Assessment Tools Analysis Essay Example | Topics and Well Written Essays - 250 words

Assessment Tools Analysis - Essay Example the assessment tools are often utilized to evaluate and assess patients in different states and stages of their wellness, stress, illness, and life (Weber and Kelley, 2010). Therefore, the assessment tools are critical instruments in the health care since they help nurses to determine problems of patients. There are assortments or numerous assessment tools that are frequently utilized within the health care systems. The frequently used nursing assessment tools include Glascow Coma Scale, vital signs, and pain scale, physical and social examinations (Weber and Kelley, 2010). Quality health care services rendered to a patient often depends on the efficiency and accuracy of the results obtained during the assessment. The essential step in the analysis is the trust between the patient and the nurse; otherwise, the assessment tools employed may be irrelevant in the health care. Nursing assessment is a difficult process; however, it is the basis of caring to the patients. Therefore, effective application of assessment analysis tool requires the establishment of holistic relationship between the patient and the caregiver or the nurse. The nursing assessment tools are analyzed in three broad categories including Apgar score, Edinburgh Postnatal Depression Scale (EPDS), and Finnegan Scale (Web er and Kelley, 2010). Thus, it is vital for  nurses to practice and adopt the use of these theorems towards rendering effective and quality nursing or health care to

MGM600-0803B-02 Applied Managerial Decision-Making - Phase 3 Essay

MGM600-0803B-02 Applied Managerial Decision-Making - Phase 3 Discussion Board 2 - Essay Example ANOVA test is of two types, One-Factor ANOVA and Two-Factor ANOVA (with and without replication). In One-Factor ANOVA, Dependent Variable (numerical) may be affected by one independent variable (categorical). In Two-Factor ANOVA, Dependent Variable (numerical) may be affected by two independent variables (categorical). An ANOVA test is useful, when different data sets (more than two) need to be compared for similar distribution population (treatment. A t-test can also be used for comparison; however, it is limited to two samples. For more than two data sets, many t-test needs to be carried out sequentially that will increase statistical error due to accumulation. An ANOVA test lessons the statistical error due to analysis of entire data set at once and makes it more likely that a determination can be made in valid manner (Skrzypczak, 2006; Pieniazekon, A. 2007). Suppose 10 day’s daily defect rates for automotive computer chips manufactured production data for four different plant locations were available. Now for this data ANOVA can be useful for determining whether the observed differences in the plants’ sample mean defect rates merely due to random variation or the observed differences between the plants’ defect rates too great to be attributed to chance. Here ANOVA hypothesis will be ‘mean defects rates are same for at all four plants (H0)’ and ‘at least one mean differs from the others (H1)’. The One-Factor ANOVA dependent variable will be defect rate and independent variable will be plant locations (Doane, & Seward, 2007). Suppose a hospital management needs to test whether a patient’s length of a stay (LOS) depends on the diagnostic-related group (DRG) code and the patient’s age group, so that resources and fixed costs are correctly allocated. Considering case of bone fracture, LOS is a dependent variable measured in hours and type of fracture (facial, radius or ulna, hip or femur, other lower extremity, all other) and