Therefore, we must acquire enrollment and claims data for these beneficiaries, and subsequently develop algorithms that will query the data to produce summaries of payment, utilization, and quality outcomes during the study year. These summaries will be used in our evaluation of the program.4
In the end, the goal of this text is not to make any real determinations about utilization, payments, and quality of care; after all, we are using fake data that cannot be used for drawing any real conclusions and exists solely to develop code.5 Rather, our goal is to prepare you for working on your own real world research projects by using our example research programming project to teach the mechanics of using Medicare data to measure utilization and Medicare payments, and to identify chronic conditions and commonly used indicators of quality outcomes. Therefore, by the end of this text, the reader will understand important concepts that are applicable and foundational to using Medicare administrative claims and enrollment data to, say, identify most any chronic condition or compute most any quality outcome metric.
We can now be more specific about the things we would like to measure. In particular, evaluating the success of the program involves coding the following measurements of utilization and payment for the beneficiaries in the pilot program we are studying. We need to:
• Calculate the number of evaluation and management (E&M) visits in a physician office setting, and the amount paid for those E&M services.
• Calculate measures of inpatient hospital utilization, and the amount paid for inpatient hospital claims.
• Calculate the utilization as it pertains to the professional component of emergency department (ED) visits.
• Calculate the utilization of ambulance services.
• Calculate the number of outpatient visits, as well as skilled nursing facilities (SNFs), home health agencies (HHAs), and hospice care.
• Calculate the total Medicare amount paid for all Part A claims for our population.
In addition, evaluating the success of the program also entails coding the following measurements of quality outcomes, often at the physician level:
• Measure evaluation and management utilization for beneficiaries with diabetes or chronic obstructive pulmonary disease (COPD).
• Identify the extent to which diabetics received services for eye exams.
• Calculate the number of hospital readmissions for beneficiaries with COPD.
• Finally, we will provide examples of methods to summarize and present results by beneficiary demographic characteristics, as well as by provider. While these examples are by no means exhaustive (e.g., we do not summarize and present every analysis performed in earlier chapters, we do not endeavor to analyze results using a control population, and we do not look for significant changes in performance over time), they do provide the reader with a foundation for further work.
The above concepts meet our criteria of being relevant, foundational, and adaptable. For example, instead of studying hospital admissions for Medicare beneficiaries with diabetes, you could study the same utilization and cost measurements for beneficiaries with prostate cancer. Similarly, you could adapt the measurement of retinal eye exams for diabetics to examine a different procedure (say, immunization for influenza) for beneficiaries with a different chronic condition (say, beneficiaries with prostate cancer or COPD).
Chapter Outline
Each chapter in this book will address a section of the project:
• Chapter 2 sets a foundation for using and understanding the data by learning about the Medicare program. Remember, the guiding principle of this book is that the only proper way to answer research questions about the Medicare program is by understanding the program that drives the data.
• Chapter 3 builds on the foundation developed in Chapter 2 by describing the content of Medicare data files in detail.
• Chapter 4 plans the project by describing the initiation, planning, and design phase of the Systems Development Life Cycle (SDLC).
• Chapter 5 covers requesting, obtaining, and loading the necessary data. In this chapter, we begin to work with our source data. This chapter marks the beginning of the discussion on the creation of the analytic files we will use to summarize our results and ultimately to answer our research questions.
• Chapter 6 defines beneficiary enrollment characteristics, including the creation of variables that indicate continuous enrollment, age, and geographic information.
• Chapter 7 presents code to calculate the aforementioned measurements of utilization.
• Chapter 8 presents code to calculate the aforementioned measurements of Medicare payment.
• Chapter 9 identifies common medical conditions by focusing on diabetes and COPD, and develops examples of basic measurements of quality outcomes for beneficiaries who have these conditions.
• Chapter 10 focuses on bringing the output of Chapter 5 through Chapter 9 together, using that output for answering the research questions, and presenting those answers. We will also discuss the steps involved in finalizing our work through documentation, preservation of code, and complying with all of CMS’s Data Use Agreement6 policies, such as the destruction of data.
As you can see, another way of presenting the organization of this book is to say that the first four chapters are not focused on writing SAS code. Rather, they are focused on learning about the Medicare program, Medicare data, CMS’s systems, and the unique process of planning a research programming project that utilizes Medicare administrative data. Again, this is intentional. It is significantly important that the reader acknowledge that one must understand the Medicare program in order to successfully work with Medicare data, and one must understand Medicare data in order to properly answer research questions with Medicare data. Therefore, the first four chapters set up a foundation for the remaining chapters, with the coding and the actual execution of answering our example research questions occurring in Chapter 5 through Chapter 10.
How to Use This Book
With this in mind, each reader will come to this book with different levels of programming experience and various levels of exposure to working with Medicare administrative data. I recommend the following approach based on the reader’s experience:
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