SAS Programming with Medicare Administrative Data. Matthew Gillingham

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SAS Programming with Medicare Administrative Data - Matthew Gillingham

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Note on the Source and Structure of Our Claims Data

       Part B Carrier Claims Data

       Durable Medical Equipment (DME) Data

       Outpatient Claims Data

       Inpatient Claims Data

       Skilled Nursing Facility (SNF) Claims Data

       Home Health Claims Data

       Hospice Claims Data

       Commonly Retained Elements in Administrative Claims Data

       Master Beneficiary Summary File

       Provider Data

       Example: Identification of Emergency Department (ED) Utilization

       Example: Identification of Surgical Services

       Chapter Summary

      This chapter introduces the contents of the Medicare claims and enrollment files we will use for our research programming project. The purpose of this introduction is to build on the explanation of the Medicare program presented in Chapter 2 and further prepare the programmer for using Medicare administrative data to complete our example research programming project. In Chapter 2, we learned the basics of the administration of the Medicare program. We defined Medicare, discussed enrollment, eligibility, and coverage, and provided a very simple sketch of how Medicare pays for services. We also briefly discussed how this information about Medicare influences the content of the data files used throughout the remainder of this book. In this chapter, we will build on those concepts and dive into each Medicare file we will be using for our example research programming project.1 We will review the contents of each data set, including examples of information commonly pulled out of each file for research purposes. We will end with an example of how to use the datasets to identify services provided for a surgery and services provided for a visit to the emergency department.2 Through these examples, we will see that the contents of each file are not always intuitive. Rather, the contents of each file are governed by how the services are billed and paid. We will learn to be cognizant of certain quirks, like the fact that not all services performed in an inpatient hospital appear in the inpatient claims data set. Looking forward, in Chapter 4, we will build on the information presented in this chapter by planning our programming project and, in Chapter 5, we will request the data described in this chapter. In subsequent chapters, we will actually use these data to address the research questions posed by our example project described in Chapter 1. For example, we will load and transform our claims files in Chapter 5, and calculate utilization of services in Chapter 7.

      Before going into detail about the content of the Medicare administrative claims and enrollment data we will be working with, let’s frame our discussion by identifying the source of our data and the structure of the files we will pretend to request, receive, and work with to complete our project.3 It is important to introduce this conversation now because Medicare data can come from a variety of sources and each source stores and provides the data somewhat differently.

      We will explore this topic in much more detail in Chapter 5, but for now it is important to know that, depending on our source of funding and the nature of our project, we could choose from at least four data sources:

      CMS’s data distribution contractor (sometimes referred to as the Research Data Distribution Center)

      CMS’s Data Extract System (DESY)

      CMS’s Virtual Research Data Center (VRDC) system

      CMS’s Integrated Data Repository (IDR)

      For our purposes, we will assume that we will work with CMS’s Research Data Assistance Center (ResDAC) and CMS’s data distribution contractor to request and obtain our data.4

      Medicare claims data created for research purposes are provided by CMS’s data distribution contractor separately by claim type. In other words, separate sets of files are provided for final action non-institutional (Part B carrier and durable medical equipment) and institutional (outpatient, inpatient, skilled nursing facility, home health, and hospice) services. CMS further separates data for each claim type into separate files for base claim and claim line (in the case of the set of non-institutional data files) or revenue center (in the case of the set of institutional data files) detail, resulting in seven sets of files.5

      The base claim detail (also known as header-level information) is basically summary information, including information that identifies the claim, the beneficiary who received care, the provider of service, the beginning and ending dates for the services billed on the claim, the diagnoses on the claim, and the total amount paid to the provider as reimbursement for the services performed. The claim line detail (sometimes generally referred to as line-level information) is a set of in-depth information about the specific services performed. For example, a line will contain a beginning and ending date of services, the patient’s diagnoses (represented by diagnosis codes), the services performed (represented by procedure codes), payment amounts for the services, and the identifier of the provider that performed each service. In a SAS dataset, the claim is spread across multiple records with one record per service rendered.

      In Chapter 5, we will transform these separate files to contain all claim- and line-level information in a single record. In other words, we will take the file with multiple records per claim and construct arrays on a single record to represent each of the line-items. This maneuver is not something you would do in your own research programming but, as we will discuss, the advantage is that we can work with a structure of claims data sets that can be created using data from any of the three sources. As such, this transformation “levels the playing field” and makes the remainder of the book accessible to a broader audience. In addition, such a structure just happens to be my preferred method of working with claims data because it affords the opportunity to see the entire paid claim in one record! Because such a transformation can consume valuable resources, more advanced readers should determine for themselves the most efficient way to structure their claims data.

      Carrier claims data contain claims information filed by non-institutional providers using the CMS-1500 claim form. When a Medicare beneficiary

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