An individual have disaggregated the length of stay values and… An individual have disagg

An individual have disaggregated the length of stay values and… An individual have disaggregated the length of stay values and separated them into their appropriate MS-DRG category, but he or she still haven’t answered the question that prompted the initial analysis: Is the individual facility’s ALOS for heart failure consistent with that of all Medicare heart failure patients? The individual want to complete the analysis by testing the hypothesis that him or her facility’s ALOS is greater than the Medicare benchmark. More formally, the individual have specified the following null and alternative hypotheses:Ho: OUR ALOS FOR DRG = BENCHMARK ALOS FOR DRGH1: OUR ALOS FOR DRG > BENCHMARK ALOS FOR DRGThe benchmark data will be the ALOS figures reported by CMS for 2016 (the most recent data available) that were used in Assignment 3.1:CMS DataThe CMS spreadsheet contains MS-DRG data (number of discharges and mean length of stay (LOS)) for each in 2016. These figures are what CMS reported for 2016. Use the z-test function to test the hypothesis for each of the three MS-DRGs: 291, 292, 293.An individual have some familiarity with the Excel software and she have read about finding probabilities using standardized scores. The individual have decide to answer the probability question posed above using Excel’s z.test function given as: =z.test(range:range,CMS LOS), where range:range represents the cells where the facility data are located, and CMS LOS is the national average against which to compare (note, leave the ”sigma” value blank).The results of this test will tell an individual the probability that he or she will reject the null hypothesis when it is actually true (i.e., that he or she will say their ALOS is greater than the benchmark when in reality their ALOS is not statistically different than the benchmark). This is known as a “Type I” error, and an individual want the probability of making this type of error to be as small as possible. The conventional threshold (or comfort level) for making this type of mistake is five percent (i.e., an individual is willing to accept that in five samples out of 100 they will mistakenly reject the null hypothesis when it is true). Naturally, a probability that is smaller is preferred since the likelihood of having made a mistake is smaller. This is essentially what a “p-value” represents: the probability of making a Type I error (of rejecting the null hypothesis when it is true, or in practical terms, concluding that a difference exists when in reality none exists)An individual’s calculations using the data specified above to determine if him or her facility’s ALOS for heart failure is consistent with that of all Medicare heart failure patients. Then, demonstrate or explain in a brief report so that an individual can replicate his or her analysis at some future date. An individual’s brief should include the following:Discuss whether, in future analyses, an individual will collect data from a sample of heart failure patients at his or her facility or look at all heart failure patients at her facility. Be sure to support this decision.Distinguish between the statistics and parameters that an individual is using (i.e., what are the statistics and what are the parameters?).Once an individual have estimated the probabilities for each MS-DRG, explain whether he or she believes that their facility has ALOS that are within an acceptable range (i.e. are statistically the same) compared to the national average.Paste a screenshot of her Excel calculations into the last page of their report.ReferencesNEDARC. (2016). Hypothesis testing. Retrieved from http://www.nedarc.org/statisticalHelp/advancedStatisticalTopics/hypothesisTesting.html The Normal Distribution: MathIsFun Advanced: Normal Distribution offers a straightforward discussion of the process of standardizing a normal distribution to the normal distribution (i.e., the standard normal distribution). https://m.youtube.com/watch?v=ykmT12Ipigc&feature=youtu.beProbability: The video below from the Khan Academy goes into more detail on probability. It is not required for this course, but available if you’d like further information. http://www.youtube.com/watch?v=3ER8OkqBdpEZtest using Excel: This is a fairly uninteresting but useful video on the mechanics of using the z-test function in Excel. Ztest using Excel. https://m.youtube.com/watch?v=AvjJuCKUIq4 Health Science Science Nursing MHA HLTH 6040 Share QuestionEmailCopy link Comments (0)

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