A critical component for any registry is a safe, secure, reliable method to store and interact with your data. In this section, we will explore REDCap and how it can be used for creating and managing your registry.
What is REDCap?
REDCap stands for Research Electronic Data Capture, also known generically as electronic data management software. There are many sources of REDCap information, including a large community-based consortium for support and ideas (see REDCap Resources below). Here, however, we will focus on using REDCap for registry creation and management. As a researcher building a registry, you will need a secure, effective place to store your data, and REDCap is a great option.
Creating and maintaining a registry requires thorough planning, attention to detail, and strong organization. Using REDCap allows a research team to design, standardize, and maintain quality measure for registries.
Why Use REDCap?
Let us review and contrast methods of electronically capturing and storing registry data, including spreadsheets and relational databases.
Spreadsheets are wonderful tools for managing finances, sales, or task lists. However, spreadsheets are neither designed nor optimized for storing research data, especially about human subjects. Although plenty of researchers have created simple or even complex registries using spreadsheets, there are many disadvantages to doing so.
Table 1: Spreadsheet data collection
Consider having two subjects, as shown in Table 1. They fit nicely into two rows of a spreadsheet, but say we want to add lab results for blood glucose, which is a temporal, repeating result as seen in Table 2:
Table 2: Spreadsheet data collection with lab values
The result is a wider data set. If we add the date and time of each result, it just gets wider. Additionally, because a subject could have hundreds of glucose results, storing all that data “horizontally” in a single spreadsheet becomes highly inefficient.
There are several disadvantages to using spreadsheets for data collection:
- More susceptible to human error – All validation, defaults, and constraints must be manually defined on individual cells. Don’t want negative values for a lab value? That will have to be configured per cell.
- Consistency and data linkages are cumbersome – Maintaining consistency among your records will be manual, or require complex formulas to keep data linking accordingly. For example, if demographics are in one sheet and labs in another the link between those sheets can be easily lost, or altered.
- Difficult to troubleshoot – A bad formula or incorrectly referenced cell can wreak havoc on a spreadsheet and leads to data loss.
- Limited collaboration – Typically, a spreadsheet can only be modified by a single user at a time. While others can create copies to edit while a file is in use, merging these changes usually has complications.
Beware the Cloud: Cloud Services and PHI
Several online spreadsheet applications are available. These applications breakdown one of the fundamental disadvantages of spreadsheets ‘collaboration’ as they allow more than one user to access and simultaneously edit the spreadsheet. However, these services are generally not HIPAA compliant and still are prone to data errors.
- Relational Databases
If a spreadsheet is not right for your project, you might determine that a better way to store such results is in a vertical fashion, as shown in Table 3. This is, in fact, an excellent approach to storing longitudinal participant data, and can be achieved with relational databases. There are a variety of types of relational databases including desktop databases, server databases, and cloud databases, each with a multitude of applications and tools available for their creation and management.
- Desktop Database – Store data on an individual device or even network location, while it has several advantages of relational database, it also has several detriments including security and collaboration.
- Server Database – Store data on a server accessible by those with proper security. Most enterprise and professional databases are server databases, as is REDCap
- Cloud Database – Store data…in the cloud. Which is off premise, and while it enjoys all the benefits of relational databases, security is still a hot topic and a risk.
Table 3: “Vertical” data storage
You may ask, “Could I just build my own database?” Of course—but doing so comes with the responsibility for infrastructure, programming, maintenance, and security. Unlike a custom database solution, REDCap is a database that:
- Comes standard with a user-friendly interface for you to safely store human subject research data.
- Allows more than one person from the study team to work on the project at the same time.
- Is maintained by your institution, freeing you up from concerns about IT infrastructure.
To summarize, consider the comparison chart in Table 4 below. Any of these methods could be used to create a registry, but REDCap offers many key features to start your registry out on the right path.
Table 4: Database Comparison
Feature Spreadsheet Own Database REDCap Cost Spreadsheet $ $$$$ $ Spreadsheet $ Low 1 Desktop Depends on User Save often! Storage Capacity Own Database Low High High Own Database $$$$ High >1 Custom Built Depends on Programming Depends on Programming Number of Users REDCap 1 >1 >1 REDCap $ High >1 Web High Daily Interface Desktop Custom Built Web Security Depends on User Depends on Programming High Back-ups Save Often! Depends on Programming Daily
Want to convert to REDCap?
If you already have your registry in spreadsheets or another database, but would like to convert it into REDCap, contact NC TraCS for a consult.
When you use REDCap, all data are kept secure and private. REDCap can remove identifiers from a dataset prior to exporting for analysis to create either a limited data set or a safe harbor data set. A safe harbor data set is the removal of the 18 pieces of information considered identifiers for the purposes of HIPAA compliance. REDCap supports data security in the following ways:
- Supports HIPAA Compliance
- Data stored on a secure server
- Database access requires user authentication with password
- Data access based on an individual’s role on a project
- Logging and audit trails on all data interactions
- IRB approved for collection and storage of Protected Health Information (PHI) including surveys
Learn more about data privacy and security in registries here.