Date of Award


Document Type


Degree Name

Doctor of Philosophy (PhD)

Legacy Department

Applied Economics

Committee Member

Dr. David Willis, Committee Co-Chair

Committee Member

Dr. David Hughes, Committee Co-Chair

Committee Member

Dr. Patrick Gerard

Committee Member

Dr. Daniel Miller

Committee Member

Dr. William Bridges


The current method for calculating excess hospital readmission penalties does not incorporate measures of socioeconomic status, thereby leaving nonprofit teaching and safety net hospitals vulnerable to financial reimbursement penalties due to exogenously determined heterogeneous patient populations. The literature has shown that socioeconomically disadvantaged groups are readmitted to nonprofit teaching hospital's in higher proportions than more advantaged groups. Increased readmission to nonprofit teaching hospitals has been linked with cost shifting from those unable to pay to those with the ability to pay for medical care. Therefore, a new method for determining hospital excess readmission penalties is needed to reduce the incentive of cost shifting and penalize under-performing hospitals in a more justifiable way. The two objectives of this research are to demonstrate the differences among hospital readmission rates by hospital type, and to demonstrate how the current Hospital Readmission Reduction program penalizes nonprofit teaching hospitals for excess readmissions as a result of their exogenous patient mix. A proposed method of adjusting excess readmission penalty determination uses patient insurance status to proxy for socioeconomic status. Hospitals are then grouped into quintiles of similar distributions based on patient mix. The proposed method of calculating excess readmission penalties is applied to a database of hospital claims for acute myocardial infarction (AMI) patients in the state of South Carolina. Results of the proposed method are then compared to results from the existing Centers for Medicare and Medicaid Services (CMS) method of calculating excess readmission penalties. The collected empirical data is subsequently used to construct bootstrapped samples to re-estimate excess readmission penalty. The bootstrapped analysis showed the difference in same hospital readmission penalties between the two methods resulted in a 1.12% revenue reduction for nonprofit teaching hospitals and 0.22% reduction for non-teaching hospitals. As a result, controlling for hospital patient characteristics caused by exogenous patient mix is likely to reduce the degree of hospital cost shifting to private payers.



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