From the course: Designing Big Data Healthcare Studies, Part One

Definition of epidemiology - R Tutorial

From the course: Designing Big Data Healthcare Studies, Part One

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Definition of epidemiology

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- [Announcer] What is Epidemiology? Epidemiology is a set of tools for studying the three Ds, the distribution and determinants of disease. I recognize that Epidemiology is only one set of tools for designing studies. There are other sets of tools and concepts that can be used too. For example, Psychology takes a different approach conceptually than Epidemiology, and certainly Engineering, which does not study humans, has a different set of terminology around study design. But Epidemiological tools are the ones you want to use if you are actually studying disease or health, or anything to do with health care, because the tools in Epidemiology are specifically designed for that. In the three Ds, by distribution we mean where is the disease geographically and what subpopulations does it affect? How is it distributed among the population? By determinants, we are looking for causes of the disease. Is it caused by elements in the environment? Certain behaviors, certain genetics? Finally, we have disease. We say disease, but I admit this is a little outdated. Now, we use the term outcomes, but that ruins my three Ds thing, so I just say please think outcomes and not disease. You can have good and bad outcomes. In fact, you want good outcomes, so why not study those too? Outcomes are not always biological. For example, getting a mammogram may be an outcome we want as a result of a public health campaign, and while that's related to health care and it's a good thing, it's not biological. (grunts) Take it from someone who's had one, those women in that picture are just a little too happy. When I tell people I'm an Epidemiologist, what they generally first think of is foodborne illnesses or other acute, communicable diseases like flu or Ebola, even Bioterrorism. In fact, a lot of people think Epidemiology is mostly focused on these acute diseases. It's true that Epi has been in the spotlight over acute diseases, but actually there is really a lot more chronic disease Epidemiology which studies conditions like arthritis, pictured here, as well as diabetes, cardiovascular disease, and mental health disorders. It is also used for studying outcomes related to health and health care, like being able to afford health insurance, accessing treatment, receiving treatment, and getting screenings. But the dirty little secret is that you can use this set of tools for studying all kinds of things in data science, such as meeting certain marketing objectives and goal, or improving knowledge or awareness, or even the reputation of a company, process, or effort. I'm not kidding. Epidemiology is a super useful set of tools. All you need to do is know how to use them to study the outcome you want to study.

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