Data Informatics Services Core (DISC)
The Data Informatics Services Core (DISC) collaborates with research faculty and staff from the Johns Hopkins Medical Institutions, offering several options for this collaboration depending on the researcher's needs and interests.
This collaboration includes assistance in developing and implementing, or reviewing, data capture tools and data management systems. DISC includes data managers and administrative staff. DISC also coordinates with JHBC’s Biostatistics arm to enlist their expertise in study design and analysis requirements for the best interests of the research study. DISC provides support for REDCap which is a secure web-based application for flexible data capture and management with thousands of worldwide installations.
What We Offer
- REDCap support for database design, setup and modification of the database, user support and custom programming for project requirements as needed.
- Writing programs to perform data management tasks in major statistical packages, such as:
- Conversion of data structures
- Data cleaning and preparation for analysis
- Maintaining data’s quality assurance over the life of the project
- Protection of PHI fields, as required
- Creation of additional fields (summaries, new fields based on combinations of other fields)
- Review of database design and data capture instruments
NOTE: Data entry and data monitoring services are not provided.
Why and When to Engage DISC
Engaging DISC in the development and implementation of data management aspects of the research study facilitates better organization and use of data capture tools, better accuracy of data capture with defined coding of variables, and a better interface to analysis requirements. DISC can assist with suggestions for data capture tools, form design, improving data quality and best practices for data management. The research study benefits from efficiencies and data accuracies based on an organization and documentation of different data streams (lab, survey, mobile, longitudinal), consistency in coding and naming conventions, security as needed, improved data handling, and managing data in a reproducible manner.
The most effective time for engaging DISC is in the planning stages of the study before data capture begins. This facilitates ensuring that the data are set up correctly from the beginning of the study with respect to their subsequent uses and allows the data to be captured as intended to meet the study’s objectives.
Collaboration and Consulting Options
JHBC offers a range of options to provide data capture/management support for JHU faculty and staff.
Institute of Clinical and Translational Research (ICTR) - Free Access
As a recipient of a National Institutes of Health (NIH) Clinical and Translational Science Award (CTSA) since 2007, Johns Hopkins allows us to make available limited free consultations to JHU research faculty and staff performing clinical and translational research.
An ICTR request provides a researcher with up to 5 free hours of biostatistics or data management consultation/analysis per research project. These requests can be submitted as a follow-up to a walk-in clinic visit, or when a researcher knows that their questions require more substantive discussion than afforded by the clinic. A separate ICTR request should be submitted for biostatistics and for data management support on the same project.
For a data management request, a data manager will be assigned to the request based on the information provided (within 3 business days). If a biostatistics request is also submitted, the biostatistician and data manager will work together to ensure consistency in approach. Once the assignment has been made, the data manager will contact the researcher (within a week) to set up an initial meeting to discuss and clarify the needs of the research project, and to discuss an approach for supporting the request.
If the researcher's request requires more than the 5 free hours, the researcher can coordinate with JHBC for support through a Fee-for-Service or long-term collaboration agreement.
Acknowledgement of NIH
To recognize the assistance provided by this grant, NIH requests that the following statement be included as an acknowledgement in any dissemination of the supported research.
We would like to acknowledge data management support from the National Center for Research Resources and the National Center for Advancing Translational Sciences (NCATS) of the National Institutes of Health through Grant Number 1UL1TR001079.
When the amount of limited free ICTR support is not adequate for the project, researchers can take advantage of our fee-for-service contracts. In discussion with the DISC manager, Andre Hackman (firstname.lastname@example.org), a project task order (PTO) is prepared which includes an estimate for the amount of effort (in hours and cost) required for the data manager, and biostatistician if needed, and which delineates the type of tasks that will be provided for that estimate. The researcher will be asked to sign the PTO and to include the financial information needed to bill for the work provided. The PTO is an estimate, and the project is only charged for hours worked by the data manager(s). The use of REDCap is based on a monthly charge which includes user support and overall administrative responsibilities for the database. Details on REDCap pricing can be found here. The estimate can be amended over time in discussion with Andre Hackman as requirements change in terms of effort/tasks required, the period of time over which the tasks are requested, or funding vehicles. Work will begin once the PTO has been signed and is invoiced monthly. Rates are evaluated annually to defray the costs of operating JHBC as a not-for-profit center within JHSPH.
For some projects, a researcher may want to have a data manager assigned to a project for a period of time on a percent/level of effort (LOE) basis. In grant proposals, these collaborators may be considered key personnel. This type of arrangement is coordinated with the researcher and the DISC manager, Andre Hackman (email@example.com), to determine a best fit with JHBC's resources and the researcher's needs. Once this has been discussed, the researcher will need to submit a faculty collaboration request which will then be approved by the assigned data manager and the DISC manager. The researcher will then be contacted by JHBC administrative staff regarding the costs (salary, benefits and computing fees) associated with this type of arrangement.
The LOE request should match the effort to be expended and by the size and complexity of the study design and data management support expected. LOEs can vary across the years/phases of the project.
Collaboration and Consulting Expectations
Consultation and collaboration require a mutually agreed-upon understanding of, and respect for, the expectations that will guide this relationship. These expectations will be part of the initial discussions and may include the following categories.
Making Efficient Use of a Collaboration
The first meeting between the researcher and data manager is an opportunity to begin to clearly define the tasks and timelines required. Good communication is important. The better prepared a researcher is in the initial meetings, the more efficient the collaboration can proceed. The following include examples of information the researcher should be prepared to discuss with the data manager.
- Data dictionary of fields to be captured: variable names, format, coding values
- Timing of data to be captured if multiple time points
- Levels of access for data entry and oversight
- Calculations between fields
- Validation of fields based on other fields
To provide quality work to all of our researchers, the following are guidelines of time to be allowed for a data capture/management request. Recognizing that projects and requests differ in their complexity and needs, and that there are competing demands for support, specific timeframe requirements will be discussed with the data manager in the initial meetings. The timeframe may be re-evaluated as the request is refined.
- Setting up a small to medium-sized REDCap database – 2 weeks
- Setting up a large or complex REDCap database – 4 weeks
- Custom programming for REDCap database, depending on complexity of tasks – 2 to 4 weeks
- Writing programs to perform data management tasks in major statistical packages – 2 to 4 weeks, depending on complexity of tasks
- Review of database design and data collection instruments – 2 weeks