HMGT400 UMUC Research and Data Analysis in Health Care Exercise

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HMGT 400 Research and Data Analysis in Health Care-Exercise

Dataset:HMGTHOSP.csv (Please download dataset from the class)

Required program: EXCEL  (BONUS points for using RStudio or R Programming).

Author, Hossein Zare, PhD

Citation: Zare, H. (2017). HMGT 400 Research and Data Analysis in Health Care-Exercise. UMUC.EDU

For each week exercise, Master RStudio codes (for BONUS point seekers) and a video will be posted.

Week 2, Exercise:

Use the dataset from week1 exercise and then answer the following questions:

  1. Compare the following information between teaching and non-teaching hospitals.
  2. What are the main significant differences between teaching and non-teaching hospitals? (use t-test)
  3. Comparing hospital net-benefit, which hospital has better performance? To answer this question first compute the hospital net benefits with subtracting and then use t-test to compare the significant differences between teaching and non-teaching hospitals.
  4. Use a box-plot and compare hospitals-cost and hospital-revenues between teaching and non-teaching hospitals.
  5. Write a short paragraph and describe your findings and their importance for the managerial decision-making. List a specific managerial function and the way the processed date will be used to meet the managerial objectives.

Table 2. Descriptive statistics between teaching and non-teaching hospitals, 2011 & 2012

Hospital Characteristics

Teaching

Non-Teaching

p-value

N

Mean

St. Dev

N

Mean

St. Dev

1. Hospital beds

2. Number of paid Employee

3. Number of non-paid Employees

4. Interns and Residents

5. System Membership

6. Total hospital cost

7. Total hospital revenues

8. Hospital net benefit

9. Available Medicare days

10. Available Medicaid days

11. Total Hospital Discharge

12. Medicare discharge 

13. Medicaid discharge

Use Excel for calculations (mandatory)

(BONUS points:Master RStudio script is available for this exercise (see the RStudio: working toward BONUS points module in week 2), modify as needed for the analysis)

 
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