EXERCISE 3 AND 4
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:
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) |
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N |
Mean |
STD |
N |
Mean |
STD |
N |
Mean |
STD |
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Hospital Characteristics |
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Hospital beds |
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Number of paid Employee |
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Number of non-paid Employee |
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Internes and Residents |
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System Membership |
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Total hospital cost |
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Total hospital revenues |
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Hospital net benefit |
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Available Medicare days |
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Available Medicaid days |
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Total Hospital Discharge |
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Medicare discharge |
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Medicaid discharge |
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Herfindahel index |
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(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)