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HMGT 400 Research and Data Analysis in Health

HMGT 400 Research and Data Analysis in Health- FINAL EXAM

Data File: HMGTFINALEXAM.csv (Request from Professor after you submit Group Assignment #3)

Software Tool: Analysis ToolPak, RegressItLogistic or XLMiner Analysis ToolPak

Question #1 (15 credits):

The FINAL EXAM data file provides data on hospitals in 2011 and 2012. Analyze the FINAL EXAM dataset. You may calculate the “Hospital Beds per Population (Per Capita)” variable by dividing “total_hospital_beds by tot_population. Use the analysis results to complete Table 1 (template) below. Net Hospital benefits = Hospital Revenues minus Hospital Costs.

Table 1. Comparing hospitals in 2011 with hospitals in 2012

2011 2012 t Value (Pr<|t|) N Mean St. Dev N Mean St. Dev Hospital Characteristics 1. Hospital beds 1078 229.3831 206.7204 921 1301.885 32944.54 0.285168 2. Number of paid Employee 945 1146.951 1414.9 354 653.2254 875.9757 1.18516E-09 3. Number of non-paid Employee 80 48.1 68.10483 115 41.87826 43.81463 0.438670 4. Internes and Residents 279 79.65591 138.8227 44 4.340909 3.863624 0.000377 5. System Membership 1079 0.60797 0.552588 922 0.646421 0.680688 0.092113986 6. Total hospital cost 1078 203721472.4 303617442.7 919 183732389.6 265000930.8 0.122213 7. Total hospital revenues 1078 477069773.3 1034436756 919 471954365.8 1093163806 0.917651 8. Net Hospital benefits 1078 919 9. Available Medicare days 1068 16538.37734 19225.12023 919 16538 0 0.99643 10. Available Medicaid days 1052 5311.276616 9190.481016 919 5311 0 0.994757 11. Total Hospital Discharge 1074 9312.395717 10711.43761 919 9345 0 0.927247 12. Medicare discharge 1070 3206.281308 3380.252336 920 111902.162 3296796.503 0.280894 13. Medicaid discharge 1064 1253.279135 1900.277427 905 1171.319337 1762.961121 0.34953 Socio-Economic Variables 14. Hospital Beds per Population (Per Capita) 1078 0.002338 0.004095 919 0.002349 0.003575 0.9515 15. Percent of population in poverty 1078 25.96855288 9.66858643 919 25.79129489 9.528074007 0.6901 16. Percent of Female population in poverty 1078 15.87625232 5.562371262 919 15.7773667 5.444037856 0.6696 17. Percent of Male population in poverty 1078 10.09230056 4.321048879 919 10.01392818 4.316069396 0.6933 18. Median Household Income 1078 50137.41373 13656.34485 919 49714.11099 12863.14896 0.4460 Then please answer the following questions.

- A) What are the significant differences for each of the hospital characteristics between 2011 and 2012?
The number of paid employees, on the other hand, was larger in 2011 than in 2012, indicating a considerable difference. Between the two years, there is a major difference between Internes and Residents.

- B) What are the significant differences for each of the socio-economic variables between 2011 and 2012?
There are no significant differences for the socio economic variables between 2011 and 2012.

- C) Based on your findings did hospitals (in general) have a better performance in 2011 or 2012? Explain.
2011 hospital performance looks better based upon findings. In 2011 there were more hospital beds, more paid employees, more interns and residents, more revenue, more Medicaid and Medicare discharges.

- D) How does hospital performance relate to the hospital characteristics and how does it relate to the socio-economic characteristics?
Question #2 (15 credits):

In the data file, create a new variable called “hospital net benefits”. Do this by subtracting “hospital costs” from “hospital revenues”.

Analyze the dataset and then complete Table 2 (template). In the last column report the T-test results comparing hospital characteristics between 2 groups of hospitals “1. For-profit & Other ownership”, 2.“Non-profit & public” hospitals. Note in the data file:

If own = 0 then the hospital is non-profit owned

If own = 1 then the hospital is for-profit owned

If own = 2 then the hospital is public (government) owned

If own = 3 then the hospital is owned by some other organization

Table 2. Comparing “For-profit & Other” hospital group to “Non-profit & Public” hospital group in two years (2011, 2012)

For Profit & Other Non-Profit & Public t Value (Pr<|t|) N Mean St. Dev N Mean St. Dev Hospital Characteristics 1. Hospital beds 2. Number of paid Employee 3. Number of non-paid Employee 4. Internes and Residents 5. System Membership 6. Total hospital cost 7. Total hospital revenues 8. Net Hospital Benefits 9. Available Medicare days 10. Available Medicaid days 11. Total Hospital Discharge 12. Medicare discharge 13. Medicaid discharge Socio-Economic Variables 14. Per Capita Hospital Beds 15. % population in poverty 16. % Female population in poverty 17. % Male population in poverty 18. Median Household Income Then answer the following questions:

1) What are the main significant differences between the “For-profit & Other” hospital group and the “Non-profit & Public” hospital groups? Which test is the best fit test? Why?

2) Use a column plot or graph to compare “Net Hospital Benefits” between “for-profit & other” and “non-profit & public” hospitals.

3) Create a scatter plot with the correct variable and axes labels and legend. Use the plot to compare hospital cost (x-axes) and revenue (y-axes) and discuss your findings?

4) If we assume that hospital net-benefit is a good measure of hospital performance, which type of hospitals had the better performance between “for-profit & other” and “non-profit & public” hospitals?

5) Overall, what are the main statistically significant differences between “for-profit & other” and “non-profit & public” hospital groups?

Question #3 (15 credits):

Our data file provides the variable herf_ins called the Herfindahl–Hirschman Index which measures market concentration for the health insurance market. Please note that unlike the class exercise in which you used herf_cat, which measured market concentration for the hospital market, in this assignment you are using herf_ins which measures market concentration for the health insurance market.

Analyze the data to complete Table 3 (template) below:

Table 3. Comparing hospitals in High, Moderate, and Low Insurance Market Concentration in two years (2011, 2012)

High Concentration Insurance Market Moderate Conc. Insurance Market Low Concentration Insurance Market ANOVA Count Mean STDev Count Mean STDev Count Mean STDev F Value (Pr<|F|) Hospital Characteristics 1. Hospital beds 2. No. of paid Employees 3. No. of non-paid Employees 4. Internes and Residents 5. System Membership 6. Total hospital cost 7. Total hospital revenues 8. Net Hospital benefits 9. Available Medicare days 10. Available Medicaid days 11. Total Hospital Discharges 12. Medicare discharge-ratio 13. Medicaid discharge-ratio Socio-Economic Variables 14. Per Capita Hospital Beds 15. Median Household Income Then answer the following questions:

1) In a short paragraph describe and explain what the Herfindahl index is. You can use the reference provided in the class exercise or any other citation.

2) Compare the following information between hospitals located in high, moderate, and low concentration health insurance markets?

- a) What are the main significant differences between hospitals in the different insurance markets? (use the ANOVA test)
- b) What is the impact of being in a high-concentration health insurance market on hospital revenues and costs?
- c) Does being in a high concentration market have a positive impact on net hospital benefits?
- d) What about the number of Medicare and Medicaid discharges? Are hospitals in high concentration insurance markets more likely to accept Medicare and Medicaid patients?
- e) What is the impact of other variables?
(Note: to answer the last question, please compute Medicare-discharge ratios and Medicaid-discharge ratios first and then run two t-Tests (high concentration vs. moderate concentration, and high vs. low concentration market). Please support your findings with an illustrative graph.

Question #4 (Credits 20)

Regression Models

Analyze the data by running a regression model with “Net Hospital Benefits” as the dependent variable and present your results using the Table 4 template below.

Table 4 – Regression Model 1

Coefficient ST. ERR T Stats P-values Lower 95% Upper 95% Intercept/Constant Total Hospital beds Teaching Hospital Dummy Count (N) = R Square =

- a) Describe and discuss your findings.

- b) Do the number of hospital beds or whether a hospital is a teaching hospital or not have a positive or negative impact on hospital net-benefit. (Hospital Performance)? In answering this question, consider statistical significance.

Regression Model 2:

Analyze the data by running a linear regression model and present your results using the Table 5 template below.

Table 5 – Regression Model 2

Coefficient ST. ERR T Stat P-values Lower 95% Upper 95% Intercept/Constant Total Hospital beds Non-Teaching Hospital Dummy Count (N) = R Square =

- a) Describe and discuss your findings.

- b) Do the number of hospital beds or whether a hospital is a non-teaching hospital or not have a positive or negative impact on hospital net-benefits. (hospital performance)? In answering this question, consider statistical significance.

- c) Use the results from your Regression model 1 and regression model 2 to comment on any differences or similarities in impact of teaching hospital status or non-teaching hospital status on hospital net-benefits. (hospital performance)?

Regression Model 3:

Analyze the data by running a linear regression model and present your results using the Table 6 template below.

Table 6 – Regression Model 3

Coefficient ST. ERR T Stat P-values Lower 95% Upper 95% Intercept/Constant Total Hospital beds Teaching Hosp. Dummy Medicare discharge ratio Medicaid discharge ratio Count (N) = R Square =

- a) Describe and discuss your findings.

- b) Do the number of Medicare or Medicaid patients in a teaching hospital have a positive or negative impact on hospital net-benefits. (hospital performance)? In answering this question, consider statistical significance.

Regression Model 4:

Analyze the data by running a linear regression model and present your results using the Table 7 template below.

Table 7 – Regression Model 4

Coefficient ST. ERR T Stat P-values Lower 95% Upper 95% Intercept/Constant Total Hospital beds Non-Teaching Hosp. Dummy Medicare discharge ratio Medicaid discharge ratio Count (N) = R Square =

- a) Describe and discuss your findings.

- b) Do the number of Medicare or Medicaid patients in a non-teaching hospital have a positive or negative impact on hospital net-benefit. (hospital performance)? In answering this question, consider statistical significance.

- c) Based on your findings please recommend three policies to improve hospital performance. Please make sure to use the final model for your recommendation

Question #5 (Credits 20)

Logistic Regression Models

Analyze the data by running a linear regression model and present your results using the Table 8 template below.

Use “being a member of a hospital network” (system_member) as the dependent variable. and the independent variables presented in Table 8 template below

Table 8 – Logistic Model 1

Coefficient ST. ERR P-Value Exp (coeff) Exp (z SE) Exp (Std. Coeff.) Intercept/Constant Total Hospital costs Count (N) = R Square =

- a) Describe and discuss your findings.

Logistic Model 2:

Analyze the data by running a linear regression model and present your results using the Table 9 template below.

Table 9 – Logistic Model 2

Coefficient ST. ERR P-Value Exp (coeff) Exp (z SE) Exp (Std. Coeff.) Intercept/Constant Total Hospital Costs Total Hospital Revenue Count (N) = R Square =

- a) Describe and discuss your findings.

Logistic Model 3:

Analyze the data by running a linear regression model and present your results using the Table 10 template below.

Table 10 – Logistic Regression Model 3

Coefficient ST. ERR P-Value Exp (coeff) Exp (z SE) Exp (Std. Coeff.) Intercept/Constant Total Hospital Costs Total Hospital Revenue Medicare discharge ratio Medicaid discharge ratio Count (N) = R Square =

- a) Describe and discuss your findings.

- b) What is the impact of having more Medicare or more Medicaid patients in the hospitals, on membership in hospital systems?

- c) Based on your findings from Logistic Regression Model 3, please recommend three policies to justify whether hospitals will organize themselves into hospital systems or not.

Question 6 (15 credits)

- Please offer a research question for a study involving human subjects.

- Explain the difference between the research process involving human subjects and the research process not involving human subjects.

- Discuss ethical implications surrounding human subjects research studies.

- Explain the governance of the human subjects research studies over the data and the process.

- Provide examples of the consequences for not meeting IRB (Institutional Review Board) protocol requirements.

HMGT 400 Research and Data Analysis in Health—FINAL EXAM, 1

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