Data Collection and Management Systems for Clinical Research
Every research study involves data that must be collected, stored, updated, queried, and analyzed. While the ability to use a spreadsheet program like Microsoft Excel is an essential skill for the clinical researcher, a spreadsheet program is generally inadequate for most research data collection and management needs. Relational database management systems (RDBMSs) are designed to manage datasets efficiently and securely. To use these systems, researchers must grasp a small but key set of data management principles. This course gives students a thorough grounding in these principles. At the same time, it gives students hands-on practice with the most popular desktop RDBMS, Microsoft Access, and the most common tool for developing web-based research data collection forms, REDCap. Learning these two tools will help students understand the conceptual material and enable them to build genuine solutions. Students will build simple but functional data collection systems in REDCap and relational databases in Access, and they will learn to work with datasets, including updating, querying, formatting, deriving new fields, creating reports, and exporting for analysis. Using this conceptual and practical foundation, the course introduces other DBMS options available to researchers and creation of a data management plan.
At the conclusion of this course, students will:
- Understand the basics of the Relational Database Model, including key concepts such as tables, records, fields, data types, relationships, and primary/foreign keys;
- Be capable of creating on-screen data collection systems using REDCap;
- Know the basics of querying a multi-table, relational database using SQL; and
- Be capable of planning (and budgeting) for data management in a research study.
Michael A. Kohn, MD, MPP
Weekly lectures introduce the substantive content for each module, which is subsequently reinforced in weekly lab assignments. The lab sessions give students the opportunity to ask questions and have more interaction with faculty.
- Lectures: Thursdays: 8:30 to 9:20 AM, August 1 through September 12.
Lecture recordings will be available online later in the day. To determine if you have sufficient bandwidth to view online lectures, please visit our demonstration site.
- Computer Labs:
In-person labs: Thursdays: 9:30 to 10:30 AM. Begin August 1. You will need to bring a laptop to all lab sessions.
Online labs: Wednesdays: 4:30 to 6:00 pm
Students may take the course in an entriely in-person format (physically attending lectures and computer labs), entirely online format, or a hybrid. All students are expected to watch the lectures, either in-person or online. Computer labs are optional and are available to provide additional help for students with questions. These sessions can be attended in-person or online. All students are expected to turn in their weekly homework problem sets through the assigned online portal.
All course materials and handouts will be posted on the course's online syllabus.
"Chapter 16: Data Management" by MA Kohn in Designing Clinical Research by Stephen B Hulley, et al. Wolters Kluwer. 4th Edition. 2013.
Books may be purchased either through the publisher or a variety of commercial venues (e.g., Amazon.com).
Microsoft Access will be used for several assignments. The software is not available for the MAC, but version 2010 or higher can be used on the PC. For students who do not already own the software, it can be used via MyResearch, which is a secure data hosting service for UCSF researchers. In addition to providing secure, HIPAA-compliant storage for research study data, MyResearch provides remote-desktop access to several applications including Microsoft Access. We will submit the initial account request for all students enrolled in EPI 218, but you must sign an online "attestation form" prior to receiving your login ID.
By the first session in the course, you should have tested your MyResearch account and ensured that you can log in. Please note that MyResearch limits free storage to 5 gigabytes of data. Students will be responsible for any charges that incur for data storage beyond this limit, but the storage requirement for the course will be less than 0.1 gigabytes.
REDCap is a web-based research data collection system developed by an academic consortium based at Vanderbilt University. REDCap enables researchers to build browser-based data entry forms, surveys, and surveys with attached private data entry forms. The survey builder is similar to SurveyMonkey or Qualtrics. As with MyResearch, REDCap is available through UCSF Academic Research Systems, and we will submit your initial account request. The same online attestation form required for MyResearch applies to REDCap. You must have a functional REDCap log-in prior to the 2nd session of the course.
To apply for this course, please fill out and submit the application below. Please see our fee page for cost information. The deadline for application is July 15, 2019. Only one application needs to be completed for all courses desired during the quarter.
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