Health Care Data for Decision Making Assignment

Added on -2019-10-01

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Running Head- Health Care Data for Decision Making Health Care Data for Decision Making
1Health Care Data for Decision Making Table of ContentsIntroduction.................................................................................................................................................2Research Objective......................................................................................................................................2Data Description..........................................................................................................................................2Analysis.......................................................................................................................................................5Conclusion.................................................................................................................................................12Recommendation.......................................................................................................................................13References.................................................................................................................................................14
2Health Care Data for Decision Making IntroductionThe UTS Hospital wants to analyze his data to know the relationship between ICU hours,length of stay, marital status,and gender.The technique of regression analysis is applied topredict the ICU hours with the help of length of stay,married, single, and others. The techniqueof hypothesis testing is used to test if there is any difference in the mean length of stay betweenthe two type of gender in the UTS hospital (Portela, F., 2014).Research ObjectiveThe research objective is to analyze the relationship ofICU hours in the UTS hospitalwith the length of stay (LOC) and marital status.The dependent variable is ICU hours. Theindependent variables are the length of stay and marital status in the UTS hospital. Amongvarious categories of marital status, the area of concern is to analyze the ICU hours for married,single, and others. Since most of the patients in the hospital belong to the married or singlecategory, hence the emphasis is done on these categories (McCance, K. L., & Huether, S. E.2018).I also want to test if there is adifference in the average length of stay at the UTS Hospitalbetween males and females. The dependent variable is the length of stay. The independentvariable is gender which is classified as either male or female.Data DescriptionThe variable ICU hours is a continuous variable which is measured by the ratio scale ofmeasurement. The ICU hour for patient 1 in comparison with that of patient2. The variable
3Health Care Data for Decision Making Length of stay is also a continuous variable which is measured by the ratio scale ofmeasurement. Marital status is measured by the nominal scale of measurement as it is has sixcategories. The various categories of marital status are divorced, married, separated, single,unknown, and widowed. The variable gender is a discrete variable which is measured by thenominal scale of measurement. Gender is classified as either male or female (Chatfield, C.2018).The table of descriptive statistics for the variables measured by the ratio scale ofmeasurement are given below.The average length of stay is 4.2 units with a standard deviation of 7.9. The average ICUhours is 8.3 hours with a standard deviation of 77.59.The large value of the standard deviation (ameasure of dispersion) is an indication that the value of average length of stay is notreliable.With the large value of standard deviation (which is a measure of dispersion), I can say

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