HMGT 400 Week 8 Assignment #4 Final Exam

ENV100T Week 4, MKT421T Week 3, MKT421 Week 2, RES720 Week6, RES720 Week5, RES720 Week4, RES720 Week3, RES720 Week2, RES720 Week1, MFCC556 Week 6, MFCC556 Week5, MFCC556 Week 5, MFCC556 Week4, MKT421T Week1, MFCC556 Week 4, MFCC556 Week3, MFCC556 Week 3, MFCC556 Week2, MFCC556 Week 2, MFCC556 Week 1, OPS350 Week 5, OPS350 Week 4, OPS350 Week 3, OPS350 Week 2, OPS350 Week 1, HRM300T Week 5, HRM300T Week 4, HRM300T Week 2, HRM300T Week 1, DOC741 Week 6, DOC741 Week 5, DOC741 Week 4, DOC741 Week 2, DOC741 Week1, DOC741 Week 1, HSN575 Week8, HSN575 Week 8, HSN575 Week 7, HSN575 Week 6, HSN575 Week 3, HSN575 Week 2, LDR531 Week4, NSG511 Week 6, MBA5001 Week 5, MBA5001 Week5, MBA5001 Week 4, MBA5001 Week4, MBA5001 Week 3, MBA5001 Week3, MBA5001 Week 2, MBA5001 Week2, MBA5001 Week1, MBA5001 Week 1, PSY211 Week 5, PSY211 Week 4, PSY211 Week 3, PSY211 Week 2, PSY211 Week 1, DOC720R Day3, BSA375 Week 5, BSA375 Week 4, BSA375 Week2, BSA375 Week 2, CMGT445 Week 5, CMGT445 Week 4, CMGT445 Week 3, CMGT445 Week 1, BSA412 Week 5, BSA412 Week5, BSA412 Week4, BSA412 Week 4, BSA412 Week 3, BSA412 Week2, BSA412 Week 2, BSA412 Week 1, CMGT420 Week 5, CMGT420 Week5, CMGT420 Week4, CMGT420 Week 4, CMGT420 Week 3, CMGT420 Week3, CMGT420 Week2, CMGT420 Week 2, RES710 Week8, RES710 Week7, RES710 Week6, RES710 Week5, RES710 Week4, RES710 Week3, RES710 Week2, LDR711A Week 7, LDR711A Week 5, LDR711A Week 3, CPMGT300 Week 5, LAW531T Week 6, LAW531T Week 5, LAW531T Week 4, LAW531T Week 3, LAW531T Week 2, ISCOM383 Week 4, ISCOM383 Week 3, ISCOM383 Week 2, ISCOM383 Week 1, HRM531 Week 2, CNSL556 Week 3, CNSL556 Week 2, STR581 Week 6, STR581 Week3, HSN565 Week5, MGT312T Week 5, MGT312T Week 4, MGT312T Week 3, FIN571 Week 5, LDR726 Week8, LDR726 Week 8, LDR726 Week 7, LDR726 Week 6, LDR726 Week4, LDR726 Week 5, LDR726 Week 4, LDR726 Week 2, LDR726 Week 1, CCMH515CA Week 8, CCMH515CA Week6, CCMH515CA Week 6, CCMH515CA Week 4, CCMH515CA Week 3, CCMH515CA Week 2, CCMH515CA Week 1, LEA5125 Week 1, ENT588 Week 3, CCMH548 Week 6, CCMH548 Week6, CCMH548 Week5, CCMH548 Week 5, CCMH548 Week 3, CCMH548 Week 2, CCMH548 Week 1, CCMH544 Week 8, CCMH544 Week 7, CCMH544 Week 6, CCMH544 Week 5, CCMH544 Week 4, CCMH544 Week 3, CCMH544 Week 2, CCMH544 Week 1, GEN480 Week 5, GEN480 Week4, GEN480 Week 4, GEN480 Week 3, GEN480 Week 2, GEN480 Week1, GEN480 Week 1, ACC492 Week 5, ACC492 Week5, ACC492 Week 4, ACC492 Week4, ACC492 Week3, ACC492 Week 3, ACC492 Week 2, ACC492 Week2, ACC492 Week1, OPS571 Week1, OPS571 Week 2, OPS571 Week3, OPS571 Week4, OPS571 Week 6, REL133 Week4, REL133 Week3, REL133 Week2, REL133 Week1, HUM150 Week 5, HUM150 Week 4, HUM150 Week 3, HUM150 Week 1, HUM150 Week 2, HSN570 Week 5, HSN570 Week 4, HSN570 Week 3, HSN570 Week 2, HSN570 Week 1, HSN565 Week 6, HSN565 Week 5, HSN565 Week 3, HSN565 Week 2, HSN565 Week 1, MGT420 Week 5, MGT420 Week 3, MGT420 Week 1, DOC720R Day 3, DOC720R Day 2, DOC720R Day 1, RES710 Week 8, RES710 Week 7, RES710 Week 6, RES710 Week 5, RES710 Week 4, RES710 Week 3, RES710 Week 2, RES710 Week 1, RES709 Week 8, RES709 Week 7, RES709 Week 6, RES709 Week 5, RES709 Week 4, RES709 Week 3, RES709 Week 2, RES709 Week 1, COMM110 Week5, COMM110 Week 2, COMM110 Week1, COMM400 Week 5, COMM400 Week4, COMM400 Week 4, COMM400 Week 2, COMM400 Week1, COMM400 Week 1, CPMGT305 Week 5, CPMGT305 Week 4, CPMGT305 Week 3, CPMGT305 Week 2, CPMGT305 Week 1, CPMGT302 Week 5, CPMGT302 Week 4, CPMGT302 Week 3, CPMGT302 Week 2, CPMGT302 Week 2, CPMGT302 Week 1, CPMGT301 Week 5, CPMGT301 Week 4, CPMGT301 Week 2, CPMGT301 Week 1, GBM380 Week 4, GBM380 Week 2, QNT351 Week 1, ETH316 Week 3, ETH316 Week2, ETH316 Week 2, ETH316 Week 1, DOC788 Week 2, DOC788 Week 1, LDR736 Week 8, LDR736 Week 7, LDR736 Week 6, LDR736 Week 4, LDR736 Week 3, LDR736 Week 2, LDR736 Week 1, DOC723 Week 6, DOC723 Week 5, DOC723 Week 4, DOC723 Week 3, DOC723 Week 2, DOC723 Week 1, ORG727 Week 8, ORG727 Week 5, ORG727 Week 4, ORG727 Week 3, ORG727 Week 2, ORG727 Week 1, MGT726 Week 7, MGT726 Week 4, MGT726 Week 3, MGT726 Week 1, RES720 Week 8, RES720 Week 7, RES720 Week 6, RES720 Week 5, RES720 Week 4, RES720 Week 3, RES720 Week 2, RES720 Week 1, MHA516 Week 6, MHA516 Week 5, MHA516 Week 4, MHA516 Week 3, MHA516 Week 2, MHA505 Week 6, MHA505 Week 5, MHA505 Week 4, MHA505 Week 3, MHA505 Week 2, CCMH535 Week 6, CCMH535 Week 4, CCMH535 Week 2, CCMH535 Week 1, CCMH525 Week 7, CCMH525 Week 6, CCMH525 Week 4, CCMH525 Week 3, CCMH525 Week 2, CCMH525 Week 1, CCMH551 Week 6, CCMH551 Week 5, CCMH551 Week 4, CCMH551 Week 3, CCMH551 Week 2, CCMH551 Week 1, HCS499 Week 4, HCS499 Week3, HCS499 Week 3, HCS499 Week 2, ENG313 Week 2, ENG313 Week1, ENG313 Week 1, PSY420 Week5, PSY420 Week 5, PSY420 Week 4, PSY420 Week3, PSY420 Week 3, PSY420 Week 2, PSY420 Week 1, PSY410 Week 5, PSY410 Week 3, PSY410 Week 2, PSY410 Week1, PSY410 Week 1, MKT440 Week 5, MKT440 Week 4, MKT440 Week 3, MKT440 Week 1, MGT373 Week 5, MGT373 Week 4, MGT373 Week 3, MGT373 Week 2, MGT373 Week 1, MGT411 Week 5, MGT411 Week 3, MGT411 Week 2, MGT411 Week 1, OPS571 Week 5, OPS571 Week 4, OPS571 Week 1, MKT593 Week 4, MKT593 Week 2, MKT593 Week 1, MKT562 Week 4, MKT562 Week 3, MKT562 Week 2, MKT562 Week 1, MKT544 Week 5, MKT544 Week 4, MKT544 Week 3, MKT544 Week 1, MKT554 Week 4, MKT554 Week 2, MKT554 Week 1, GLG220 Week5, GLG220 Week4, GLG220 Week2, GLG220 Week1, ENT588 Week5, ENT588 Week 5, ENT588 Week 4, ENT588 Week3, ENT588 Week2, ENT588 Week1, MFCC551CA Week8, MFCC551CA Week7, MFCC551CA Week6, MFCC551CA Week5, MFCC551CA Week4, MFCC551CA Week3, MFCC551CA Week2, MFCC551CA Week1, CCMH506 Week7, CCMH506 Week6, CCMH506 Week5, CCMH506 Week4, CCMH506 Week3, CCMH506 Week2, CCMH506 Week1, CCMH504 Week6, CCMH504 Week5, CCMH504 Week4, CCMH504 Week1, CCMH510 Week5, CCMH510 Week3, CCMH510 Week2, CCMH510 Week1, FIN571 Week5, FIN571 Week2, BIS221T Week 5, ENV100T Week 2, ENG223 Week5, ENG223 Week4, ENG223 Week3, ENG223 Week 2, ENG223 Week2, ENG223 Week1, PHL458 Week5, PHL458 Week4, PHL458 Week3, PHL458 Week2, PHL458 Week1, HST175 Week5, HST175 Week4, HST175 Week3, HST175 Week2, HST175 Week1, POL115 Week 3, POL115 Week1, POL115 Week2, HUM105 Week3, HUM105 Week2, HUM105 Week1, SOC100 Week4, SOC100 Week3, SOC100 Week2, SOC100 Week1, PSY203 Week 5, PSY203 Week4, PSY203 Week 4, PSY203 Week3, PSY203 Week 3, PSY203 Week 2, PSY203 Week 1, FIN486 Week4, FIN486 Week 2, SCI201 Week2, SCI201 Week 1, SCI201 Week1, FIN366 Week5, FIN366 Week 5, FIN366 Week4, FIN366 Week 4, FIN366 Week3, FIN366 Week 3, FIN366 Week2, FIN366 Week 2, FIN366 Week1, FIN366 Week 1, FIN419 Week 1, ISCOM476 Week5, ISCOM476 Week3, ISCOM374 Week 5, ISCOM374 Week4, ISCOM374 Week 3, ISCOM374 Week3, ISCOM374 Week2, ISCOM473 Week5, ISCOM473 Week4, ISCOM473 Week2, ISCOM473 Week1, ISCOM424 Week5, ISCOM424 Week4, ISCOM424 Week3, ISCOM424 Week 2, ISCOM424 Week2, ISCOM424 Week1, ARTS125 Week5, ARTS125 Week3, ARTS125 Week2, ARTS125 Week1, HRM498 Week5, HRM498 Week4, HRM498 Week3, HRM498 Week 2, HRM498 Week2, HRM498 Week1, BIS221T Week2, BIS221T Week1, MTH216 Week3, MTH216 Week2, PSY405 Week5, PSY405 Week 3, PSY405 Week3, PSY405 Week2, PSY405 Week1, PSY110 Week 5, PSY110 Week 4, PSY110 Week 3, PSY110 Week2, PSY110 Week1, CJS201 Week 2, CJS201 Week5, CJS201 Week4, CJS201 Week3, CJS201 Week2, CJS201 Week1, ACC491 Week5 team, ACC491 Week5, ACC491 Week 4, ACC491 Week4, ACC491 Week 3, ACC491 Week3, ACC491 Week 1, ACC491 Week1, ECO365 Week1, COMM315 Week5, COMM315 Week4, COMM315 Week3, COMM315 Week2, COMM315 Week1, SOC262 Week5, SOC262 Week4, SOC262 Week3, SOC262 Week2, SOC262 Week1, MGT230 Week 5, MGT230 Week 4, MGT230 Week5, MGT230 Week4, MGT230 Week3, MGT230 Week2, MGT230 Week1, MKT421 Week5, MPA533 Week 5, MPA533 Week 4, MPA533 Week 3, HRM310 Week 5, HRM310 Week5, HRM310 Week4, HRM310 Week3, HRM310 Week2, HRM310 Week1, HRM324 Week5, HRM324 Week4, HRM324 Week3, HRM324 Week2, HRM324 Week1, MGT418 Week 5, MGT418 Week5, MGT418 Week4, MGT418 Week3, MGT418 Week2, MGT418 Week 1, MGT418 Week1, HSN560 Week6, HSN560 Week5, HSN560 Week4, HSN560 Week3, HSN560 Week2, HSN560 Week1, FIN422 Week 5, FIN422 Week 4, FIN422 Week5, FIN422 Week4, FIN422 Week3, FIN422 Week2, FIN422 Week1, FIN402 Week5, FIN402 Week4, FIN402 Week3, FIN402 Week2, FIN402 Week1, IT200 Week 4, IT200 Week5, IT200 Week4, IT200 Week3, IT200 Week2, IT200 Week 1, GEO180 Week 4, GEO180 Week5, GEO180 Week4, GEO180 Week3, GEO180 Week 2, GEO180 Week2, GEO180 Week1, ISCOM305 Week 5, ISCOM305 Week5, ISCOM305 Week 2, GEN201 Week 5, GEN201 Week 4, GEN201 Week 3, MGT445 Week5, MGT445 Week4, MGT445 Week3, MGT445 Week2, MGT445 Week1, MPA533 Week 6, MPA533 Week5, MPA533 Week2, MPA593 Week6, MPA593 Week5, MPA593 Week4, MPA593 Week3, MPA593 Week2, MPA593 Week1, MPA583 Week6, MPA583 Week5, MPA583 Week4, MPA583 Week3, MPA583 Week2, MPA583 Week1, MPA563 Week6, MPA563 Week5, MPA563 Week4, MPA563 Week3, MPA563 Week2, MPA563 Week1, PSY360 Week5, PSY360 Week4, PSY360 Week3, PSY360 Week2, PSY360 Week1, HM475 Week 4, HM475 Week5, HM475 Week4, HM475 Week3, HM475 Week2, HM475 Week1, MPATM543 Week6, MPATM543 Week5, MPATM543 Week4, MPATM543 Week3, MPATM543 Week2, MPATM543 Week1, MPA573 Week 3, MPA573 Week6, MPA573 Week5, MPA573 Week4, MPA573 Week3, MPA573 Week2, MPA573 Week1, MPA543 Week6, MPA543 Week5, MPA543 Week4, MPA543 Week3, MPA543 Week2, MPA543 Week1, HRMPA533 Week6, HRMPA533 Week5, HRMPA533 Week4, HRMPA533 Week3, HRMPA533 Week2, HRMPA533 Week1, LAWPA513 Week 5, LAWPA513 Week6, LAWPA513 Week5, LAWPA513 Week4, LAWPA513 Week3, LAWPA513 Week2, LAWPA513 Week1, HSN525 Week8, HSN525 Week7, HSN525 Week6, HSN525 Week5, HSN525 Week4, HSN525 Week3, HSN525 Week2, HSN525 Week1, NSG550 Week6, NSG550 Week5, NSG550 Week4, NSG550 Week3, NSG550 Week2, NSG550 Week1, MPA533 Week6, MPA533 Week5, MPA533 Week4, MPA533 Week3, MPA533 Week2, MPA533 Week1, NSG513 Week6, NSG513 Week5, NSG513 Week4, NSG513 Week3, NSG513 Week2, NSG513 Week1, NSG512 Week 6, NSG512 Week6, NSG512 Week5, NSG512 Week4, NSG512 Week3, NSG512 Week2, NSG512 Week1, NSG511 Week6, NSG511 Week5, NSG511 Week4, NSG511 Week3, NSG511 Week2, NSG511 Week1, HCS529 Week5, HCS529 Week4, HCS529 Week3, HCS529 Week2, HCS529 Week1, HCS535 Week6, HCS535 Week5, HCS535 Week4, HCS535 Week3, HCS535 Week2, HCS535 Week1, HCS552 Week6, HCS552 Week5, HCS552 Week4, HCS552 Week3, HCS552 Week2, HCS552 Week1, PSY340 Week 2, PSY340 Week5, PSY340 Week4, PSY340 Week3, PSY340 Week2, PSY340 Week1, PSY335 Week 2, PSY335 Week5, PSY335 Week4, PSY335 Week3, PSY335 Week2, PSY335 Week1, ETH120 Week5, ETH120 Week4, ETH120 Week 4, ETH120 Week2, ETH120 Week1, DOC705R Day 2, DOC705R Day5, DOC705R Day4, DOC705R Day3, DOC705R Day2, DOC705R Day1, MGT314 Week5, MGT314 Week4, MGT314 Week 4, MGT314 Week2, MGT314 Week1, SOC333 Week 1, SOC333 Week5, SOC333 Week4, SOC333 Week3, SOC333 Week2, SOC333 Week1, PSY310 Week 5, PSY310 Week5, PSY310 Week4, PSY310 Week3, PSY310 Week2, PSY310 Week1, PSY305 Week5, PSY305 Week4, PSY305 Week3, PSY305 Week2, PSY305 Week1, COMM102 Week5, COMM102 Week4, COMM102 Week3, COMM102 Week2, COMM102 Week1, PSY245 Week 4, PSY245 Week 3, PSY245 Week5, PSY245 Week4, PSY245 Week3, PSY245 Week2, PSY245 Week1, PSY215 Week 5, PSY215 Week5, PSY215 Week4, PSY215 Week3, PSY215 Week2, PSY215 Week1, MPA553 Week6, MPA553 Week5, MPA553 Week4, MPA553 Week3, MPA553 Week2, ACC574 Week6, ACC574 Week5, ACC574 Week4, ACC574 Week3, ACC574 Week2, ACC574 Week1, QNT562 Week6, QNT562 Week5, QNT562 Week4, QNT562 Week3, QNT562 Week2, QNT562 Week1, BIS320 Week 4, BIS320 Week 3, BIS320 Week5, BIS320 Week4, BIS320 Week3, BIS320 Week2, BIS320 Week1, PSY250 Week1, PSY250 Week5, PSY250 Week4, PSY250 Week3, PSY250 Week2, LTC310 Week5, LTC310 Week4, LTC310 Week3, LTC310 Week2, CPMGT300 Week5, CPMGT300 Week4, CPMGT300 Week3, CPMGT300 Week2, CPMGT300 Week1, SOC315 Week5, SOC315 Week4, SOC315 Week 3, SOC315 Week3, SOC315 Week2, SOC315 Week1, LTC328 Week5, LTC328 Week3, LTC328 Week2, LTC315 Week4, LTC315 Week3, LTC315 Week2, ACC561 Week6, ACC561 Week 3, ACC561 Week3, ACC561 Week2, ACC561 Week1, QRB501 Week4, QRB501 Week2, HCS433 Week3, HCS433 Week2, HCS437 Week5, HCS437 Week4, HCS437 Week3, HCS437 Week2, HCS465 Week5, HCS465 Week3, HCS465 Week 2, HCS465 Week2, HCS451 Week5, HCS451 Week3, HCS451 Week2, HCS483 Week4, HCS483 Week 4, HCS483 Week 3, HCS483 Week3, HCS457 Week 5, HCS457 Week5, HCS457 Week4, HCS490 Week5, HCS490 Week 4, HCS490 Week4, HCS490 Week2, HCS385 Week 5, HCS385 Week5, HCS385 Week4, HCS385 Week3, POL215 Week5, POL215 Week 3, POL215 Week2, POL215 Week1, HST206 Week 5, HST206 Week4, HST206 Week3, HST206 Week1, LDR531 Week6, LDR531 Week 5, LDR531 Week5, LDR531 Week4, LDR531 Week 3, LDR531 Week3, LDR531 Week2, LDR531 Week1, HRM531 Week5, HRM531 Week4, HRM531 Week2, HRM531 Week1, HST276 Week5, HST276 Week4, HST276 Week3, HST276 Week1, ENG135 Week4, ENG135 Week5, ENG135 Week3, ENG135 Week 3, ENG135 Week2, ENG135 Week1, SOC110 Week5, SOC110 Week4, CJA345 Week1, CJA345 Week2, CJA345 Week 2, CJA345 Week3, CJA345 Week 3, CJA345 Week4, CJA345 Week 4, CJA345 Week5, CJA345 Week 5, MGT448 Week 4, MGT448 Week 3, MGT448 Week5, MGT448 Week4, MGT448 Week3, MGT448 Week2, MGT448 Week1, ISCOM305 Week 4, ISCOM305 Week 3,ISCOM305 Week 2, ISCOM305 Week5, ISCOM305 Week4, ISCOM305 Week3, ISCOM305 Week2, ISCOM305 Week1, PSY280 Week4, PSY280 Week3, PSY280 Week2, PSY280 Week1, PSY280 Week5, PSY280 Week5, PSY225 Week 5, PSY225 Week 4, PSY225 Week5, PSY225 Week4, PSY225 Week3, PSY225 Week2

Question #1 (15 credits):[RStudio Users and Excel Users]

The FINAL EXAM dataset, provides some information about hospitals in 2011 and 2012, download the FINAL EXAM data and then complete the descriptive table. Please answer the following questions.

  1. In term of hospital characters what are the significant difference between 2011 and 2012?
  2. In term of socio-economic variables what are the significant difference between 2011 and 2012?

To report the “Per Capita Hospital Beds to Population”, you need to divide “total_hospital_beds/tot_population)

  1. Based on your findings in which years hospitals had better performance? How hospital performance related to hospital characteristics and socio-economic characteristics? Please write at least three main different movements between 2011 and 2012.

Table 1. Descriptive statistics between hospitals in 2011 & 2012

  2011 2012 p-value
N Mean St. Dev N Mean St. Dev
Hospital Characteristics              
1. Hospital beds   100     150   0.004
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. Hospital net benefit              
               
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 to Population              
15. Percent of population under poverty              
16. Percent of Female population under poverty              
17.  Percent of Male population under poverty              
18. Median Household Income              

 

 

 

Question #2 (15 credits): [RStudio Users and Excel Users]

Use the final exam dataset and then answer the following questions:

  • Compare the following information between for-profit and non-for-profit hospitals.
  • What are the main significant differences between for-profit and non-for-profit hospitals? Which test is the best fit test? Why?
  • Use a box-plot and compare Hospital net benefit between for-profit and non-for-profit hospitals.
  • Show another scatter plot and compare hospital cost (x-axes) and revenue (y-axes) and discuss your findings?
  • 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 FP and NFP hospitals.
  • Overall, what are the main significant differences between for-profit and non-for-profit hospitals?

Table 2. Descriptive statistics between FP & NFP

  For Profit Non-For-Profit p-value
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. Hospital net benefit              
               
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 to Population              
15. Percent of population under poverty              
16. Percent of Female population under poverty              
17.  Percent of Male population under poverty              
18. Median Household Income              

 

 

 

Question #3 (15 credits): [RStudio Users and Excel Users]

The dataset provides Herfindahl–Hirschman Index for health insurance market, please use the herf_ins variable and answer the following questions:

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.

Please remember for the class exercise you used the herf_cat as a hospital Herfindahl index. For this question make sure to use herf_ins as Herfindahl index for insurance market.

Use the final exam dataset and then answer the following questions:

  • In a short paragraph explain the Herfindahl index you can use the reference provided in the class exercise or any other citation.
  • Compare the following information between hospitals located in high, moderate and low competitive health insurance markets?
    • 1. What are the main significant differences between hospitals in different markets? (use Anova test)
    • 2. What is the impact of being in high-competitive health insurance market on hospital revenues and cost?
    • 3. Do you think being in high-competitive market has positive impact on net hospital benefits?
    • 4. 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?
    • 5. What is the impact of other variables?

(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

  High Competitive Market Moderate Competitive Market Low Competitive

Market

ANOVA/Chi-Sq (results)
Hospital Characteristics N Mean STD N Mean STD N Mean STD
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. Hospital net benefit                    
                     
9. Available Medicare days                    
10. Available Medicaid days                    
                     
11. Total Hospital Discharge                    
12. Medicare discharge-ratio                    
13. Medicaid discharge-ratio                    
Socio-Economic Variables                    
14. Per Capita Hospital Beds to Population                    
15. Median Household Income                    

 

 

Question #4 (Credits 20)- [RStudio Users]

Linear Regression Model

If you have chosen to work with RStudio, please run the following model and complete the following tables.

1st Model:

Run a linear model and predict the difference between hospital beds (use the bed-tot) and hospital’s ownership on hospital net-benefit? Discuss your finding, do you think having higher beds has positive impact on the hospital net benefit? What about the ownership?Benefit=F(b0+B1bed+b2Own2+B3ow2+b4own3+e)

  Model 1a  
Hospital Characteristics Coef. St. Err p-value
Hospital beds      
Ownership      
For Profit      
Non-for profit Ref. Ref. Ref.
Other      
N Df+K+1    
R-Squared      

 

2nd Model:

Now, estimate the impact of being a member of a system on hospital net benefit? And discuss your finding (not more than 2 lines)? Is it significant?

 

  Model 2  
Hospital Characteristics Coef. St. Err p-value
Hospital beds      
Ownership      
For Profit      
Non-for profit      
Other      
Membership      
System Membership      
N      
R-Squared      

 

3nd Model:

Now, include the ratio of ratio-Medicare-discharge and ratio-Medicaid-discharge in your model? How do you evaluate the impact of having higher Medicare and Medicaid patients on hospital net benefit?

 

  Model 3  
Hospital Characteristics Coef. St. Err p-value
Hospital beds      
Ownership      
For Profit      
Non-for profit      
Other      
Membership      
System Membership      
Socio-Economic Characteristics      
Medicare discharge ratio      
Medicaid discharge ratio      
N      
R-Squared      

 

Based on your finding please recommend 3 policies to improve hospital performance, please make sure to use the final model for your recommendation.

 

Discuss your findings.

 

 

 

Question #4 (Credits 20)- [Excel Users]

Linear Regression Model

If you have chosen to work with Excel, please run the models and complete the following tables.

Model 1:

Run a linear model and predict the difference between hospital beds (use the bed-tot) and hospital net-benefit in teaching hospitals?Note: hospital-net-benefit=total_hosp_revenue-total_hosp_costY(benefit), B0+B1(beds)

Hospital Characteristics Coef. ST. ERR T Stat P-values Lower 95% Upper 95%
Model-1            
Hospital beds            
N            
R Square            

 

Model 2:

Run a linear model and predict the difference between hospital beds (use the bed-tot) and hospital net-benefit in non-teaching hospitals?

Use the results from model 1 and model 2 and compare the results between teaching and non-teaching hospitals.

Hospital Characteristics Coef. ST. ERR T Stat P-values Lower 95% Upper 95%
Model-2            
Hospital beds            
N            
R Square            

 

Model 3:

Now, include the ratio of ratio-Medicare-discharge and ratio-Medicaid-discharge in first model? How do you evaluate the impact of having higher Medicare and Medicaid patients on hospital net-benefit in teaching hospitals?

Hospital Characteristics Coef. ST. ERR T Stat P-values Lower 95% Upper 95%
Model-3            
Hospital beds            
ratio-Medicare-discharge            
ratio-Medicaid-discharge            
N            
R Square            

 

Model 4:

Now, include the ratio of ratio-Medicare-discharge and ratio-Medicaid-discharge in first model? How do you evaluate the impact of having higher Medicare and Medicaid patients on hospital net-benefit in non-teaching hospitals?

 

Hospital Characteristics Coef. ST. ERR T Stat P-values Lower 95% Upper 95%
Model-4            
Hospital beds            
ratio-Medicare-discharge            
ratio-Medicaid-discharge            
N            
R Square            

 

Based on your finding please recommend 3 policies to improve hospital performance, please make sure to use the final model for your recommendation.

 

 

 

 

Question #5 (Credits 20) [RStudio Users]

If you have chosen to work with RStudio, please run three models and complete the following tables.

Model 1: Run a logit model and use being a member of network and find out its impact on hospital beds and hospital ownership? (Model 1)

Hospital Characteristics Coef. St. Err p-value
Hospital beds      
Ownership      
For Profit      
Non-for profit Ref.    
Other      
N      
AIC      

 

Model 2: Now, include hospital revenue and report the Coeff.? (Model 2)

Hospital Characteristics Coef. St. Err p-value
Hospital beds      
Ownership      
For Profit      
Non-for profit Ref.    
Other      
Hospital revenue      
N      
AIC      

 

Model 3: Now, include the ratio of ratio-Medicare-discharge and ratio-Medicaid-discharge in your model? And keep all variables you used for models 1, 2 & 3 and discuss your findings? Do you recommend keeping membership for a hospital? Why or why not? (Model 3)

Hospital Characteristics Coef. St. Err p-value
Hospital beds      
Ownership      
For Profit      
Non-for profit Ref.    
Other      
Hospital revenue      
Medicare discharge ratio      
Medicaid discharge ratio      
N      
AIC      

 

Based on your finding please recommend 3 policies to improve hospital performance in hospitals, please make sure to use the final model for your recommendation.

 

 

Question #5 (Credits 20)- [Excel users]

If you have chosen to work with Excel, please run above three models and complete the following tables.

Model 1: Run a regression model and use being a member of network and find out its impact on hospital cost? (Model 1)

  Coef. ST. ERR T Stat P-values Lower 95% Upper 95%
Model-1            
Hospital cost            
N            
R Square            

 

Model 2: For the 2nd model run a regressionmodel and use being a member of network and find out its impact on hospital cost and hospital revenue? (Model 2)

  Coef. ST. ERR T Stat P-values Lower 95% Upper 95%
Model-2            
Hospital cost            
Hospital Revenue            
N            
R Square            

 

Model 3: For the 3rd model run a regressionmodel and use being a member of network and find out its impact on ratio-Medicare-discharge and ratio-Medicaid-discharge.

  Coef. ST. ERR T Stat P-values Lower 95% Upper 95%
Model-3            
Hospital cost            
Hospital Revenue            
Medicare discharge ratio            
Medicaid discharge ratio            
N            
R Square            

 

Based on your finding please recommend 3 policies and discuss the impact of being on a network on hospital cost, hospital revenue and find out its impact on ratio-Medicare-discharge and ratio-Medicaid-discharge. Do you recommend keeping membership for a hospital? Why or why not?

 

 

Question 6: (15 credits) [RStudio Users and Excel Users]

Note: Please limit your answer for each question to maximum 2 paragraphs and make sure to support your findings with at least one citation – following APA 6.

  1. Please offer a research question for the study using human subject research.
  2. Explain the difference between the research process involving human subjects and the research process not involving human subjects.
  3. Discuss ethical implications surrounding human subject research studies.
  4. Explain the governance of the human subject research studies over the data and the process.
  5. Provide examples of the consequences for not meeting IRB (Institutional Review Board) protocol requirements.

 

 

Useful formula and guideline.

The computation of the p-value is illustrated in following figures.

 

 

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