Seminars & Workshops
Research Database Development Part 1: Basics & Best Practices

Overview

Are you involved in building a REDCap database for your research project?

Building an appropriate database for your study is critical to ensuring successful data collection and analysis. Learn how to build your database in this three-part Research Database Development course presented by Tufts CTSI. There are no pre-requisites required for any of the three course registrations, but participation in all three courses is encouraged as they build on each other.

Part 1: Basics & Best Practices

This two-hour session will begin with an interactive lecture presented by Rachael Huebner, MPH, Clinical Data Manager at Tufts CTSI, followed by a workshop in which participants will practice building a simple database in Excel. Participation will be required for the workshop portion.

Pre-requisite: none

Topics covered include:

  • Database development best practices
  • Determining which data to collect
  • Choosing variable types
  • Naming variables
  • Assigning numbers to variables
  • Using Excel to create a database

After attending this session, participants should be able to:

  • Recognize database creation best practices
  • Identify the clinical and demographic data needed to answer a study question
  • Effectively name and code variables
  • Create an Excel sheet appropriate for study data collection

Details

Date: Wednesday, August 26, 10:00AM-noon

Location: online via Zoom

Registration

Members of any Tufts CTSI-affiliated institution are welcome to attend.

To receive the Zoom link, please register here.

Instructors

Rachael Huebner, MPH is the Clinical Data Manager at Tufts CTSI, providing data management support and training to researchers. Prior to joining Tufts, she worked in data management for industry-sponsored clinical trials after receiving her MPH from Boston University School of Public Health.

Ethan Goldstein is a Project Coordinator for the Informatics team at Tufts CTSI. He is responsible for REDCap user and application support. Ethan has been involved in REDCap database development for more than four years. He started at Brigham and Women’s Hospital where he designed REDCap-based systems for issue tracking and subject recruitment. He is a native of Boston, and a graduate of Clark University with a degree in Biology.

Tufts CTSI Professional Education & Expectation for Course Participants

Tufts CTSI’s Professional Education programs provide non-degree continuing education and training for clinical and translational research professionals from all Tufts CTSI partners and beyond.

Course enrollment priority is given to researchers from Tufts CTSI partner institutions. If your participation needs to be approved by your supervisor or a person responsible for your time release, you may provide their contact information when you register for the program.

This course is provided free of charge, and was supported by the National Center for Advancing Translational Sciences, National Institutes of health, Award Number UL1TR002544. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

 

Seminars & Workshops
Research Database Development Part 2: Building a REDCap Database

Overview

Are you involved in building a REDCap database for your research project?

Building an appropriate database for your study is critical to ensuring successful data collection and analysis. Learn how to build your database in this three-part Research Database Development course presented by Tufts CTSI. There are no pre-requisites required for any of the three course registrations, but participation in all three courses is encouraged as they build on each other.

Part 2: Building a REDCap Database

This two-hour session will consist of a guided tutorial led by Ethan Goldstein, Informatics Project Coordinator at Tufts CTSI, followed by a discussion on building REDCap databases for your own research. Participants should be prepared to discuss their research projects. Instructors will work with you to create REDCap accounts prior to this session.

Topics covered include:

  • Introduction to REDCap
  • Creating projects, forms, and fields
  • Exporting data

After attending this session, participants should be able to:

  • Describe the differences between classic and longitudinal projects, and identify when to use each
  • Create projects, forms, and fields in REDCap
  • Export data from REDCap to Excel

Details

Date: Thursday, August 27, 10:00AM-noon

Location: online via Zoom

Registration

Members of any Tufts CTSI-affiliated institution are welcome to attend.

To receive the Zoom link, please register here.

Instructors

Rachael Huebner, MPH is the Clinical Data Manager at Tufts CTSI, providing data management support and training to researchers. Prior to joining Tufts, she worked in data management for industry-sponsored clinical trials after receiving her MPH from Boston University School of Public Health.

Ethan Goldstein is a Project Coordinator for the Informatics team at Tufts CTSI. He is responsible for REDCap user and application support. Ethan has been involved in REDCap database development for more than four years. He started at Brigham and Women’s Hospital where he designed REDCap-based systems for issue tracking and subject recruitment. He is a native of Boston, and a graduate of Clark University with a degree in Biology.

Tufts CTSI Professional Education & Expectation for Course Participants

Tufts CTSI’s Professional Education programs provide non-degree continuing education and training for clinical and translational research professionals from all Tufts CTSI partners and beyond.

Course enrollment priority is given to researchers from Tufts CTSI partner institutions. If your participation needs to be approved by your supervisor or a person responsible for your time release, you may provide their contact information when you register for the program.

This course is provided free of charge, and was supported by the National Center for Advancing Translational Sciences, National Institutes of health, Award Number UL1TR002544. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

 

Seminars & Workshops
Research Database Development Part 3: Advanced REDCap Features

Overview

Are you involved in building a REDCap database for your research project?

Building an appropriate database for your study is critical to ensuring successful data collection and analysis. Learn how to build your database in this three-part Research Database Development course presented by Tufts CTSI. There are no pre-requisites required for any of the three course registrations, but participation in all three courses is encouraged as they build on each other.

Part 3: Advanced REDCap Features

This two-hour session will begin with a demonstration of commonly used advanced REDCap features, led by Ethan Goldstein, Informatics Project Coordinator at Tufts CTSI, followed by an interactive conversation answering participants’ real-life REDCap questions.

Topics covered include:

  • Complex piping and calculations within REDCap forms
  • Establishing workflows with the Survey Queue and Alerts and Notifications sections
  • Understanding how Action Tags can be used to help guide data collection
  • Ensuring high-quality input by establishing Data Quality rules

After attending this session, participants should be able to:

  • Identify use cases for advanced REDCap features
  • Implement commonly-used advanced features in REDCap projects

Details

Date: Friday, August 28, 10:00AM-noon

Location: online via Zoom

Registration

Members of any Tufts CTSI-affiliated institution are welcome to attend.

To receive the Zoom link, please register here.

Instructors

Rachael Huebner, MPH is the Clinical Data Manager at Tufts CTSI, providing data management support and training to researchers. Prior to joining Tufts, she worked in data management for industry-sponsored clinical trials after receiving her MPH from Boston University School of Public Health.

Ethan Goldstein is a Project Coordinator for the Informatics team at Tufts CTSI. He is responsible for REDCap user and application support. Ethan has been involved in REDCap database development for more than four years. He started at Brigham and Women’s Hospital where he designed REDCap-based systems for issue tracking and subject recruitment. He is a native of Boston, and a graduate of Clark University with a degree in Biology.

Tufts CTSI Professional Education & Expectation for Course Participants

Tufts CTSI’s Professional Education programs provide non-degree continuing education and training for clinical and translational research professionals from all Tufts CTSI partners and beyond.

Course enrollment priority is given to researchers from Tufts CTSI partner institutions. If your participation needs to be approved by your supervisor or a person responsible for your time release, you may provide their contact information when you register for the program.

This course is provided free of charge, and was supported by the National Center for Advancing Translational Sciences, National Institutes of health, Award Number UL1TR002544. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

 

Seminars & Workshops
The Odyssey of OHDSI: Using Health Care Data for Research

How can we use health care data to generate reproducible scientific evidence or reliable clinical predictions? What innovative tools are available to allow us to efficiently work with our own data and in collaboration with others?

Join Tufts CTSI on May 6-8 at The Odyssey of OHDSI: Using Health Care Data for Research on the Tufts Health Sciences Campus in Boston to find out!

Observational Health Data Sciences and Informatics (OHDSI, pronounced Odyssey) is a rapidly expanding multi-sector research collaborative dedicated to uncovering the value of health data through large-scale analytics. The OHDSI community includes dozens of academic, corporate, and governmental institutions that use health data for research in the US and around the world. The community conducts methods research to identify best practices and builds state-of-the-art open source tools that implement those methods.

This exciting three-day workshop led by principal developers Marc Suchard, MD, PhD, University of California at Los Angeles (UCLA); Martijn Schuemie, PhD, and Jenna Reps, PhD, Janssen Research and Development, will teach you how to use OHDSI tools on data that conforms to the OHDSI community’s OMOP Common Data Model (CDM). In addition to implementing best practices, these tools are designed to simplify research processes by eliminating data wrangling and standardizing the parts of complex multistep processes that don’t require thoughtful consideration while informing many parts that do.

Day one will briefly cover OHDSI and how it supports research. Most of the day will cover how data are represented by vocabularies in the OMOP CDM and how to use the ATLAS toolset to define cohorts. Day two will give researchers, statisticians, and data analysts a hands-on introduction to using either of the two most mature OHDSI analytic tool sets. These will be taught in two tracks. The first will cover tools for population-level effect estimation. The second will cover tools for developing patient-level prediction models. Day three will guide participants through every step of conducting a study using the methods and tools covered in Day 2. Each session will build incrementally on the last so participants in later sessions will benefit most if they understand material covered in earlier sessions.

This will be a highly practical, hands-on training, perfect for any researcher, statistician, analyst, methodology specialists, or staff who uses health care data for research. Attendees should have basic R experience and understanding of observational data, as well as prior experience analyzing observational data such as electronic health records, before attending this session, and are encouraged to attend all three sessions.

Course Faculty

  • Christian Reich, MD, PhD
    VP Real World Analytics Solutions, IQVIA
  • Jenna Reps, PhD
    Senior Epidemiology Informaticist, Janssen research and Development
  • Martijn Schuemie, PhD
    Director, Epidemiology Analytics, Janssen Research and Development
  • Anthony Sena
    Associate Director of Epidemiology Analytics, Janssen Research and Development
  • Marc Suchard, MD, PhD
    Professor, Department of Biomathematics, David Geffen School of Medicine, University of California, Los Angeles

Learning Objectives

After completing this workshop series, you should be able to:

  • Relate key OMOP CDM and vocabulary principles to PHDSI’s standardization process
  • Define cohorts, conduct cohort studies, or develop patient-level prediction models using OHDSI tools
  • Identify and access educational and other resources needed to become more fully proficient at using these tools in your research work.

After completing Day 1, you should be able to:

  • Navigate OMOP CDM and vocabularies to define populations and outcomes.
  • Discuss the structure of the OMOP CDM and how the OHDSI community uses it to support observational research.

After completing Day 2, you should be able to:

  • Track 1:
    • Demonstrate how OHDSI tools can be utilized to design and implement a comparative cohort study in observational healthcare data
  • Track 2:
    • Describe the patient-level prediction model process
    • Develop models using the OHDSI Patient-Level Prediction framework
    • Identify key elements to develop and validate prediction models using the OHDSI tools.

After completing Day 3, you should be able to:

  • Discuss basic study design and statistical concepts and procedures

Details

Monday, May 6, 2019, 10:00AM-5:00PM

OMOP-CDM, Vocabulary, Cohort Definitions
Tufts University School of Dental Medicine, Rachel’s Auditorium, 14th Floor
1 Kneeland Street, Boston

Tuesday, May 7, 2019, 9:00AM-5:00PM

Track 1: Population-level Effect Estimation (Cohort Method)
Tufts University School of Dental Medicine, Dental Board Room 1533, 15th Floor
1 Kneeland Street, Boston

Track 2: Patient-level Prediction
Tufts University School of Dental Medicine, Rachel’s Auditorium, 14th Floor
1 Kneeland Street, Boston

Wednesday, May 8, 2019, 9:00AM-5:00PM

OHDSI Tools and Hands-On Your Data
Tufts Center for Medical Education, Room 216A, 2nd Floor
145 Harrison Avenue, Boston

Registration

This workshop is intended for people who want to learn how health data are represented using OHDSI’s data standards and those who want to use OHDSI tools to define research cohorts, conduct cohort studies, or develop patient-level prediction models using OHDSI tools. The series is perfect for any researcher, statistician, analyst, methodology specialists, or staff who uses health care data for research.

Each session will incrementally build on the skills gained in the previous session(s). Though not a prerequisite, participants who have attended or already understand the material covered in previous sessions will gain the most from subsequent sessions.

To reserve your space, please register here by April 29.

 

Tufts CTSI Professional Education & Expectation for Course Participants

Tufts CTSI’s Professional Education programs provide non-degree continuing education and training for clinical and translational research professionals from all Tufts CTSI partners and beyond.

Course enrollment priority is given to researchers from Tufts CTSI partner institutions. If your participation needs to be approved by your supervisor or a person responsible for your time release, you may provide their contact information when you register for the program.

This course is provided free of charge, and was supported by the National Center for Advancing Translational Sciences, National Institutes of health, Award Number UL1TR002544. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.