Hello there. You might not believe me right away, but I hope to convince you quickly that analytical groupers or software that puts codes or patient records into simpler categories will often be your best friends. Groupers are powerful because they can immediately solve problems for you. There have been many times in my career that doctors, researchers, or administrators tell me to identify a population with let's say disease X, who experienced treatment Y and then they were given drug Z. But general categories are useless in the database world. Diseases, treatments, and drugs are coded by tens of thousands of codes. The people requesting the information often understand the medical concepts, but they often are not coding experts who can provide all of the codes and database fields. So here, the groupers come to the rescue. An analyst can show the requester, the grouper categories. Once they selects the ones they want, it is easy to extract data based on the codes that have been matched to the more general groups. In sum, when you are overwhelmed by the details of health data, find help from groupers. This module has a number of lessons to introduce the importance of groupers. First, I'll introduce groupers and review the importance of groupers within healthcare analytics. Thus, I will briefly address the questions; what are groupers? Why are groupers useful? Next, I'll review open source grouper systems. Some of these algorithms are extremely valuable, given they are free and they can help you group complex codes into actionable groups. Finally, I will discuss the benefits and costs associated with commercial groupers. These grouper tools usually must be licensed for a fee, but given all the powerful analytical work that they can help you with, it may be worth your organization's time and money to invest in such tools. Overall, in my experience, I found the groupers to be one of the most important aspects of my work. I encourage you to think about these tools in your own work.