried to use a multi-objective optimization model to guide and correct the pharmaceutical supply chain to deal with the related requests. This is important because it can help managers to improve their plans.