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Clinical Research Data/Informatics

The ICTR Informatics Core provides an integrated set of tools and services to help clinical researchers collect, extract, and analyze clinical data for research at every stage of the research lifecycle.

Prepare Your Study

SlicerDicer

Investigators with access to Epic can use Epic’s SlicerDicer to get rough patient counts.  To find SlicerDicer in Epic, go to the Epic search bar and type in SlicerDicer. IRB approval is needed prior to using these data for recruitment or to conduct your research or publish.

Note that SlicerDicer has the following limitations:
– not all data in Epic are available for searching in SlicerDicer (most notably text data)
– patient data collected outside of the Johns Hopkins Epic system will not be available in SlicerDicer with the exception of some historical lab and encounter data.

TriNetX

TriNetX is a self-service tool launched broadly in January 2019. TriNetX has advanced analytic tools and a cleaner set of data then what is available in SlicerDicer. TriNetX is populated with data from Epic which have been cleaned, curated and more fully mapped to codes like LOINC to improve data quality and analysis.

Learn more.

Accrual to Clinical Trials (ACT)

The ACT Network is a real-time platform allowing researchers to explore and validate feasibility for clinical studies across the NCATS Clinical and Translational Science Award (CTSA) consortium, from their desktops.

Learn more.

Core for Clinical Research Data Acquisition (CCDA)

When investigators have sophisticated inclusion and exclusion criteria that cannot be satisfied by using SlicerDicer or TriNetX, we recommend that they contact the CCDA for assistance. Investigators receive 2 initial hours of service subsidized by the ICTR, during which we are often able to complete simple feasibility queries.

Learn more.

If you need a letter of support from the ICTR Informatics Core, please contact Bonnie Woods, IT Senior Director at bonnie.woods@jhu.edu or Christopher Chute so that we can better understand your proposed study, and provide you with a signed letter of support on official letterhead.

We offer 90 minute sessions attended by Dr. Christopher Chute, Bonnie Woods, and invited guests (as required) to address the specific questions being posed by the study teams.

To apply for an informatics consult, click here.

For more information, contact Bonnie Woods at bonnie.woods@jhu.edu.

 

Tools for Conducting Your Study

CRMS is a web-based tool designed to organize and streamline clinical research management designed to improve communication among study team members.

CRMS must be used by studies which could result in a patient bill. It may also be used by retrospective studies to define the study cohort in order to facilitate data extraction from Epic and other information systems.

Learn more.

EPIC

For data capture in the Epic medical record: Leverage Epic to build custom content to capture clinical data, alert providers to potential research participants, and build patient-reported outcomes questionnaires. There is an hourly fee for this service. 

Learn more.

REDCap

For case report forms outside of Epic: Build your own surveys and data collection forms quickly and securely using REDCap. This tool is often used to collaborate on data collection with other institutions. There is a Bronze free version and a Silver version with more functionality at a cost of $50/month. 

Learn more.

Qualtrics

For surveys: Use Qualtrics to build simple to complex surveys, tests and quizzes, and more free of charge.

Learn more.

The ICTR Informatics Core provides multiple tools and services for study recruitment.

  • With prior IRB approval, investigators may use SlicerDicer to get an identifiable list of patients for whom they have provided care who meet the inclusion and exclusion criteria for their study.
  • With IRB approval, the Core for Clinical Data Acquisition (CCDA) can provide investigators with a list of patients that meeting their study’s inclusion and exclusion criteria.
  • PACE offers customized EPIC content for your project to enhance the efficiency and standardization of the data collection process and improve data quality.

For more general information about study recruitment, we recommend visiting our recruitment page.

OpenSpecimen is a Biospecimen Information Management System that is a scalable solution for a biorepository which meets the needs of a broad group of investigators and biobanks. 

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DocuSign is a 21 CFR Part 11 compliant electronic signature tool that can be used to enable remote signatures on research consent forms.

Learn more.

Analyze Your Data

The Core for Clinical Research Data Acquisition (CCDA) assists researchers with accessing clinical data for research purposes. The CCDA is staffed with experienced data analysts who will assist you with access to data while also helping you comply with Data Trust privacy and security regulations.

Learn more.

Natural Language Processing (NLP) is a programming technique to find and extract data of interest from text documents.

NLP can sometimes involve a simple search for known text strings but is often more complex due to the ways that human beings use language. For example, the concept of smoking could be expressed in many different ways in a text document, such as “has never smoked”, “used to smoke 3 packs a day”, “recently quit smoking”, “is in a smoking cessation program”.

The Center for Clinical NLP, with faculty and staff from the Johns Hopkins School of Medicine, the Johns Hopkins Whiting School of Engineering, and the Johns Hopkins Applied Physics Laboratory (APL), are well versed in techniques and tools to assist you with your NLP needs.

For more information, contact Bonnie Woods at bonnie.woods@jhu.edu.

PMAP pulls data from the Epic Medical Record and other data sources into a Data Commons, where the data are integrated together and available in a format that is operable by sophisticated machine learning and natural language processing technologies. 
PMAP is available to all Johns Hopkins Medicine researchers. A portion of the services are provided at no cost. 

Learn more.

SAFE, the Secure Analytic Framework Environment, is a virtual desktop that provides Johns Hopkins Medicine investigators (whether engaged in research or other data-intensive activities) with a secure environment to analyze and share sensitive data (e.g. PHI, PII) with colleagues.

Learn more.