BackgroundDue to extensive literature in the field of lung cancer and their heterogeneous results, the aim of this study was to systematically review of systematic reviews studies which reviewed the cost-effectiveness of various lung cancer screening and treatment methods.MethodsIn this systematic review of systematic reviews study, required data were collected searching the following key words which selected from Mesh: “lung cancer”, “lung oncology”, “lung Carcinoma”, “lung neoplasm”, “lung tumors”, “cost- effectiveness”, “systematic review” and “Meta-analysis”. The following databases were searched: PubMed, Cochrane Library electronic databases, Google Scholar, and Scopus. Two reviewers (RA and A-AS) evaluated the articles according to the checklist of “assessment of multiple systematic reviews” (AMSTAR) tool.ResultsOverall, information of 110 papers was discussed in eight systematic reviews. Authors focused on cost-effectiveness of lung cancer treatments in five systematic reviews. Targeted therapy options (bevacizumab, Erlotinib and Crizotinib) show an acceptable cost-effectiveness. Results of three studies failed to show cost-effectiveness of screening methods. None of the studies had used the meta-analysis method. The Quality of Health Economic Studies (QHES) tool and Drummond checklist were mostly used in assessing the quality of articles. Most perspective was related to the Payer (64 times) and the lowest was related to Social (11times). Most cases referred to Incremental analysis (82%) and also the lowest point of referral was related to Discounting (in 49% of the cases). The average quality score of included studies was calculated 9.2% from 11.ConclusionsTargeted therapy can be an option for the treatment of lung cancer. Evaluation of the cost-effectiveness of computerized tomographic colonography (CTC) in lung cancer screening is recommended. The perspective of the community should be more taken into consideration in studies of cost-effectiveness. Paying more attention to the topic of Discounting will be necessary in the studies.

Background: The fair wage to specialist physicians and nurses can enhance their job motivation, quality of work, job satisfaction level, and improve the delivery of services to patients. The present study aimed to compare the proportion of changes in earnings of specialist physicians and nurses before and after implementing the Iran’s New Tariffs Book and compare their average income with a number of selected countries. Methods: This descriptive-analytical study was conducted cross-sectional in the hospitals affiliated to Iran University of Medical Sciences (IUMS) in 2016. Six months before and after the announcement and implementation of the Iran’s New Tariffs Book, the relative values of healthcare services were compared. Study population included all specialist physicians and nurses working in the hospitals affiliated to IUMS. Sample size was determined by sampling formula. Results: The proportion of changes in the income of medical specialists and nurses after establishing the book varied between 8% and 184%. Based on our findings, the highest increases were observed in internal medicine (184%), surgery (160%), gastroenterology (153%), and pediatrics (120%), whereas, the lowest ones belonged to ophthalmology (8%), emergency medicine (11%), neurology (24%) and anesthesia (32%). Nurses’ income was surged by 43%. Conclusion: Pursuant to the findings, the income belonged to all examined medical specialists and nursing groups has increased after implementing the Iran’s New Tariffs Book. The result suggested that income differences among groups have been broadened after the implementation of the Book. There was a wide and significant difference in specialist physicians’ income vis-à-vis nursing groups’ income before and after establishing the New Book.

CONTEXT: Selecting variables is a fundamental step in evaluating comparative efficiency because the results of measuring efficiency depend on the used variables. AIMS: The aim of this study is to provide a comprehensive set of input and output variables for measuring efficiency with an emphasis on application in general hospitals in Iran. MATERIALS AND METHODS: This study comprised a literature review followed by a Delphi survey process. After extracting the variables from the literature review in order to reach consensus on them and identify the native variables, the researchers used the Delphi technique in three rounds. Thirty Iranian hospital managers, in Alborz, Saveh, Qazvin, Qom, and Hamadan universities, participated in this study. For analysis, the interquartile range (IQR) and median were used. IQR was used to assess the agreement of Delphi panel members. RESULTS: After literature review, nine indicators were identified as input variables and 11 indicators were identified as output variables. After the proposed changes by Delphi members, 24 input variables and 24 output variables were identified to measure hospital efficacy. Finally, ten variables were selected as inputs and ten variables were selected as outputs to measure the performance of public hospitals in Iran by using the consensus of the members in the Delphi panel. CONCLUSIONS: This study proposes a framework for selecting the most appropriate variables for measuring the hospital efficiency with an emphasis on nonparametric methods. Choosing variables to measure hospital efficiency requires infrastructure such as an intelligent information system.

Stock companies play a key role in the economy of any country and the success of these companies depends to a great degree on investors and creditors' interest who invest in them. Auditors' reports assume a special position in the decisions taken by investors and creditors. Therefore, the importance of offering high quality information with a view on recent events in the firms (bankruptcy and dissolution, financial scandals, loses suffered by creditors, etc.) becomes clear; moreover, audit reports can prevent these events by creating certain signals. To this end, modern heuristic methods for the prediction of the type of auditor's opinion are offered in this paper. The aim of this study is to investigate the ability of probabilistic neural network method and to compare it with artificial neural network in order to identify and predict the type of independent auditor's opinion in Iran in the time period of 2009 to 2013. The patterns used to predict the type of independent auditor's opinion can be divided into different categories-these categories are becoming more complex and more advanced: single-variable models, multi discriminant analysis, regression function, neural networks, etc. neural networks are getting increasing popularity among researchers for their non-linear and non-parametric properties. Therefore, modern approaches are used in this study to predict the type of auditor's opinion.

Background: Developing countries, such as Iran, have been struggling with high rates of insurance deduction. As part of the Health Transformation Plan (HTP) in Iran, a new reference book was introduced to update the medical tariffs. This study aimed to compare the rates and extent of insurance deductions before and after HTP in Iran's public hospitals.Methods: This was a quasi-experimental study. Overall, 400 medical bills were selected from Iran's national Health Information System using multilevel random sampling before and after HTP implementation (2014 and 2017). Insurance deductions were divided into 5 groups: (1) diagnostic procedures, (2) medication and medical appliances, (3) accommodation and human capital provision, (4) surgery, and (5) other services. Using STATA Version 14.0, independent t test and Fisher's exact test were used for data analysis. Significance level was set at 0.5.Results: There was a significant decrease in insurance deductions among Iran's Health Insurance (HI) and Social Security Insurance (SSI). Accordingly, before HTP, the average amount of insurance deductions was 58.9% and 71.3% in HI and SSI, respectively. Moreover, there was a significant decline in all 5 groups between the pre-and postimplementation of HTP (p<0.05). Based on the results, hospitalization time (OR=2.31, 95% CI=1.9-3.2), patients in general hospitals (OR=1.49, 95% CI=1.4-2.7), coverage by SSI (OR=2.54, 95% CI=1.8-5.6), and having surgery (OR=3.5, 95% CI=2.0-7.3) increase the chance of insurance deduction significantly (p<0.05).Conclusion: Findings of this study showed that after HTP, insurance deductions were decreased significantly. The causes of this decline may be due to the range of services covered by public insurances, increase in insurance coverage, and improvement in health providers-insurance companies communication.