Background Hospitals are highly resource-dependent settings, which spend a large proportion of healthcare financial resources. The analysis of hospital efficiency can provide insight into how scarce resources are used to create health values. This study examines the Technical Efficiency (TE) of 12 teaching hospitals affiliated with Tehran University of Medical Sciences (TUMS) between 1999 and 2011. Methods The Stochastic Frontier Analysis (SFA) method was applied to estimate the efficiency of TUMS hospitals. A best function, referred to as output and input parameters, was calculated for the hospitals. Number of medical doctors, nurses, and other personnel, active beds, and outpatient admissions were considered as the input variables and number of inpatient admissions as an output variable. Results The mean level of TE was 59% (ranging from 22 to 81%). During the study period the efficiency increased from 61 to 71%. Outpatient admission, other personnel and medical doctors significantly and positively affected the production (P< 0.05). Concerning the Constant Return to Scale (CRS), an optimal production scale was found, implying that the productions of the hospitals were approximately constant. Conclusion Findings of this study show a remarkable waste of resources in the TUMS hospital during the decade considered. This warrants policy-makers and top management in TUMS to consider steps to improve the financial management of the university hospitals.

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 Childhood malnutrition as a major public health problem among children in developing countries can affect physical and intellectual growth and is also considered as a main cause of child morbidity and mortality. The objective of this study was to estimate the prevalence of under-nutrition and identify determinants of malnutrition among children under 6 years of age in Fars province, Iran. Methods This survey was conducted by house to house visit through multi-stage sampling in 30 cities of Fars province, during December 2012 to January 2013. A total of 15408 children, aged 0–6 years old, were studied for nutritional assessment in terms of underweight, stunting, and wasting. Also, socio-demographic measures were obtained from structured questionnaire. Backward stepwise logistic regression was used to relate underlying factors to the odds of under-nutrition indices. Results The rates of stunting, underweight, and wasting were 9.53, 9.66, and 8.19%, respectively. Male children were more stunted compared to females (OR= 1.41, CI: 1.26–1.58). Also, stunting was significantly associated with lower family income (OR= 3.21, CI: 1.17–8.85) and lower maternal education (OR= 0.80, CI: 0.64–0.98). Living in urban areas, and poor water supply were identified as significant risk factors of all three types of childhood under-nutrition. Moreover, Khamse and Arab ethnic groups were more vulnerable to under-nutrition. There was a suggestion that non-access to health services were associated with wasting (OR= 1.87, CI: 1.39–2.52) and also large family size was related to underweight (OR= 1.35, CI: 1.10–1.65). Conclusion The prevalence of under-nutrition in the study population was categorized in low levels. However, planning the public preventive strategies can help to control childhood under-nutrition according to underlying factors of malnutrition in the study population including gender, settlement area, family size, ethnicity, family income, maternal education, health services, and also safe water supply.

Despite progress towards greater public engagement, questions about the optimal approach to access public preferences remain unanswered. We review two increasingly popular methods for engaging the public in healthcare priority-setting and determining their preferences; the Citizens’ Jury (CJ) and Discrete Choice Experiment (DCE). We discuss the theoretical framework from which each method is derived, its application in healthcare, and critique the information it can provide for decision-makers. We conclude that combining deliberation of an informed public via CJs and quantification of preferences using DCE methods, whilst it remains to be tested as an approach to engaging the public in priority-setting, could potentially achieve much richer information than the application of either method in isolation.

Health Impact Assessment (HIA) is a relatively young field of endeavour, and hence, future progress will depend on the planning, implementation and rigorous evaluation of additional HIAs of projects, programmes and policies the world over. In the June 2014 issue of the International Journal of Health Policy and Management, Fakhri and colleagues investigated underlying principles of HIA through a comprehensive review of the literature and expert consultation. With an emphasis on the Islamic Republic of Iran, the authors identified multiple issues that are relevant for guiding HIA practice. At the same time, the study unravelled current shortcomings in the understanding and definition of HIA principles and best practice at national, regional, and global levels. In this commentary we scrutinise the research presented, highlight strengths and limitations, and discuss the findings in the context of other recent attempts to guide HIA.

In both developing and developed countries, health ministries closely examine use of so-called nudges to promote population health and welfare. Cass Sunstein and Richard Thaler, who developed the concept, define a nudge as “any aspect of the choice architecture that alters people’s behavior in a predictable way without forbidding any options or significantly changing their economic incentives. To count as a nudge, the intervention must be easy and cheap to avoid. Nudges are not mandates” (1).

As diabetes and obesity rates continue to climb at astronomical rates in the Middle East, future generations are at an even greater risk for diabetes and the associated complications. Many factors are at play and it is clear that creative solutions are needed to retool provider resources in the Middle East towards prevention of diabetes and its complications while leveraging technology to maximize outreach within the accepted cultural norms. Only by building the capacity to address the current diabetes burden as well focusing on prevention for the future, can Middle East countries create a strong infrastructure for a successful future.

Brugha and Bruen (2014) raise a number of compelling issues related to the interaction between politics and policy in the global health context. The first question that their views invite is whether this is, at heart, best characterized as a benign or malign influence. Many commentators have suggested that this overlap should be discouraged (see, for example, Marseille et al 2002; Thomas & Weber 2004; Fidler 2011), while others advocate a decrease in 'stove-piped' or 'siloed' approaches to government, politics, and academia (Lee et al 2010; Feldbaum 2011). To use a parallel example, the world of sport has indirectly contributed a number of notable political advances, not least the end of apartheid in South Africa as a partial result of the ban imposed on their international teams (Nixon 2002). In spite of this, organizations such as FIFA refuse to be drawn into sanctioning international football teams on non-sporting grounds (Sobolev & Gazeta 2014). The future scope and role of global health will, inevitably, face corresponding challenges.

Background The main purpose of this study was to identify factors that influence healthcare quality in the Iranian context. Methods Exploratory in-depth individual and focus group interviews were conducted with 222 healthcare stakeholders including healthcare providers, managers, policy-makers, and payers to identify factors affecting the quality of healthcare services provided in Iranian healthcare organisations. Results Quality in healthcare is a production of cooperation between the patient and the healthcare provider in a supportive environment. Personal factors of the provider and the patient, and factors pertaining to the healthcare organisation, healthcare system, and the broader environment affect healthcare service quality. Healthcare quality can be improved by supportive visionary leadership, proper planning, education and training, availability of resources, effective management of resources, employees and processes, and collaboration and cooperation among providers. Conclusion This article contributes to healthcare theory and practice by developing a conceptual framework that provides policy-makers and managers a practical understanding of factors that affect healthcare service quality.

The global health agenda has been dominating the current global health policy debate. Furthermore, it has compelled countries to embrace strategies for tackling health inequalities in a wide range of public health areas. The article by Robert and colleagues highlights that although globalization has increased opportunities to share and spread ideas, there is still great asymmetry of power according to the countries’ economic and political development. It also emphasizes how policy diffusion from High Income Countries (HICs) to Low- and Middle-Income Countries (LMICs) have had flaws at understanding their political, economic, and cultural backgrounds while they are pursuing knowledge translation. Achieving a fair global health policy diffusion of ideas would imply a call for a renewal on political elites worldwide at coping global health politics. Accordingly, moving towards fairness in disseminating global health ideas should be driven by politics not only as one of the social determinants of health, but the main determinant of health and well-being among—and within—societies.