The Relationship Between Patient Satisfaction And Inpatient Admissions

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Statistical Significance in Research Messina 's research study uses different methods to assess the relationship between patient satisfaction and inpatient admissions in teaching and nonteaching hospitals. Messina uses descriptive statistics which is appropriate for his research study that helps to describe, show and summarizes the quantitative data that represents the sample used (Messina et al., p 182). This study sample size, which consists of teaching and nonteaching hospitals, is large enough and adequate for this type of study. Descriptive statistics measures the mean, median and mode to determine the mean scores of patient satisfaction and admissions inpatient volume data (Messina et al., p 182). The descriptive statistics for skewness and kurtosis were also used in this study which showed that admission volumes were not normally distributed (Messina et al., p 182). The Spearman coefficient rank-order correlation in this study measures the patient satisfaction (independent variable) and admissions volume (dependent variable). A correlation analyses as well as the Mann-Whitney U-test was performed on the teaching and nonteaching hospitals to assess the relationship between admission volume and satisfaction mean score (Messina et al., p 183). Statistical Testing Results Messina et al. five years’ research study descriptive statistics for all the teaching and nonteaching hospitals participating in the study had a mean score of 82.57, 79.05 minimum and 86.18 maximum (Messina et al., p 182). The skewness and kurtosis statistics results have shown that admission volumes weren’t distributed normally and the mean scores on patient satisfaction were normally distributed (Messina et al., p 182). The Spearman rank-order correlatio... ... middle of paper ... ...ay not be harmful in a pragmatic trial; in contrast, it can be accepted as responses to treatment and also included in the results, therefore treatment results will be the total difference between two treatments yielding results in a variety of health benefits (Roland & Torgerson, p 285). Conclusion The Messina et al study, according to the chart has used the appropriate elements for comparing two different groups of hospitals with using descriptive statistics to describe the subjects and the interval data type is used with mathematical studies like the Messina research. By choosing a sample size over two participants, (they used 14 hospitals) would be adequate for this type of study. Statistical significance is a better choice for this type of study when a researcher wants to compare two different groups and it is not necessary to have a clinical or natural setting.
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