hmgt 400 exercise 4
hmgt 400 exercise 4
Instructions
Download file from here: WeeklyExercise-Questions
Download data file from here: HMGT400HOSPITAL
Video: https://youtu.be/AT8BiEBqeVg
Instruction: Step-by-Step-Guideline
Video: https://youtu.be/AT8BiEBqeVg
Download codes from here: E4-Codes
Download codes from here without running DYPLR package:E-Codes-No-Dplyr
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.
Week 2, Exercise:
Use the dataset from week1 exercise and then answer the following questions:
- Compare the following information between teaching and non-teaching hospitals.
- What are the main significant differences between teaching and non-teaching hospitals? (use ttest)
- 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.
- 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)
- 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 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:
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:
- Compare the following information between hospitals located in high, moderate and low competitive markets? (table 1)
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 | 219 | 130.9178 | 386.1857 | 1332 | 420.5188 | 594.2665 | 1479 | 373.6403 | 562.2281 | F value=6.3724
P value=0.01164 |
| Number of paid Employee | 219 | 499.8935 | 813.2644 | 1324 | 1570.1115 | 1954.9221 | 1470 | 1308.9686 | 1722.4468 | F value=3.0271
P value=0.08198 |
| Number of non-paid Employee | 0 | Null | Null | 25 | 35.87832 | 30.50019 | 35 | 47.00928 | 97.11851 | F value=0.3055
P value=0.5826 |
| Internes and Residents | 22 | 38.32182 | 45.60323 | 423 | 112.20558 | 176.11024 | 480 | 86.55375 | 149.89660 | F value=1.9973
P value=0.1579 |
| System Membership | 219 | 0.4246575 | 0.4954233 | 1332 | 0.6073574 | 0.4885218 | 1479 | 0.6315078 | 0.4825590 | F value=21.572
P value=3.553e-06 |
| Total hospital cost | 219 | 73687086 | 121326585 | 1332 | 255520655 | 341985822 | 1479 | 201077823 | 267368743 | F value=0.83
P value=0.3623 |
| Total hospital revenues | 219 | 17.48018 | 1.029278 | 1332 | 18.71215 | 1.461939 | 1479 | 18.39917 | 1.627141 | F value=4.4126
P value=0.03576 |
| Hospital net benefit | 219 | 4013058 | 19021599 | 1332 | 15320472 | 39434375 | 1479 | 13353106 | 41078313 | F value=1.8043
P value=0.1793 |
| Available Medicare days | 219 | 5377.214 | 9993.885 | 1324 | 18983.776 | 20297.62 | 1472 | 16792.697 | 19219.182 | F value=12.292
P value=0.0004616 |
| Available Medicaid days | 217 | 1416.413 | 4429.091 | 1317 | 6553.995 | 10676.835 | 1451 | 4812.455 | 8164.626 | F value=0.0876
P value=0.7673 |
| Total Hospital Discharge | 219 | 2607.836 | 5065.392 | 1326 | 11100.959 | 11741.300 | 1472 | 9120.806 | 10397.483 | F value=6.1548
P value=0.01316 |
| Medicare discharge | 219 | 1067.938 | 1753.820 | 1324 | 3781.610 | 3652.702 | 1472 | 3435.407 | 3623.243 | F value=19.615
P value=9.81e-06 |
| Medicaid discharge | 217 | 309.8802 | 748.9359 | 1334 | 1324.1560 | 1961.7498 | 1448 | 1066.6464 | 1605.2900 | F value=2.4087
P value=0.1208 |
| Herfindahel index | 219 | 1.963470 | 0.1880338 | 1332 | 1.668919 | 0.6663497 | 1479 | 1.697769 | 0.6392140 | F value=9.3585
P value=0.002239 |
- What are the main significant differences between hospitals in different markets? (use Anova test)
Hypothesis statement
H0: There is no significant difference between the three competitive market levels
H1: There is a significant difference between the competitive market levels
The main significant difference among the three different markets are on variables Hospital beds, System membership, total hospital revenues, Available medical days, Total hospital discharge, Medicare discharge and Herfindahel index. On these 7 variables the P values are less than the level of significance of 0.05 in all cases, therefore we reject the null hypothesis and conclude that there is a significant difference in the three market levels on these 7 variables. On the rest on the variables the P value of the Anova tests is greater than the level of significance of 0.05 hence we do not reject the null hypothesis and therefore conclude that there is no significant difference.
- Use the density curves and compare hospitals cost and revenues between three markets.
For hospital cost as competition reduces the mean of the total hospital increases. This is evident by the decreasing frequency on figure 5.
For the hospital revenue, from the descriptive statistics it is clear high competitive have markets have the least revenue and moderate competitive markets have the greatest revenue. This has clearly been brought out by the distribution on figure 6.
- 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
In high competitive market both the total hospital cost mean and the total hospital revenue mean are lowest compared to the other two levels of market. This implies that” a high competitive market leads to low hospital cost and subsequent low revenue. This is despite the fact that Anova test shows that total hospital cost shows there is no significant difference in the three market levels while total hospital revenue shows a significant difference.
The mean net hospital benefit in high competitive market is 4,013,058, that of moderate competitive market is 15,320,472 and in low competitive market is 13,353,106. It is very clear that net hospital benefit is lowest in high competitive market from the mean. This implies that a high competitive market does not have a positive impact on the net hospital benefit. Despite this, there is no significant difference in net hospital benefit in the three competitive market levels.
The medicare discharge is lowest at the highest competitive market level(0) and greatest at moderate competition market level (1)
The medicaid discharge is lowest at the highest competitive market level (0) and greatest at moderate competition market level (1) although the difference in moderate competitive market level (1) and low competitive level (2) is minimal.
I believe hospitals in higher competitive market are more likely to accept more Medicare and Medicaid patients due to the low mean discharges at the high competitive market which implies there should be room to accept more Medicare and Medicaid discharges


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