Example of Wound Care Using Medpar Data

Example of Wound Care Using Medpar Data

DOI: 10.4018/978-1-61520-905-7.ch016
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Abstract

Medpar Data is used for billing Medicare; it typically is “packed” into different sheets of data. The first step required to use the data is to “unpack” it into its component sheets and then to merge the necessary data. Once that is finished, we can examine patients in sequence to investigate the total care of wounds, especially patients who have diabetic foot ulcers. This particular dataset was received from a clinic that specialized in the treatment of wounds. It contains detailed diagnosis information for inpatient and outpatient care. One of the problems is that there are two different coding sets that are used in the Medpar data. Inpatient data are coded using the ICD9 codes; outpatient data are coded using HCPCS codes. The advantage of such a dataset is that the wound care is highly concentrated within it, so that we can focus and drill down into wound care. The disadvantage is that the different coding systems have to be matched for analysis purposes. In this section, we want to look at the type of outpatient care prior to inpatient treatment, and to see if there is a progression of treatment that leads to better patient outcomes.
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Method

Medpar gives the billing information for Medicare. It is publicly available, although there can be a small cost affiliated with data acquisition. In fact, many of the public companies that define patient severity indices rely upon Medpar because it is so readily available. In addition, The Centers for Medicare and Medicaid maintain a data warehouse consisting of patients with a defined chronic disease, and this information, too, is available for a fee. There are multiple forms in Medicare data and we provide the SAS code on how to “unpack” the different forms for use in analysis. We are using the 2005 version of the data. The preprocessing to combine the data was given in Chapter 3. We need to unpack the different sheets of the Medpar data in order to use the information. Once that is done, we can first focus on the inpatient datasets.

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