EXERCISE 3 AND 4

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HMGT400WEEK1EXERCISE1AND23AND4.docx

Week 1, Exercise:

The attached dataset, provides some information about hospitals in 2011 and 2012, download the data and then complete the descriptive table. Please use the following format to report your findings.

Table 1. Descriptive statistics between hospitals in 2011 & 2012

Variables

2011

2012

p-value

N

Mean

St. Dev

N

Mean

St. Dev

Hospital beds

1505

376.6086

560.8998

1525

376.8

579.8366

< 2.2e-16

Number of paid Employee

1498

1237.276

1615.797

1515

1491.121

1961.637

< 2.2e-16

Number of non-paid Employee

30

39.973

72.58805

30

44.76976

81.29861

6.653e-05

Total hospital cost

1505

216873322

304570722

1525

214748023

294143536

< 2.2e-16

Total hospital revenues

1505

228706319

323339811

1525

229978391

321273114

< 2.2e-16

Available Medicare days

1499

16739.16

19214.29

1516

17110.14

19765.74

< 2.2e-16

Available Medicaid days

1484

5301.199

9207.699

1501

5366.333

9340.373

< 2.2e-16

Total Hospital Discharge

1500

9492.326

10898.6

1517

9544.051

10994.17

< 2.2e-16

Medicare discharge

1499

3230.624

3388.957

1516

3598.248

3785.675

< 2.2e-16

Medicaid discharge

1481

1130.727

1757.158

1498

1119.547

1740.423

< 2.2e-16

Based on your findings in which years hospitals had better performance? Please write a short paragraph and describe your findings. The hospitals had better performance in 2012 compared to 2011. The mean number of hospital beds in 2012 was slightly higher than the mean number of hospital beds in 2011. In terms of revenue, the mean revenue in 2012 was higher than the mean revenue in 2011. The total cost in 2011 was also higher than the total cost in 2012. For these variables, the p.value is less than 0.05 hence the null hypothesis is not rejected at 95% confidence interval. This implies that the means between the two groups are not different.

(Note: Master RStudio script is available for this exercise, but you need to modify that for this analysis)

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 ttest)

3) Comparing hospital net-benefit which hospitals has better performance? To answer this question first compute the hospital net benefits with subtracting hospital costs and revenues and then use ttest 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.

The costs were higher for teaching hospitals (1) compared to non-teaching hospitals (0)

The Revenues were higher for teaching hospitals (1) compared to non-teaching hospitals (0)

5) Write a short paragraph and describe your findings.

Based on the t-.test results shown below, there were no significant differences between teaching and non-teaching hospitals for all the variables. This is because as shown below, the p.value is less than 0.05 hence at 95% confidence Interval, we do not reject the null hypothesis (There is no significant difference in the means).

For the hospital net benefit, the p. value is also less than 0.05 hence at 95% confidence interval, the null hypothesis is not rejected, hence there is no significant difference between teaching and non-teaching hospitals in terms of performance.

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

Variables

Teaching

Non-Teaching

p-value

N

Mean

St. Dev

N

Mean

St. Dev

Hospital Characteristics

936

5.554487

1.743811

2094

3.637058

1.733039

< 2.2e-16

Hospital beds

936

549.0256

605.0675

2094

299.6791

536.7652

< 2.2e-16

Number of paid Employee

929

2475.563

2550.745

2084

869.8128

1001.237

< 2.2e-16

Number of non-paid Employee

30

57.08453

101.8859

30

27.65823

32.58495

6.653e-05

Internes and Residents

617

124.8958

179.446

308

41.52964

96.46728

< 2.2e-16

System Membership

936

0.6698718

0.4705105

2094

.5773639

0.4940966

< 2.2e-16

Total hospital cost

936

392976714

424408629

2094

136608825

169943309

< 2.2e-16

Total hospital revenues

936

417498875

457483256

2094

145244082

184064399

< 2.2e-16

Hospital net benefit

936

24522169

52182871

2094

8635291

30582257

< 2.2e-16

Available Medicare days

929

28825.6

24287.36

2086

11626.08

13979.94

< 2.2e-16

Available Medicaid days

929

10372.87

13102.66

2056

3057.124

5538.334

< 2.2e-16

Total Hospital Discharge

929

16649.56

13564.48

2088

6345.484

7654.591

< 2.2e-16

Medicare discharge

929

5571.574

4247.162

2086

2455.252

2773.352

< 2.2e-16

Medicaid discharge

929

2011.146

2310.712

2050

723.5776

1227.923

< 2.2e-16

(Note: Master RStudio script is available for this exercise, but you need to modify that for this analysis)

Week 3 & 4, Exercise:

The dataset provides Herfindahl–Hirschman Index, and herfindahel index categories, please use the herf_cat variable and answer the following questions:

Note: “The Herfindahl–Hirschman Index is a commonly accepted measure of market concentration used by antitrust enforcement agencies and scholars in the field. The HHI is calculated by squaring the market share of each firm competing in the market and then summing the resulting numbers” (NASI, 2015; pp: 14-16). read more from here:

https://www.urban.org/sites/default/files/publication/50116/2000212-Addressing-Pricing-Power-in-Health-Care-Markets.pdf

For this exercise you do not need to compute the HHI, but if you have any questions, please do not hesitate to ask me, but try to learn more about this you will need that to report your findings.

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

1) Compare the following information between hospitals located in high, moderate and low competitive markets? (table 1)

2) What are the main significant differences between hospitals in different markets? (use Anova test)

3) Use the density curves and compare hospitals cost and revenues between three markets.

4) What is the impact of being in high-competitive market on hospital revenues and cost? Do you think being in high-competitive market has positive impact on net hospital benefits? What about the number of Medicare and Medicaid discharge? Do you think hospitals in higher completive market more likely to accept more Medicare and Medicaid patients? What are the impact of other variables? Please discuss your findings in 1-2 paragraphs.

(Note: to answer to the last question, please compute the ratio-medicare-discharge and ratio-medicaid-discharge first and then run 2 ttest ) high vs. moderate and high vs. low competitive market), please support your findings with box-plot).

Table 3. Comparing hospital characteristics and market, 2011 and 2012

Variables

High Competitive Market

Moderate Competitive Market

Low Competitive

Market

ANOVA (results)

N

Mean

STD

N

Mean

STD

N

Mean

STD

Hospital Characteristics

Hospital beds

Number of paid Employee

Number of non-paid Employee

Internes and Residents

System Membership

Total hospital cost

Total hospital revenues

Hospital net benefit

Available Medicare days

Available Medicaid days

Total Hospital Discharge

Medicare discharge

Medicaid discharge

Herfindahel index

(Note: Master RStudio script is available for this exercise, but you need to modify that for this analysis)

01

0e+00

1e+09

2e+09

3e+09

Figure 1. Boxplot of Hospital Costs for teaching & Non-teaching hospitals

Teaching/Non-Teaching

Hospital Costs

01

0e+00

1e+09

2e+09

3e+09

4e+09

Figure 1. Boxplot of Hospital Revenues for teaching & Non-teaching hospitals

Teaching/Non-Teaching

Hospital Revenue

Week 1, Exercise:

The attached dataset, provides some information about hospitals in 2011 and 2012, download the data and then

complete the descriptive table. Please use the following format to report your findings.

Table 1. Descriptive statistics

between hospitals in 2011 & 2012

Variables

2011

2012

p

-

value

N

Mean

St. Dev

N

Mean

St. Dev

Hospital beds

1505

376.6086

560.8998

1525

376.8

579.8366

< 2.2e

-

16

Number of paid Employee

1498

1237.276

1615.797

1515

1491.121

1961.637

< 2.2e

-

16

Number of

non

-

paid

Employee

30

39.973

72.58805

30

44.76976

81.29861

6.653e

-

05

Total hospital cost

1505

216873322

304570722

1525

214748023

294143536

< 2.2e

-

16

Total hospital revenues

1505

228706319

323339811

1525

229978391

321273114

< 2.2e

-

16

Available Medicare

days

1499

16739.16

19214.29

1516

17110.14

19765.74

< 2.2e

-

16

Available Medicaid days

1484

5301.199

9207.699

1501

5366.333

9340.373

<

2.2e

-

16

Total Hospital Discharge

1500

9492.326

10898.6

1517

9544.051

10994.17

< 2.2e

-

16

Medicare discharge

1499

3230.624

3388.957

1516

3598.248

3785.675

< 2.2e

-

16

Medicaid discharge

1481

1130.727

1757.158

1498

1119.547

1740.423

< 2.2e

-

16

Based on your findings in which years hospitals had better performance? Please write a short paragraph and

describe your findings.

The hospitals had better performance in 2012 compared to 2011. The mean number of

hospital beds in 2012 was slightly higher than the mean number of hospital beds in 2011. In terms of revenue,

the mean revenue in 2012 was higher than the mean revenue in 201

1. The total cost in 2011 was also higher

than the total cost in 2012. For these variables, the p.value is less than 0.05 hence the null hypothesis is not

rejected at 95% confidence interval. This implies that the means between the two groups are

not

diffe

rent.

(Note: Master RStudio script is available for this exercise, but you need to modify that for this analysis)

Week 1, Exercise:

The attached dataset, provides some information about hospitals in 2011 and 2012, download the data and then

complete the descriptive table. Please use the following format to report your findings.

Table 1. Descriptive statistics between hospitals in 2011 & 2012

Variables 2011 2012 p-value

N Mean St. Dev N Mean St. Dev

Hospital beds 1505 376.6086 560.8998 1525 376.8 579.8366 < 2.2e-16

Number of paid Employee 1498 1237.276 1615.797 1515 1491.121 1961.637 < 2.2e-16

Number of non-paid

Employee

30 39.973 72.58805 30 44.76976 81.29861 6.653e-05

Total hospital cost 1505 216873322 304570722 1525 214748023 294143536 < 2.2e-16

Total hospital revenues 1505 228706319 323339811 1525 229978391 321273114 < 2.2e-16

Available Medicare days 1499 16739.16 19214.29 1516 17110.14 19765.74 < 2.2e-16

Available Medicaid days 1484 5301.199 9207.699 1501 5366.333 9340.373 < 2.2e-16

Total Hospital Discharge 1500 9492.326 10898.6 1517 9544.051 10994.17 < 2.2e-16

Medicare discharge 1499 3230.624 3388.957 1516 3598.248 3785.675 < 2.2e-16

Medicaid discharge 1481 1130.727 1757.158 1498 1119.547 1740.423 < 2.2e-16

Based on your findings in which years hospitals had better performance? Please write a short paragraph and

describe your findings. The hospitals had better performance in 2012 compared to 2011. The mean number of

hospital beds in 2012 was slightly higher than the mean number of hospital beds in 2011. In terms of revenue,

the mean revenue in 2012 was higher than the mean revenue in 2011. The total cost in 2011 was also higher

than the total cost in 2012. For these variables, the p.value is less than 0.05 hence the null hypothesis is not

rejected at 95% confidence interval. This implies that the means between the two groups are not different.

(Note: Master RStudio script is available for this exercise, but you need to modify that for this analysis)