IU REDCap Day 2024

Continental Breakfast
Assorted breakfast pastries, scones, or muffins (Cals: 240-340) (Veg)
Vegan muffins (Cals: 240-340) (V)
Udi's gluten-free muffins (Cals: 240-340) (AG)Seasonal fresh fruit display (Cals: 60) (V, Veg, AG)
Regular and decaf coffee and assorted hot teas (Cals:0)
Orange juice (Cals:120)

V - Vegan
Veg - Vegetarian
AG - Avoiding Gluten

9:35 am - 10:20 am      Rm 450C      General Audience
Through collaborations with research teams, REDCap has grown from its beginnings as a local research tool to a research application used worldwide by over 3 million users in 156 countries. Attendees will learn about REDCap's origin story, growth over time, and global impact.

10:20 am - 10:30 am Continental Breakfast (left from morning)
Assorted breakfast pastries, scones, or muffins (Cals: 240-340) (Veg)
Vegan muffins (Cals: 240-340) (V)
Udi's gluten-free muffins (Cals: 240-340) (AG)Seasonal fresh fruit display (Cals: 60) (V, Veg, AG)
Refill regular and decaf coffee and assorted hot teas (Cals:0)
Orange juice (Cals:120)

V - Vegan
Veg - Vegetarian
AG - Avoiding Gluten

10:30 am - 10:55 am    Rm 307     Beginner
This workshop introduces IU faculty, staff, and students to IU's Research Electronic Data Capture (IU REDCap). REDCap is a self-managed, secure, web-based platform designed to support data collection and data management for research, operations support, and quality improvement projects. REDCap's easy-to-use, intuitive features allow users to rapidly build and manage secure online surveys and databases. This session will cover the basics of using IU REDCap. By the end of the session, attendees will have a good understanding of the features of REDCap, including surveys.

10:30 am - 10:55 am    Rm 309     Intermediate
REDCap is built around change management principles, but it can still be confusing how to maintain a separate test environment. This session looks at a few ideas and one real-life example.

ABSTRACT
Lori L. Millikan | Managing Test and Production Environments

REDCap is built around change management principles, but it can still be confusing how to maintain a separate test environment.

• Why bother having a separate test environment?
• Training
• Play around
• Lots of moving parts

Quick overview of REDCap change management tools available

• Project Setup
• Online Designer – Draft Mode (with undo) and Review Changes
• Copy or Back Up the Project
• Project Revision History
• Data Dictionary (both download and upload)

Some test/prod ideas using these tools alone (will highlight advantages/disadv of each)

• No test environment—make changes directly to production with Draft Mode
• Create a copy of your project whenever you want to make changes
• Maintain two REDCap projects and copy data dictionary/alerts/etc. from test to prod

Real-life Foster Care Bridge Clinic model
Maintain two REDCap projects AND some basic documentation outside of REDCap

• Slide showing the test/prod projects that have animations adding in the two turnover docs

        -- Advantages added = more easily understood and searched
        -- Disadvantage added = time to do the documentation

• Test project never gets moved to production status, always in development status
• May end up with acceptable differences (like the word TEST added to surveys)
• Look at actual turnover list
• Look at some actual go-live documents

Other REDCap tools we use

• Upload/download Data Quality Rules
• Upload/download Alerts? (never got this one to work well?)
• Logging Manage/Design events

Some differences between Test and Production are always there:

• “TEST” language on some surveys and alerts
• Alert recipients, time frames and [Secure Message] tags
• Reports, Project Dashboards

Discussion - What do the session participants do?

10:30 am - 11:20 am     Rm 450C     Intermediate
Learn how you can create reports to simplify finding records, custom dashboards for quick viewing, and utilization of notifications to assist with response timelines.

ABSTRACT
Brenda Hudson | Utilization of Reports, Notifications, and Custom Dashboards to Assist with Team Efficiency

REDCap is an excellent tool for online surveys and data capture. Because of its structure, you can collect a multitude of data but the number of fields and data may make it difficult to organize your data. Well, worry no more! We will discuss how you can create reports to simplify finding records, custom dashboards for quick viewing, and utilization of notifications to assist with response timelines. This session will touch upon these different topics with information on finding additional training opportunities.

11:00 am - 11:25 am    Rm 309     Advanced
REDCap CDIS features, which allow data to be pulled from the Electronic Medical Record (EMR) using the Fast Healthcare Interoperability Resources (FHIR) API, will be presented. It allows seamless, efficient, and real-time data from Cerner.

ABSTRACT
Real-Time Data Synchronization: Assessing the Impact of REDCap CDIS (Clinical Data Interoperability Service) |
Waqas Amin1, Saravanan Kanakasabai2, Randell Grout4, Scott Michael3, Titus Schleyer4

1Indiana Clinical and Translation Science Institute, Indiana University
2Indiana University Health
3Research Software and Solutions, Indiana University
4Regenstrief Institute

Introduction:
The objective of this study is to present the ongoing implementation and utility testing of the REDCap Clinical Data Interoperability Service (CDIS) within a healthcare research setting. Collaboratively overseen by the Indiana Clinical and Translational Science Institute (CTSI), Indiana University Health (IUH), and Eskenazi Health, this project aims to streamline data extraction from Electronic Medical Record (EMR) systems for secondary research purposes using the CDIS. The service offers features that provide real-time data synchronization, automated workflows for data transfer, and secure data handling compliant with HIPAA regulations.

Methods: The REDCap CDIS uses the FHIR API to pull data from the EMR. The CDIS provides Clinical Data Pull (CDP) that automatically pulls EHR data into user-defined REDCap data fields. Clinical Data Mart (CDM) collects longitudinal data for a patient. Five use cases were selected to assess the effectiveness of the CDIS in electronically extracting data from the EMR systems. During the testing process, the tech team is setting up the clinical data pull, and developing adjudication processes to replace complex ETL processes.

Results: The implementation of the REDCap CDIS was successful in achieving real-time data synchronization across multiple EMR systems. Automated workflows streamlined data transfer processes, enhancing efficiency and replace to replace complex ETL processes. . Additionally, the CDIS improved data security and compliance with HIPAA regulations. The rapid adoption of the CDIS was observed across multiple institutes, indicating its potential utility.

Conclusion: The implementation and utility testing of the REDCap Clinical Data Interoperability Service demonstrate its effectiveness in streamlining data extraction from EMR systems for research purposes. Through collaborative oversight and engagement with research teams, the CDIS facilitates real-time data synchronization, automated workflows, and enhanced data security. The rapid adoption of the CDIS across multiple institutes highlights its potential to improve data collection efficiency, quality, and compliance. Further developments in user access governance workflows will enhance its usability for various research studies.

11:00 am - 11:25 am     Rm 307     Beginner
This presentation will emphasize the need for creating a process for analyzing the protocol for the data management elements necessary for creating an effective REDCap database. It will also discuss strategies for effectively mapping out the protocol to translate its elements into a functional REDCap database.

ABSTRACT
Holladay | Translating the Protocol into REDCap

The core of any scientifically robust social behavioral research study is a comprehensive protocol that outlines how the research will be conducted, including the methods and processes that will be used. Protocols, often intricate and specialized for each study, form the foundation of sound research, but are complex in nature. It is often the job of the clinical research coordinator, in collaboration with the Principal Investigator and sometimes, a data manager, to take the necessary elements of the protocol and translate it into a REDCap database that can be used for data collection.

The adage "garbage in, garbage out" holds particular relevance in clinical research. It is critical to capture the necessary data elements correctly when the study first starts data collection. This concept is paramount because it can be difficult, if not impossible, to collect data that may have been missed due to inadequate REDCap design. The protocol contains many elements, such as how data will be collected, what data will be collected, when data will be collected, as well as regulatory documentation requirements. Understanding the protocol's flow is crucial for effectively translating it into a REDCap database where the necessary data is collected and stored. The protocol may require various contributors providing information for REDCap database, including study staff and study participants. Knowing the study's flow, including identifying who needs to input data and on what timeline are important factors for ensuring a functional REDCap database. It is important for the study team not only to comprehend and translate the study design flow for data input but also consider how the database can efficiently output post-study data for data analysis. Both concepts are key elements to effective data collection and management processes.

This presentation will emphasize the need for creating a process for analyzing the protocol for the data management elements necessary for creating an effective REDCap database. It will highlight why prioritizing this process is crucial, even amidst the time constraints often encountered during study start-up. It will also discuss strategies for effectively mapping out the protocol to translate its elements into a functional REDCap database.

11:20 am - 11:35 am  Continental Breakfast (left from morning)
Assorted breakfast pastries, scones, or muffins (Cals: 240-340) (Veg)
Vegan muffins (Cals: 240-340) (V)
Udi's gluten-free muffins (Cals: 240-340) (AG)Seasonal fresh fruit display (Cals: 60) (V, Veg, AG)
Refill regular and decaf coffee and assorted hot teas (Cals:0)
Orange juice (Cals:120)

V - Vegan
Veg - Vegetarian
AG - Avoiding Gluten

11:35 am - 12:00 pm     Rm 450C     General audience
In this session, you will see examples of using standard REDCap functionality (no API-based code, external modules, SQL fields, etc.) to make REDCap do things you might not expect were possible.

12:00 pm - 1:10 pm Lunch Menu
Tossed garden salad (V, Veg, AG) (40 cal)

Herb brined turkey breast (AG) with Sage gravy on the side (gravy is not AG) (260 cal / 5 oz serving)
Herb and panko crusted salmon (170 cal / 4 oz serving)
Beyond Meatloaf (V, Veg)

Ginger vegetable fried rice (V, Veg) (290 cal / 1 cup serving)
Whole Wheat Penne with broccoli, lemon and garlic (V, Veg) (430 cal / 6 oz. serving)
Garlic roasted red bliss potatoes (130 cal / 4 oz serving)
Roast brussels sprouts (45 cal / 1/2 cup serving)

Dessert Bars, including AG and Vegan brownies

Refill regular and decaf coffee and assorted hot teas
Coke, Sprite, Diet Coke

V - Vegan
Veg - Vegetarian
AG - Avoiding Gluten

PLEASE NOTE:
* Unfortunately, we won’t be able to provide Kosher sustenance during IU REDCap Day - if you require Kosher meals, please plan to bring something with you. We, hopefully, were able to honor all other sustenance requests - but please double-check the menus and plan accordingly.

* The turkey is not halal, but the salmon and sides are.

* None of dishes can be certified gluten-free/ nut-free since items are prepared in same facilities. Cross contamination is a risk. However, gluten-friendly foods are indicated in the menu.

1:10 pm - 1:35 pm     Rm 307     Beginner
Evolution of a REDCap clinical database, utilized for quality improvement in a statewide primary care learning collaborative across health systems, will be reviewed. Quality assurance methods and successes and challenges in standardization across a statewide QI project will be described.

ABSTRACT
Paxton | Leveraging REDCap to maintain standardization and quality assurance of data across a statewide quality improvement initiative 

Background: An interdisciplinary team of faculty in Department of Pediatrics at Indiana University School of Medicine (IUSM) launched the Early Autism Evaluation (EAE) Hub system, an innovative tiered system of developmental screening and autism evaluation within the primary care setting. The goal of this initiative is to improve localized access to early autism diagnosis for young children to promote entry into evidence-based intervention at the earliest time. Quality improvement (QI) data for every evaluation across the EAE system is collected in REDCap and used to improve care.

Objectives: Review the evolution of a REDCap clinical database utilized for quality improvement in a statewide primary care learning collaborative across health systems. Explain quality assurance methods and successes and challenges in standardization across a statewide QI project.

Methods/Results: As our program was initially implemented and then evolved with clinical application, areas for potential quality improvement were identified and measures were created and edited. Defining all these measures clearly was critical. REDCap made it easy to create data collection instruments with clear definitions. REDCap features including drop downs, date validation, and calculations that make it easy for users to enter data with greater accuracy and efficiency.

Upon trialing data collection, measure definitions were further edited based on participant feedback for better clarity. REDCap’s data dictionary, codebook and logging feature make it simple to track these edits for future analysis. When measures are edited, REDCap allows you to hide the older fields/questions so older data is not lost. Older choices can also be hidden.

Accuracy of data entry is essential. Training data entry personnel is a critical step in maintaining the integrity of the data. New personnel receive virtual training by our team’s data manager that includes the most current data definitions and guidance for locating each measure. Questions and feedback are encouraged. Timely data entry is also important. If data entry is late (over 1 month), teams receive a reminder email to enter their data.

Even with all these quality assurance methods, data must still be cleaned and verified prior to analysis. Any outliers are confirmed with the EAE Hub sites. If edits are needed, it is important to edit the original record in REDCap for future analysis. To further ensure quality assurance, EAE Learning Collaborative virtual meetings are held monthly. During these 40 minutes calls, data summaries are shared and discussions are held regarding measure clarification and quality improvement projects are planned and implemented.

Conclusions: Using REDCap for the EAE statewide network data collection improves accuracy, efficiency and clarity of data entry and data management. By analyzing QI data collected in REDCap, standardization to our EAE model can be verified, opportunities for process and care improvement can be realized and information can be disseminated to collaborators and funders.

1:10 pm - 1:35 pm      Rm 309     Intermediate
This presentation will cover how the Center for Survey Research utilized REDCap as a case management system to administer a large-scale phone survey.

ABSTRACT
Clampitt | Using REDCap for Field Work

This presentation will cover how the Center for Survey Research utilized REDCap as a case management system to administer a large-scale phone survey. This case management system needed to assign interviewers a case to call based on:
• Time of day
• Number of prior calls
• Scheduled call backs
• Case disposition
• Call priority

We also needed to ensure no collisions occurred amongst interviewers accessing the same case at the same time. Different REDCap instruments were used to manage the sample, provide a calling script, administer the interview, and code a disposition. To accomplish all these tasks, we utilized the following REDCap features:
• Survey instruments
• Repeating forms
• Form display logic
• Stop actions
• Automated notifications
• Reports with advanced logic

During this presentation I will cover the basic structure of the REDCap project, including how different parts of REDCap were used to solve problems that arose, and challenges we faced.

1:10 pm - 2:00 pm     Rm 450C     Intermediate
This presentation will provide tools for making effective reports. The design of a patient tracking log will be used as an example of how complex information can be synthesized into a simple report.

ABSTRACT
Martin | Make Better Reports with @CALCTEXT and Filter Logic

For many projects, it is critical that users have real-time access to the data. From pinpointing missing information to making data-based decisions, projects benefit from having data that is up to date and easy to read. REDCap reports offer this crucial functionality, but basic reports are often bloated and difficult to parse.

Two REDCap features—the @CALCTEXT action tag and report filter logic—can greatly simplify reports and provide additional functionality. @CALCTEXT can synthesize information across many variables and reduce the need for redundant data entry. Appropriate filters keep things simple and enable users to view only pertinent information. These and related functions can give users immediate insight into the data without the need for external programs.

In this presentation, I will discuss these reporting features in relation to the NICU Tracking Log, a REDCap project I created to catalog demographic and transfer information from patients admitted to the two Neonatal Intensive Care Units (NICUs) at Riley Hospital for Children. Moving this project from a shared Excel file to REDCap created challenges related to tracking patients as they moved within and outside our hospital. Despite these difficulties, REDCap has exceeded our team’s expectations, largely because of its reporting features. Compared to Excel, it is much easier for users to gain real-time insights from the data. Using @CALCTEXT and conditional logic with REDCap reports, one can now easily identify currently admitted patients and see their exact location in the hospital. With advanced filter logic, I’ve created reports showing recently admitted or discharged patients as well as focused reports on crucial populations of our NICU babies.

To help others with their projects, I will provide examples of report functionality that are broadly applicable. Examples will range from simple to complex and will include saving space by combining information from two fields, filtering reports based on dates, and removing all those terrible empty fields caused by repeating instruments.

1:40 pm - 2:05 pm     Rm 307     Intermediate
Curious about eConsent in REDCap and how you might use REDCap to administer electronic Informed Consents? Look no further than this session for a solid introduction.

1:40 pm - 2:05 pm     Rm 309     Advanced
The presentation will include why the Copy Data on Save external module is useful when a project involves multiple databases, and a brief demonstration on how it works.

ABSTRACT
Higbie | Utilizing Copy Data on Save External Module

The reason for utilizing the Copy Data on Save External Module in developing a REDCap database for a new pragmatic project at the Indiana University Center for Aging Research (IUCAR) was to reduce potential for human error and save time by eliminating manual data entry between the screening and outcomes databases. The REDCap users in this project are REDCap novices and this module aligns with the intention to create a REDCap workflow that is as efficient as possible while simplifying the knowledge needed by users to enter data. The introduction to the external module Copy Data on Save was through a project collaboration with the Albert Einstein College of Medicine (AECOM). This module is an accessible mechanism for Research Managers or Coordinators, (i.e. advanced REDcap users that build and manage REDCap databases that may not have the knowledge base to use API or other advanced data transfer functions) to automatically transfer data between identified databases. Copy Data on Save utilizes REDCap logic and variable naming rules to determine what data is automatically transferred. Other projects could utilize this external module if it becomes more widely available.

2:00 pm - 2:15 pm  Break
Freshly Baked cookies
Vegan cookies
Savory Party mix (seasoned bread chips, rice crackers, pretzels, cheese crackers, almonds, onion crackers, and corn chips)

Refill regular and decaf coffee and assorted hot teas
Coke, Sprite, Diet Coke

2:15 pm - 2:50 pm     Rm 450C     General audience
REDCap is always evolving to address data collection needs. This session delves into some recent interesting new features and looks at what’s coming down the pike. Exciting things are happening with REDCap!