Welcome back. In this video, we're going to be defining the space for this course on data management for clinical research. That means we'll be reviewing the basic concepts. What is data management? What is clinical research and what are they when you put them together. We'll also be talking about what topics we are going to cover in our lessons over the next two weeks. And what topics we are not going to cover in this course. First, we are going to review definitions of a few common concepts in clinical research. Including clinical research itself, clinical trials, observational studies and how they're different from clinical trials. The institutional review board also known as an ethics committee and what it means to get an approval for a study and data collection instruments. If you are already comfortable with these terms than go ahead and skip ahead in this video. Look for the section on what we are and what we are not going to cover in this course. The definitions we're going to review next are drawn primarily from US sources but they scale and are relevant in many research settings. First of all, in a class on data management for clinical reserach it is important that we take a look at what is considred clincal reserach and what isn't. The short answer is that it is reserach involving human participants. It doesn't matter who is conducting the reserach or where it is being conducted. The U.S. National Institutes of Health has a specific definition for clinical research. They say it's research with human subjects that falls into one of three categories. The three categories are described generally, patient oriented research, which involves interacting directly with human subjects. Epidemiologic and behavioral studies, which look at populations in groups rather than specific individuals. And outcomes research and health services research, which look at how people get access to health care and how we can improve the outcomes of the care people receive. But the US Department of Health and Human Services notes some key exceptions to what it considers research involving human subjects. Research in educational settings, like research evaluating classroom teaching styles doesn't count nor does research using educational tests. Research using publicly available data or fully de-identified data which we'll talk about later. And evaluations of public programs aren't considered human subjects research either. And last, food evaluations and customer satisfaction studies are excluded too. Now there are two main types of clinical research studies, observational studies and clinical trials. In an observational study, investigators observe what happens to participants. Here's a definition from the website ClinicalTrails.gov. Investigators access outcomes in group participants according to a protocol or research plan. Participants may receive interventions, which can include medical products, such as drug, devices or proceedures but it is part of their routine medical care. Participants are not assigned to specific interventions by the investigator, unlike in a clinical trial. So in an observational study, researchers measure exposures and outcomes but they don't administer any particular intervention as part of the study. This kind of study can be conducted going forward in time. In which case its called a perspective study or going back in time. By reveiwing records and previously collected data, which makes it a retrospective study. A clinical trial, on the other hand is, is an interventional study. The US National Institutes of Health calls it a research study that tests how well new medical approaches work in people. US FDA gets a little more specific. Calling a clinical trial a voluntary research study conducted in people. That is designed to answer specific questions about the safety and/or effectiveness of drugs, vaccines, other theories or new ways of using existing treatments. Here's your shortcut. In observational studies, we observe. And in clinical trials, we intervene. Anytime I want to plan a new observational study or clinical trial, any type of human subjects research, I have to request approval from the Institutional Review Board associated with my institution. The application generally involves filling out a lot of forms but it's an extremely important process. The IRB reviews my proposed research to ensure that it is ethical and protects the rights and well-being of human participants. In many countries your IRB approval has to be renewed annually. But that's not universal. Some countries like Brazil have a national IRB. That reviews proposed studies in conjunction with your local IRB. The IRB sometimes likes to review your data collection instruments too. Data collection instruments are the tools you use to collect data for a research study. In this course when we say data collection instruments, study instruments or research instruments. We're referring to the questionnaires and data collection forms that we're learning how to design. Now that we've covered clinical research, let's take a look at the other half of the course title. Data management in general, involves handling data over its entire life cycle. That means managing how it's collected in one or many systems and how it's represented and arranged in database systems. It also means managing how these bits of information are thoroughly documented, backed up safely, monitored over time. Protected from unauthorized access or changes shared with other people or systems, updated with new information. Checked for quality and corrected if errors are found. How it's converted for different uses. And finally how it's destroyed. Data management is relevant in many domains like business, marketing, customer service, hospital billing and definitely clincal research. In the general scope, data management can be a highly technical activity that requires advanced skills. Data management alone isn't the focus of our course though, this is handling the data lifecycle for human subjects research. We are going to talk about the many different ways you can collect data for research. How you design a strategy for your data collection and how to choose among different data collection tools, like paper forms, the computer, phones or even iPads. How do you create a good data collection instrument and know when to use existing ones. We'll talk about the practical details of designing electronic forms, so that they capture the data you want. We'll also talk about data quality. How do you measure it, and what do you do if it's really bad? Data standards, what are some of the common ones in this field and how you can leverage them. Some relevant regulations, which can be a dry topic but it's really important. And finally we'll cover some practical information about surveys, clinical trials, multicenter studies and global health studies. And how those types of research can have different rules and requirements than what we're going to cover in the first couple weeks. I'm sure some of you are wondering about topics that you're interested in but that aren't on these lists. Maybe they just didn't make it into the summary. But just in case, let's review what this course is not going to cover. In terms of tech topics, we won't be covering the topics listed here. Web design, database design or programming. You won't need to know how to set up customized databases for your planned study using basic development tools. You also won't need to know about network architecture, how to set up and maintain secure data networks for your study, data warehousing or information retrieval. Which is a highly technical field despite its straightforward name. Finally, you won't need any specialized software for this course, like SAS, R, Stata or Matlab. This class also doesn't focus on depth on specific topics in clinical research, including how to design clinical trials Bio-statistics and data analysis, how to handle qualitative data. Our focus will be mostly on quantitative data or medical topics, medical coding terminologies and ontologies. And while we're definitely going to talk about special considerations for clinical trials This is an overview course for general clinical research. So it's not a substitute for clinical trials management certifications. Clinical trials are specially those for new drug or device evalution are highly regulated and there data invironment must be two. There are strict data standards you have to meet in extensive documentation. We'll cover some of that along with the associated regulations. But we're not including it in the hands on coursework. Well, I hope that gives you a better idea of what to expect in the next few weeks. In this video, we've defined the space of what this course is going to cover and what it isn't. We also reviewed basic concepts like clinical research, also known as human subjects research. As well as clinical trials, observational studies and the role of an ethics committee or IRB. We'll start on the real material next.