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.

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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)

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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:

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)

 

 

 

 

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

 

1. 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.

 

1. 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.

 

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

 

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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