TY - CHAP M1 - Book, Section TI - Overview of Analytic Techniques and Common Pitfalls A1 - Howell, Michael D. A1 - Stevens, Jennifer P. PY - 2020 T2 - Understanding Healthcare Delivery Science AB - The rest of this section of the book focuses on specific approaches to analyzing healthcare data: that is, how to use analytics to see the truth in the world so that you can improve patients’ health and healthcare. All these approaches, though, build on an understanding of several core principles about healthcare data. That is the focus of this chapter: These principles are important across all analytic techniques, and they represent issues that are easy to miss but can cause you to get the wrong answer if you don’t pay attention to them. Understanding these core concepts will help you select the right analytic method for the problem at hand. This chapter will introduce these core concepts, including data types (e.g., binary versus continuous), why missing data are critical, and the Four Horsemen of Mistaken Conclusions (chance, confounding, and bias — and violating the assumptions of your analytic method). It will also provide a brief overview for the analytic methods that will come in the following chapters. SN - PB - McGraw-Hill Education CY - New York, NY Y2 - 2024/03/29 UR - accesspharmacy.mhmedical.com/content.aspx?aid=1167644778 ER -