Description
As a current or future health care administration leader, you may be required to apply the use of statistical tools to measure performance improvement in your health services organization. As you have examined throughout this course, there are a variety of statistical tools at your disposal that will allow you to enhance your decision-making skills to enhance effective health care delivery in your health services organization. The statistical tools explored this week, such as chi-square, ANOVA, and regression, are all useful in helping you identify the association between certain causes of inefficiency as well as identify those performance improvement initiatives that have been most effective in reducing such inefficiencies.
Review the resources regarding these techniques and think about how your health services organization, or one with which you are familiar, might use these techniques in practice.
Describe of one of the methods presented in the resources for this week and explain how it might be used as part of a performance improvement initiative within your health services organization or an organization with which you are familiar. Be specific and provide examples. Using fictitious data, demonstrate the use of this statistical method and interpret all results. What are other statistical techniques that might be useful for your example?
NOTE: For this Discussion, you will be required to run the SPSS software platform. Attach this chart
Ross, T. K. (2014). Health care quality management: Tools and applications. San Francisco, CA: Jossey-Bass.
- Chapter 9, "Exploring Quality Issues With Statistical Tools” (pp. 333–371)
U.S. Department of Commerce, National Institute of Standards and Technology. (2016). NIST/SEMATECH e-handbook of statistical methods. Retrieved from http://www.itl.nist.gov/div898/handbook
- Chapter 1.3.5, “Quantitative Techniques”
Explanation & Answer
Attached.
REGRESSION
/MISSING LISTWISE
/STATISTICS COEFF OUTS CI(95) R ANOVA
/CRITERIA=PIN(.05) POUT(.10)
/NOORIGIN
/DEPENDENT timespentinthehealthfacilityinminutes
/METHOD=ENTER No.ofhealthofficersabsentthatday.
Regression
Notes
Output Created
24-Jan-2018 00:04:42
Comments
Input
Data
C:\Users\Mumbi\Desktop\Academic
Writing\QS work\data set.sav
Active Dataset
DataSet1
Filter
Weight
Split File
N of Rows in Working Data
16
File
Missing Value Handling
Definition of Missing
User-defined missing values are
treated as missing.
Cases Used
Statistics are based on cases with no
missing values for any variable used.
Syntax
REGRESSION
/MISSING LISTWISE
/STATISTICS COEFF OUTS CI(95)
R ANOVA
/CRITERIA=PIN(.05) POUT(.10)
/NOORIGIN
/DEPENDENT
timespentinthehealthfacilityinminutes
/METHOD=ENTER
No.ofhealthofficersabsentthatday.
Resources
Processor Time
00 00:00:00.000
Elapsed Time
00 00:00:00.008
Memory Required
Additional Memory Required
1396 bytes
0 bytes
for Residual Plots
[DataSet1] C:\Users\Mumbi\Desktop\Academic Writing\QS work\data set.sav
Variables Entered/Removedb
Variables
Variables
Entered
Removed
Model
1
Method
No. of health
. Enter
officers absent
that day
a. All requested variables entered.
b. Dependent Variable: time spent in the health facility in
minutes
Model Summary
Model
R
.053a
1
R Square
Adjusted R
Std. Error of the
Square
Estimate
.003
-.074
4.068
a. Predictors: (Constant), No. of health officers absent that day
ANOVAb
Model
1
Sum of Squares
Regression
df
Mean Square
.600
1
.600
Residual
215.134
13
16.549
Total
215.733
14
a. Predictors: (Constant), No. of health officers absent that day
b. Depend...
Review
Review
24/7 Homework Help
Stuck on a homework question? Our verified tutors can answer all questions, from basic math to advanced rocket science!