
Supplement to Chapter on Comparison of MeansPresentations
Narrated slides and videos require Flash. AssignmentsQuestion 1. In Health Administration Programs conducting satisfaction surveys are usually covered in courses on quality improvement. This exercise shows how data from satisfaction surveys can be analyzed over time. Assume that, in different time periods, 4 randomly selected patients rated their satisfaction with our services. Are we improving? Data► Answer► Question 2. In Health Administration programs accounting courses typically cover cost data. Forensic accounting examines tries to detect fraud through accounting procedures. Following data were obtained regarding the cost of taking care of patients over several time periods. Are our costs within expectation? Data► Slides► Listen► Answer► Question 3: Payment reform has made hospital payments more complex. One issue in payment reform is whether the net payments to hospitals is decreasing because of numerous carve outs for neverevents. In health administration program payment reform is covered in several courses including courses on valuebased payments. In this assignment, examine if payments for AMI to hospitals that received higher payment at start of 2015 has changed over time. You can use Access database for opening the data in this assignment. You can analyze the data using Access SQL or Microsoft SQL. Downloading these data files and linking them is a time consuming activity, allocate sufficient time to this activity. Keep the databases you download, we will repeatedly rely on the Hospital Compare data. Download dated data files from the archives. These files look like HosArchive_YYYYMMDD.zip, where YYYY is the year, and MM is the month. Unzip the files. Extract Hospital.mdb files for each time period, make sure you record the year and the month into the database name. Keep in mind that start and end periods of data are also given inside the files and that these do not correspond to the database year file. Also note that the name of variables and files change over the years. Start from 1/1/2015 till the most recent available database. Since the data on AMI payments does not change in several of the files, you can save time and analyze the following 3 files:
In these files the denominator indicates the number of patients. Payment indicates average payment per patient. Select data that meet the following conditions:
Submit an Excel file containing the control chart for the data. Download►20161110.zip► 20150716.zip► 20150122.zip► Guide► Answer► Anto's SQL► Question 4: Insurance companies and government payers are often interested in whether providers are billing their customary rate or whether they have increased their fees in contrast to the expected rate. In courses on forensic accounting, valuebased payments, and quality, one often sees comparison of provider's current charges to expected charges. Using the data downloaded in question 3, create a riskadjusted control chart for the last time period. Use the average cost in the previous time period as expected value of payment for each hospital. Compare the observed average payment to the expected (last time period's average) payment. The steps you need to follow are the following:
Submit SQL code, top 5 organizations with highest and lowest increase in payment, and result of your test of the hypothesis. Download►20161110.zip► 20150716.zip► 20150122.zip► Question 5: Calculate the Probability of observing Z values in the following ranges in a normal distribution. Answers are provided, show your intermediary table lookup values and calculations. Z calculator► Answer►
Question 6: Using the databases from Hospital Compare, download quarterly data on average number of hours of restraints from the file "HOSPITAL_QUARTERLY_QUALITYMEASURE_IPFQR_HOSPITAL". Examine the data for "UNIVERSITY OF ALABAMA HOSPITAL". This is hospital ID code 010023. Not all time periods include new data. I was able to find the following set of data (you can f ind more):
Note that the field HBIPS2_Overall_Num indicates the numerator for the measure "Hours of physicalrestraint use." The denominator for the same overall measure is in the field HBIPS2_Overall_Den. The dictionary provides the interpretation of these two fields as hours of restraint and number of patients examined. Using the procedure for XmR control chart examine if the total number of hours of restraints has changed over time. Download►20161110.zip►20160810.zip► 20160504.zip► 20151210.zip► 20151008.zip► 20150716.zip► 20150506.zip► 20150416.zip► 20150122.zip►Dictionary► Question 7: Find the value of standard normal variable z such that area under the curve below z is .3300 or .1003. z Calculator► Question 8: Variable X has a mean of 10 and standard deviation of 2 in the population. Calculate the z score that corresponds to X = 20. z Calculator► Question 9: Variable X has a mean of 4 and standard deviation of 2 in the population. Find the value of X such that the corresponding z score for this value is 3. z Calculator► Question 10: At a board meeting, you hear different statements about who the clinic is serving. According to the statements, 68% of the patients are under 25 years old and 10% are over 50 years old. Assuming that the patients are normally distributed, find the mean and standard deviation of the distribution. We estimated the mean to be 10.62 and the standard deviation to be 30.74. Show how these mean and standard deviations were calculated. z Calculator►Answer► Question 11: You are health administrator who is interested in examining organizational motivation and commitment of hospital employees. As part of a research project you have collected data from 16 employees serving in various wards of a hospital in a large metropolitan area. The following table provides information on Employee type (1 = trainee, 2 = supervisor, 3 = manager), Gender (1 = female, 2 = male), Training (010 scale), Motivation (010 scale), and Commitment (010 scale) of the 16 employees in your sample. Please make sure that you treat employees and gender as categorical variables and training, motivation and commitment as quantitative variables.
(a) Compute descriptive statistics for each variable. Check that you have not made an error in data entry and that your descriptive statistics match the following Excel output.
(b) Use Excel to perform a one sample test to evaluate whether or not
the mean motivation level of all employees in the population is
different from 5. The null hypothesis is that µ1 = 5; i.e. the
population mean motivation level is equal to 5. The alternative
hypothesis is that µ1 ≠ 5; i.e. the population mean motivation level is
significantly different from 5. Calculate the mean (4.31) and the
standard deviation (3.00) using functions in Excel. Calculate the
tstatistic and its degrees of freedom. Calculate the critical value and
test if the critical value is less than alpha of 0.05. Copy/paste
relevant Excel output. Provide interpretation of "t" test results. More
