The CFO at General Hospital noticed

The CFO at General Hospital noticed that the losses for Medicare heart failure (HF) patients were becoming larger each year. In order to understand why this is occurring, he assigned a data analyst to review the issue. The analyst requested a file including the following billing information for each case in grouping to one of the HF MS-DRGs (291, 292, 293):

Data Element	Definition
Patient	Patient ID
LOS	Length of Stay
Age	Patient Age Category
Sex	Patient Gender
AmtReim	Amount Paid by Medicare
TotAccomChg	Total Accommodation Charges
TotDeptChg	Total Departmental Charges
NumDxCodes	Number of Diagnosis Codes on Claim
admsrc	Admission Source
dischdest	Discharge Destination
drgcode	MS-DRG Code

The analyst immediately notices that the data documentation or dictionary supplied with the data does not include some critical elements. The first step in the analysis will be finding the coded values for the following variables: age category, gender, admission source, discharge destination. The analyst knows that the IT department follows the standard UB-04 codes for admission source and discharge destination and the CMS MedPAR standard for patient gender and age categories.

The goal of the study is to answer the following questions: (40 points)

1. What is the typical loss per HF patient? Assume that the cost to charge ratio (CCR) for General Hospital is 0.3 for ancillary departments and 0.5 for accommodation departments.
   1. Instructions for calculating profit:
      1. Profit/loss = amtreim – cost
      2. Cost may be estimated by taking the charge times the CCR

• Create a column (M) called Cost = =F2*.5+G2*.3 (where column F is accommodation charges and column G is ancillary or departmental charges)

1. Copy this column to all rows
2. Create a column (N) called Profit = amtreim – cost
3. Copy this column to all rows

2. Does General Hospital have any profitable HF patients? If so, can you describe those patients? (20 points)
3. How does the mix of no CC/CC/MCC patients compare to the national mix from the HCUP database? How might that impact the profitability of the HF patients? (20 points)

If you are not already familiar with HCUP data, please access http://hcupnet.ahrq.gov/ which is where you can access benchmark data on HF DRGs.