Exercise #4
If you have chosen to work with Excel, run the three linear regression models and complete the following tables using the dataset from week 1’s exercise.
Medicare and Medicaid Discharge Ratios: Medicare Discharges ÷ Total Hospital Discharges; Medicaid Discharges ÷ Total Hospital Discharges
Model 1:
Run a linear model to predict the impact of number of hospital beds (use bed-tot) on hospital net-benefit in teaching hospitals.
- Hospital Characteristics Coef. ST. ERR T Stat P-values Lower 95% Upper 95%
- Hospital beds
- R Square
(Limit all results to 2 decimal places max)
Model 2:
Run a linear model to predict the impact of number of hospital beds (use bed-tot) on hospital net-benefit in non-teaching hospitals.
- Hospital Characteristics Coef. ST. ERR T Stat P-values Lower 95% Upper 95%
- Hospital beds
- R Square
(Limit all results to 2 decimal places max)
Use the results from model 1 and model 2 and compare the results between teaching and non-teaching hospitals.
Model 3:
Now, include the Medicare and Medicaid discharge ratios 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%
- Hospital beds
- Medicare-discharge-ratio
- Medicaid-discharge-ratio
- R Square
(Limit all results to 2 decimal places max)
Model 4:
Now, include the Medicare and Medicaid discharge ratios 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%
- Hospital beds
- Medicare-discharge-ratio
- Medicaid-discharge-ratio
- R Square
(Limit all results to 2 decimal places max)
Based on your findings, recommend 3 policies to improve hospital performance. Make sure to use the final model for your recommendations.
