Discovery Data Coordinating Center

Ways to Collaborate With the Discovery DCC

Early collaboration with the Discovery DCC is critical for optimizing the potential for success, beginning at the earliest phase of study conceptualization.

Table 1 outlines how you can collaborate with the Discovery DCC during different phases of your study. Depending on the type of study and/or proposal, some of these activities may not apply to your study.

Table 1. Phases of Collaborative Activities for Funding Submissions

Activity Phase	Nature of Collaboration	Ideal Timeline
1. Initial concept
1.a. Developing the research question	Discuss the research question, conceptual framework, causal relationships, and the broad implications of the needed design parameters to evaluate that research question.	5-6 months before submission
1.b. Assessing feasibility of the associated design	Consider the feasibility of the associated designs and, if needed, reconsider the question of interest and discuss further iterations of the main concept and potential designs.
1.c. Refining the approach, sample size and power, and drafting a statistical analysis approach	Based on the discussions above, outline the corresponding approach, estimate the sample size and power, and draft a preliminary analysis plan.
2. Refining the approach
2.a. Analysis of preliminary data	If required, provide analysis of preliminary data, which can be time-consuming and can influence the resulting proposal, leading to further iterations of the above steps.	3-4 months before submission
2.b. Continued development of the design and analysis plan	Further develop the approach by discussing identification of key variables, temporal relationships among variables, and refinement of optimal statistical methods.	2-3 months before submission
2.c. Finalize the approach and funding proposal	Review and revise approach as needed. Changes made in later stages of project development often have unintended consequences on the final approach, so this further check is critical.	1 month before submission
3. Study conduct and analysis
3.a. Study initiation	Set up data collection procedures, including programming in REDCap, outline of statistical programs for subsequent reports, and development of protocols and a manual of operations.	6 months to 1 year
3.b. Data collection	Once data collection begins, upkeep and further modification of the REDCap database is often needed as the study proceeds.	Ongoing after first 6 months to 1 year
3.c. Ongoing statistical reports of recruitment and events	Provide reports on an ongoing basis (often monthly). Depending on study type, safety and adverse event reports, quality assurance reports, and reports to committees and funding agencies may also be needed throughout.
3.d. Statistical analysis of interim endpoints	Depending on study type, formal interim analyses may be needed in addition to the ongoing reports.	Midpoint of the study, or at multiple interim times
4. Final statistical analyses and writing the primary manuscript	Depending on study type, the final analysis may follow easily from the previous steps (eg, for an explanatory trial) or may take more time (eg, for many observational studies).	Near or after completion of the study
5. Revisions to the primary manuscript and follow-up manuscripts	Most studies have follow-up manuscripts on secondary objectives that continue after the end of the formal study period.	After study completion

The Team

The Discovery DCC is composed of statistical support (MS/PhD), program managers, and a data manager.
 
Statistical Support: Led by Douglas Landsittel, PhD, professor and chair of biostatistics, School of Public Health Professions, University at Buffalo, State University of New York. Dr. Landsittel has more than 20 years of experience in collaborative, educational and methods research.

Program Managers: Discovery’s full-time program managers are responsible for overseeing research projects from conception through final reporting, which may include overseeing individual research projects from pre-award through post-award, tracking project timelines and budget compliance, maintaining records and reports on project status, and working as a liaison between the PI, other investigators, and project leads.

Data Manager: Discovery’s full-time research data manager is responsible for the performance, integrity, and security of SCCM’s research-related database. Data manager consultation services are offered in the following areas:

• Developing conceptual design for planned research database projects, in conjunction with PIs and research staff
• Developing designs that facilitate back-end data organization and user-facing accessibility and usability
• Developing project-specific procedures to implement and ensure the collection of accurate and usable data
• Assisting PIs and institutions with setup, testing, and implementation of data collection

Discovery collaborates with biostatistics teams at academic centers such as Indiana University and University at Buffalo.

Web-Based Data Entry, Electronic Data Capture System: REDCap Cloud

The Discovery DCC uses REDCap Cloud for research that requires data collection. REDCap is a secure, web-based application designed to support data capture for research studies. REDCap Cloud is compliant with FDA CFR Part 11, HIPAA, and EU Annex 11 regulations.

REDCap Cloud has the following security features:

• Secure data entry and storage in the cloud accessed through single sign-on
• Protection for data in flight and at rest:
  • Using https encrypts data between the data center and the client browser
  • Checking the PHI (personal health information) box when creating a data entry field ensures that the data are auto-encrypted in the database using a 256-bit RSA key
• Secure transfer of large data files
• Robust audit trail that shows all changes to all records within the system, including a complete audit log of data, time, and user access
• Control of access to REDCap studies through assignment of users, user roles, and permissions

REDCap Cloud has several features that can be incorporated into a case report form (CRF) that ensure data accuracy and quality, as well as tools for medical coding, data monitoring, and documenting CRF completion.

• Detailed response sets for each question, reducing the need for open-ended responses
• Medical coding that allows for the use of established medical terminology
• Data edit checks (minimum and maximum values, integers, whole numbers)
• Ability to query responses to each variable, which can be set up to generate automatic queries to data entry personnel
• Source data validation
• Documenting completed CRFs
• Double data entry at the site
• Rules to limit missing values, field validation errors, outliers, and invalid date entries

Medical coding: Medical dictionaries can also be used to create CRF items on medications prescribed to study subjects. Study users can be assigned the role of medical coder and given permissions to view and modify data entered on medications prescribed.

Data monitoring: source data verification, medical review, and data review: With source data verification, data entered into a CRF have to be separately verified by someone other than the user who entered the data, typically a site monitor who is given access to the specific data entries that require monitoring. The site monitor confirms that the monitoring duties have been carried out.

Documenting completed CRFs: Data entry users check a box at the end of each CRF to indicate that it has been completed. Data entry users can also be required to provide an e-signature for CRFs completed for each subject.

API Capabilities
REDCap Cloud uses a representational state transfer (REST) API with multiple capabilities to allow for automated data uploads, including allowing applications such as statistical software to connect to REDCap Cloud and modify and/or retrieve data, updating data that was previously collected, and transferring data between projects through automated exports.

Rules for Data Storage and Transfer
All data collected will be maintained and stored in REDCap Cloud. Datasets in CSV format (unless another format is requested) will be transferred using REDCap Cloud’s secure Send-It feature. The Send-It module can be used to send large (up to 500 MB) and/or sensitive files to one or more recipients in a HIPAA-compliant manner. A secure, password-protected link will be emailed to the recipient. The link typically expires within five days. In addition to the CSV data file, a link to a PDF file codebook will also be provided. Before receiving these links, the recipient must sign a data use agreement. Once received, data files must be stored at the recipient’s site in compliance with HIPAA.

Development of Procedures and Policies

The Discovery Steering Committee is responsible for developing and implementing procedures to ensure integrity in several areas.

Clinical informatics: Oversight and mechanics of collecting, managing, reporting, securing, and protecting Discovery research data and ensuring research data integrity.

Data and safety monitoring: Ensuring monitoring for each Discovery research activity, if appropriate based on the type of research being conducted.

Institutional review board (IRB), including a central IRB: The purpose of an IRB is to ensure that appropriate steps are taken to protect the rights and welfare of human participants in a research study. A central IRB reviews research studies for multiple sites. A central IRB is a single IRB of record for a given protocol. Before a clinical trial begins, the protocol (study plan) must be reviewed by a group of experts not connected with the research to ensure that it is ethical, provides potential benefits, and does not cause unnecessary harm to participants.

The Discovery DCC uses WCG IRB for both local and central IRB submissions. WCG IRB is an independent IRB that evaluates research protocols, ensuring adherence to ethical standards and regulatory requirements for studies involving human subjects. You can find more information here. Discovery engages with site personnel, ensuring efficient processes for initial, amended, and continuing review submissions.

Data policies and intellectual property: Any and all results and inventions from research and development in connection with Discovery programs will be detailed in a written agreement by all study participants before the project begins, including but not limited to intellectual property rights such as technical information, expertise, patent application rights, patent rights, data ownership, copyright, and trade secrets.

Creation of public use data: Data from Discovery studies constitute an important scientific resource. To enhance the public health benefit of these studies, public use datasets may be made available to qualified researchers. Discovery public-use datasets will generally be made available after initial study completion, in accordance with Discovery data protection procedures. Discovery datasets will be provided to secondary investigators who agree to adhere to the signed research data use agreement (RDUA). Data will also be created for NIH or other repositories as required by specific programs. Execution of an RDUA will require approval by the investigators’ relevant IRB or demonstration of exemption from the need for IRB approval by institutional policy.

Statistical Analyses and Data Monitoring

REDCap Cloud CRFs will be used to screen, enroll, and randomize subjects. The DCC will track enrollment and other results for transparent reporting, including the number randomized to each study arm and reasons for exclusion or loss to follow-up. The number enrolled by each site and the number randomized into each study arm will be provided in data reports to the study PI. The reports will include:

• CONSORT diagram with actual versus expected enrollment figures
• Data summary tables
• Data tables that show missing visits and missing CRFs
• Listings of adverse events (AEs), serious adverse events (SAEs), deaths, unanticipated problems (UPs), and protocol deviations and violations

The statistician will perform an interim analysis of the study according to an agreed-upon schedule. This analysis may examine whether the study could be considered for early termination and/or other analyses requested by the study PIs.

Study PIs will provide definitions of AEs, SAEs, and UPs and guidance for when they should be reported by participating sites. Site PIs are responsible for reporting AEs, SAEs, and UPs that occur at their site. AEs and SAEs will be reported in REDCap Cloud.

A CRF that can be used multiple times (as needed) will be available for reporting AEs and SAEs along with the other CRFs used to collect study data. The DCC will monitor AE and SAE submissions and provide detailed reports to the study PIs. The DCC, at the direction of the study PIs, will also provide reports to the central institutional review board (IRB), if in place; the DSMB; and any other required regulating bodies. Study CRFs may include alerts to participating sites indicating that an ASE or SAE may be required.

The DCC database administrator will monitor AE and ASE form submissions to REDCap Cloud and report all submissions to the study PI within 24 hours. The administrator will also prepare weekly reports on all AE and SAE submissions and will also monitor queries sent to study PIs advising them to submit AE and SAE forms. The study PI is responsible for reporting or directing that reports be made to IRBs, NIH, and U.S. Food and Drug Administration. An email alert system that provides a more immediate means for sites to report SAEs and UPs will be put in place so that PIs are made aware of the most serious issues as they occur.

Budgeting for Discovery DCC Effort Funding Proposals

Broad guidance on how to budget for Discovery DCC personnel. Budgeting for sufficient effort is crucial for these reasons:

1. Proposals that include insufficient effort will likely be penalized in the review process, thus reducing their chances of receiving funding.
2. Insufficient effort, even when funded, will limit flexibility to address changes in the approach, data management, or other key aspects of study operation.
3. Low funding results in personnel time being spread over a large number of projects and limits their ability to think creatively and work efficiently on any one project.

Contact Tamara Al-Hakim or Chase Hamilton for budget questions.