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Quality can be defined as the ability of a product or service to satisfy the needs and expectations of the customer. Laboratories are more focusing on technical and analytical quality for reliability and accuracy of test results. Patients and clinicians however are interested in rapid, reliable and efficient service from laboratory. Turn around time (TAT), the timeliness with which laboratory personnel deliver test results, is one of the most noticeable signs of laboratory service and is often used as a key performance indicator of laboratory performance. This study is aims to provide clue for laboratory TAT monitoring and root cause analysis. In a 2 year period a total of 75,499 specimens of outdoor patient department were monitor, of this a total of 4,142 specimens exceeded TAT. With consistent efforts to monitor, root cause analysis and corrective measures, we are able to decreased the specimens exceeding TAT from 7-8 to 3.7 %. Though it is difficult task to monitor TAT with the help of laboratory information system, real time documentation and authentic data retrievable, along with identification of causes for delays and its remedial measures, improve laboratory TAT and thus patient satisfaction.

It results from reduced secretion of either total thyroxine (T4) or triiodothyronine (T3). It leads to hypersecretion of pituitary thyroid-stimulating hormone (TSH) and so greater increase in serum TSH levels. Subclinical hypothyroidism can be defined as a high serum TSH concentration and normal serum total or free T4 and T3 concentrations associated with a few or no symptoms and signs of hypothyroidism. [1] It is referred to as a state of mild thyroid failure. [2] Subclinical hypothyroidism is more common in the elderly and is found twice in women as in men. [3] It is a more common disorder than overt hypothyroidism [4] and hence early diagnosis and treatment may prevent the onset of overt hypothyroidism along with its associated effects. Background: Hypothyroidism is a common problem that reduces the functional ability of life. Hypothyroidism is associated with altered lipid levels, which increases the cardiovascular risk. Objective: The objectives of this study were to study whether there is any correlation between serum lipid levels and hypothyroidism (subclinical and overt) in a rural population of Gujarat and to study whether there is any difference in lipid levels among menopausal and postmenopausal women. Materials and Method: A cross-sectional study was conducted at Clinical Biochemistry department, P.S. Medical College, Karamsad, which consisted 100 hypothyroid patients (subclinical and overt) and 100 similar age-and sex-matched controls. Serum total thyroxine, triiodothyronine, thyroid-stimulating hormone, free thyroxine, serum cholesterol, triglyceride, high-density lipoprotein (HDL) and low-density lipoprotein levels were examined in subclinical and euthyroid patients. Results: In patient with subclinical hypothyroidism, we found elevated serum total cholesterol (217.95) and triglyceride (148.35) levels as compared to controls (P = 0.001) but statistically insignificant HDL level (51.45; P = 0.973). In patient with overt hypothyroidism, elevated serum total cholesterol (271.92) and triglyceride (166.31) were found as compared to control (P = 0.001), but HDL level (46.57; P = 0.134) was found to be decreased. Conclusion: There is association between subclinical and overt hypothyroidism with dyslipidemia. This might be a potential risk factor for coronary artery disease.

Target detection is of particular interest in hyperspectral image analysis as many unknown and subtle signals (spectral response) unresolved by multispectral sensors can be discovered in hyperspectral images. The detection of signals in the form of small objects and targets from hyperspectral sensors has a wide range of applications both civilian and military. It has been observed that a number of target detection algorithms are in vogue; each has its own advantages and disadvantages and assumptions. The selection of a particular algorithm may depend on the amount of information available as per the requirement of the algorithm, application area, the computational complexity etc. In the present study, three algorithms, namely, orthogonal subspace projection (OSP), constrained energy minimization (CEM) and a nonlinear version of OSP called kernel orthogonal subspace projection (KOSP), have been investigated for target detection from hyperspectral remote sensing data. The efficacy of algorithms has been examined over two different hyperspectral datasets which include a synthetic image and an AVIRIS image. The quality of target detection from these algorithms has been evaluated through visual interpretation as well as through receiver operating characteristic (ROC) curves. The performance of OSP algorithm has been found to be better than or comparable to CEM algorithm. However, KOSP outperforms both the algorithms.

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