Economic decision models are being increasingly used to assess medical interventions. Advances in this field are mainly due to enhanced processing capacity of computers, availability of specific software to perform the necessary tasks, and refined mathematical techniques. We here estimated the incremental cost-effectiveness of ten strategies for colon cancer screening, as well as no screening, incorporating quality of life, noncompliance and data on the costs and profit of chemotherapy in Iran. We used a Markov model to measure the costs and quality-adjusted life expectancy of a 50-year-old average-risk Iranian without screening and with screening by each test. In this paper, we tested the model with data from the Ministry of Health and published literature. We considered costs from the perspective of a health insurance organization, with inflation to 2011, the Iranian Rial being converted into US dollars. We focused on three tests for the 10 strategies considered currently being used for population screening in some Iranians provinces (Kerman, Golestan Mazandaran, Ardabil, and Tehran): low-sensitivity guaiac fecal occult blood test, performed annually; fecal immunochemical test, performed annually; and colonoscopy, performed every 10 years. These strategies reduced the incidence of colorectal cancer by 39%, 60% and 76%, and mortality by 50%, 69% and 78%, respectively, compared with no screening. These approaches generated ICER (incremental cost-effectiveness ratios) of $9067, $654 and $8700 per QALY (quality-adjusted life year), respectively. Sensitivity analyses were conducted to assess the influence of various scales on the economic evaluation of screening. The results were sensitive to probabilistic sensitivity analysis. Colonoscopy every ten years yielded the greatest net health value. Screening for colon cancer is economical and cost-effective over conventional levels of WTP8.

BackgroundHospitals are the most costly and important components of any health care system, so it is important to know their economic values, pay attention to their efficiency and consider factors affecting them.ObjectiveThe aim of this study was to assess the technical scale and economic efficiency of hospitals in the West Azerbaijan province of Iran, for which Data Envelopment Analysis (DEA) was used to propose a model for operational budgeting.Materials and MethodsThis study was a descriptive-analysis that was conducted in 2009 and had three inputs and two outputs. Deap2, 1 software was used for data analysis. Slack and radial movements and surplus of inputs were calculated for selected hospitals. Finally, a model was proposed for performance-based budgeting of hospitals and health sectors using the DEA technique.ResultsThe average scores of technical efficiency, pure technical efficiency (managerial efficiency) and scale efficiency of hospitals were 0.584, 0.782 and 0.771, respectively. In other words the capacity of efficiency promotion in hospitals without any increase in costs and with the same amount of inputs was about 41.5%. Only four hospitals among all hospitals had the maximum level of technical efficiency. Moreover, surplus production factors were evident in these hospitals.ConclusionsReduction of surplus production factors through comprehensive planning based on the results of the Data Envelopment Analysis can play a major role in cost reduction of hospitals and health sectors. In hospitals with a technical efficiency score of less than one, the original and projected values of inputs were different; resulting in a surplus. Hence, these hospitals should reduce their values of inputs to achieve maximum efficiency and optimal performance. The results of this method was applied to hospitals a benchmark for making decisions about resource allocation; linking budgets to performance results; and controlling and improving hospitals performance.

In health insurance, a reimbursement mechanism refers to a method of third-party repayment to offset the use of medical services and equipment. This systematic review aimed to identify challenges and adverse outcomes generated by the implementation of reimbursement mechanisms based on the diagnosis-related group (DRG) classification system. All articles published between 1983 and 2017 and indexed in various databases were reviewed. Of the 1,475 articles identified, 36 were relevant and were included in the analysis. Overall, the most frequent challenges were increased costs (especially for severe diseases and specialised services), a lack of adequate supervision and technical infrastructure and the complexity of the method. Adverse outcomes included reduced length of patient stay, early patient discharge, decreased admissions, increased re-admissions and reduced services. Moreover, DRG-based reimbursement mechanisms often resulted in the referral of patients to other institutions, thus transferring costs to other sectors.Keywords: Health Insurance; Third-Party Payments; Reimbursement Mechanisms; Diagnosis-Related Groups; Quality of Health Care; Patient Outcome Assessment; Systematic Review.

Background and Aim:While most of the published researches have reported the amount of inequity in geographical distribution of important health resources, only a small number of studies have focused on the trend of inequality in the distribution of these resources.The purpose of this study was to determine the trend of inequality in the distribution of intensive care beds in Iran during 2010 to 2012 by using the Gini coefficient.Methods:This is a cross-sectional research conducted in 2013. The changes over three years (2010 to 2012) were calculated by Gini coefficient to investigate the trend of inequality in geographical distribution of intensive care beds (CCU, ICU and NICU).Results:The Gini coefficient for CCU beds was calculated as 0.02, 0.04 and 0.06 in 2010, 2011 and 2012, respectively. The Gini coefficient for ICU beds was calculated as 0.03, 0.05 and 0.05 in 2010, 2011 and 2012, respectively. Also, the Gini coefficient for NICU bed was calculated as 0.02, 0.03 and 0.04 in 2010, 2011 and 2012, respectively.Conclusion:Regarding to Gini coefficient, the trend of inequality was increased in the distribution of intensive care beds in Iran. Particularly, the inequalities in distribution of CCU beds were significantly increased during past years. In fact, if this trend of inequality continues, the distribution of intensive care beds will be extremely unequal in the next five years in Iran.

Background: Due to the importance and uniqueness of the characteristics of the health sector, one of the most important priorities of the Ministry of Health is measuring the efficiency and quality of services which are provided for the people who refer to the health sectors. In all health systems, responding to the needs and wishes of patients is a crucial priority. Objectives: The main purpose of this study is to prioritize the features of the services from the perspective of patients, by applying the Logit model. Materials and Methods:This study is a descriptive cross-sectional study and in terms of results it can be classified to an applied study. Data were collected by a questionnaire filled by 330 patients in Imam Khomeini hospital, and for estimating the utility function the software STATA version 10 was applied. In this study the preferences of patients who admitted to hospitals were identified by calculating the marginal utility of the characteristics, where we also used Marginal Rate substitutions (MRS). Results: Determination of the marginal utility characteristics shows that the first priority in receiving hospital services is the type of examination, and the last priority in the cleaning service of the sections and restrooms . Waiting time between hospital arrivals and admission has a negative sign which indicates a negative impact on patient preference. Conclusions:The results of this study are consistent with studies by Kara Hanson and Barbara Mc Clean, where in their study they also showed that by the patient's perspective, hospital examination is the most important quality characteristic (coefficient = 2.78). In other words, the ultimate purpose of the hospital visit is the quality of service and examination, where many patients are willing to wait longer or pay higher costs to get the best services.Keywords: Patients' Rights; Hospitals; Discrete Choice Experiment Implication for health policy/practice/research/medical education: This work helps improve health policy in hospitals. Due to the unique characteristics of the health centers and, the importance of patient's strength and their association in the decision-making process, this research prioritizes the hospital service features according to patients' point of view by applying logistic modelling.