In a time of rising demands on hospital reimbursement levels, focus on efficient operations is becoming more imperative. In health care systems, the measurement of efficiency is usually the first step in auditing individual performance of production units, e.g. hospitals, health centers, etc. It constitutes the rational framework for the distribution of human and other resources between and within health care facilities. The term efficiency is broadly used in economics and refers to the best utilization of resources in production. Typical example of efficiency is technical efficiency, referring to the effective use of resources in producing outputs. In the Farrell framework, a hospital is judged to be technically efficient if it is operating on the best practice production frontier in its hospital industry. In general, there are two main frontier methods in measuring efficiency. The first is Data Envelopment Analysis (DEA), a linear programming method which enables the measurement of efficiency consistent with the theoretically based concept of production efficiency. DEA typically examines the relationship between inputs to a production process and the outputs of that process. The second technique for assessing efficiency that is employed is Stochastic Frontier Analysis (SFA). This is an econometric technique to estimate a conventional function; with the difference being that efficiency is measured using the residuals from the estimated equation. The error term is therefore divided into a stochastic error term and a systematic inefficiency term.

PURPOSE: Dyslipidemia has been established as one of the most important modifiable risk factors for cardiovascular disease. Due to the higher prevalence of dyslipidemia in males, this study aimed to estimate the prevalence of dyslipidemia in Iranian urban men. MATERIALS AND METHODS: A screening program was conducted in 845 Iranian men 25 years of age and older in 2014. A health interview survey was conducted to evaluate the prevalence of self-reported dyslipidemia and to collect demographic data, as well as serum lipid profile screening by a reference laboratory. Lipoprotein levels was categorized based on the Adult Treatment Panel III criteria and the data were analyzed using the chi-square test and analysis of variance. RESULTS: The overall prevalence of dyslipidemia was 51.8%, and the prevalence of various forms of dyslipidemia was as follows: hypercholesterolemia (> or =240 mg/dL), 11.4%; hyper-low-density lipoprotein cholesterol (> or =160 mg/dL), 9.6%; hypertriglyceridemia (> or =200 mg/dL), 25%; and hypo-high-density lipoprotein (HDL) cholesterol (<40 mg/dL), 34.3%. With the exception of hypo-HDL, all forms of dyslipidemia were significantly less common in men over 65 years of age (p<0.05). CONCLUSIONS: The prevalence of hypo-HDL and hypertriglyceridemia was higher than expected in Iranian adult men, with half of men 25 years of age and older affected by at least one form of dyslipidemia. A large gap in primary and secondary care was observed, because nearly 80% of patients with dyslipidemia were unaware of their status. Urgent preventive programs and lifestyle changes are necessary to reduce the prevalence of cardiovascular risk factors.
Adult* ; Cardiovascular Diseases ; Cholesterol ; Dyslipidemias* ; Humans ; Hypercholesterolemia ; Hypertriglyceridemia ; Life Style ; Lipoproteins ; Male ; Mass Screening* ; Metabolic Diseases ; Prevalence* ; Risk Factors ; Secondary Care

PURPOSE: Metabolic syndrome (MS) is characterized by a collection of interdependent disorders, including abdominal obesity, dyslipidemia, hyperglycemia, hypertension, and diabetes. The current study aimed to estimate the prevalence of MS in Qom, Iran. MATERIALS AND METHODS: A population-based screening program was conducted in the city of Qom, in 845 urban adult men over 25 years old in 2014. Abdominal obesity, fasting blood glucose (FBG), blood pressure, and the serum lipid profile were measured in subjects after fasting for at least 8 hours. MS was defined according to the Adult Treatment Panel III criteria. Data were analyzed using the chi-square test, t-test, and multiple logistic regression. RESULTS: The overall prevalence of MS was 23.0%, and the most common prevalent metabolic abnormalities associated with MS were low high-density lipoprotein cholesterol (< 40 mg/dL) in 34.3% of subjects, a waist circumference >102 cm in 33.9%, blood pressure ≥130/85 mmHg in 27.6%, fasting triglycerides (TG) ≥150 mg/dL in 25%, and FBG ≥110 mg/dL in 20.6%. A FBG level ≥110 mg/dL (odds ratio [OR]=4.85; 95% confidence interval [CI], 2.14~8.24), dyslipidemia (OR=3.51; 95% CI, 2.10~5.89), and a fasting TG ≥150 mg/dL were the most important factors contributing to MS. CONCLUSIONS: The prevalence of MS in men in Qom was higher than has been reported in other countries, but it was lower than the mean values that have been reported elsewhere in Iran. FBG was the most important factor contributing to MS, and all elements of the lipid profile showed important associations with MS.
Adult ; Blood Glucose ; Blood Pressure ; Cholesterol ; Dyslipidemias ; Fasting ; Humans ; Hyperglycemia ; Hyperlipidemias ; Hypertension ; Iran ; Lipid Metabolism Disorders ; Lipoproteins ; Logistic Models ; Male ; Mass Screening ; Obesity, Abdominal ; Prevalence ; Triglycerides ; Waist Circumference