• Data Management Overview


    Research Translation Research Network (RTRN) Data Management (DM) department supports research using practices designed to improve data quality and promote efficiency. We provide expertise in all areas of data management, from study start up to completion, meeting best practices and ensuring data integrity.

    The Data Managers use a methodical approach to translate a research concept into a concrete method of collecting, organizing and verifying data to promote accurate reporting and data analysis. Data Managers work closely with each study team to develop a system that integrates well with research practices and effectively manages the data. We create study-specific data collection instruments as electronic Case Report Forms (eCRFs), and use a web-based application with built in security features for the research database.

    Throughout the life of the project, we can provide the necessary services and expertise to help manage and report data, providing clean data sets as needed. The Data Management department also works collaboratively with other RTRN units in order to supply researchers with comprehensive services that can streamline, and coordinate the many facets of a clinical research project such as standard CRFs, which leads to standardize CRFs and programming, etc.

    Through frequent coordination with project teams, DM department provides a seamless flow of data and a constant level of communication to ensure that projects meet deadlines and milestones, and keep clinical trials on track for timely conclusion. Our data management teams fully understand and comply with Good Clinical Data Management Practice (GCDMP) and Clinical Data Interchange Standards Consortium (CDISC) standards.

    What is Data Management?


    Data management is preparing a database application to receive the data, designing edit checks to protect against entry errors, entering the data, choosing between full and partial double-data entry, generating data queries to clean the data, validating the data, writing code for administrative reports, and exporting the data to the statistician's SAS program.

    What is Informatics?


    "Clinical informaticians transform health care by analyzing, designing, implementing, and evaluating information and communication systems that enhance individual and population health outcomes, improve patient care, and strengthen the clinician-patient relationship.“

    Gardner RM et al Core Content for the Subspecialty of Clinical Informatics J Am Med Inform Assoc. 2009 Mar-Apr;16(2):153-7




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    CDSI Capabilities

    Clinical Data Services and Informatics has been a cornerstone of our clinical research services here at DCC.  Our team of highly skilled data managers has amassed more than 40 years of expertise.  Our team of data managers is well versed in Good Clinical Data Management Practices (GCDMP), Clinical Data Interchange Standards, ICH Guidelines and all applicable laws and regulations to implement FDA-regulated and non-regulated studies.  In addition, the team has strong technical, programming, and communication skills.  The CDS&I leadership has worked with Pharmaceutical companies and Contract Resource Organization (CROs) in U.S., European and Caribbean markets.  They are recognized as Certified Clinical Research Professionals (C.C.R.P). Our clinical data programmers have years of experience with SAS programming, program validation checks, data listings and much more.  Our programmers are IBM DBS Certified Specialists.  Our team’s expertise covers diverse therapeutic areas including HIV Questionnaires, Idiopathic Pulmonary Fibrosis, Multiple Sclerosis, Oncology, Cardiovascular, Gastrointestinal, Hematology, Rheumatoid Arthritis, and Psoriasis.
    Our clinical data management staff is actively involved with the Society for Clinical Data Management (SCDM), Society of Clinical Research Associates (SoCRA) and Drug Information Association (DIA), and the Clinical Data Interchange Standards Consortium (CDISC).
    Our clinical data managers can support your Phase I up to Phase IV studies.   RTRN’s clinical data management team will provide a customized, cost-effective, and flexible approach to meet all of your data needs.
    For project consultation, contact Alnida M. Ngare at Alnida.Ngare@rtrn.net or 601 979-0335
    Access Services here

    CDSI Resources

    Our clinical studies are managed utilizing industry leading applications and tools.  RTRN’s clinical data managers provide investigators with all the necessary training required to conduct successful trials adhering to required laws and regulations.
    Database set-up and production is performed in OC or REDCap.

    Oracle Clinical is a secure, web-based, clinical research software system that provides an integrated Clinical Data Management (CDM) and Remote Data Capture (RDC) solution. It is the first validated clinical research system at the Data Coordinating Center (DCC) which is maintained as a 21 CFR Part 11 compliant system.
    Research Electronic Data Capture (REDCap) is a secure, web-based application designed to support electronic data capture for clinical research studies. REDCap is a manual data cleaning process.
    CTMS Siebel, a secure, web-based clinical trial management software platform to maintain a centralized trial management database for all investigators. It is essential to have a clinical trial management system (CTMS) that will provide on-the-fly visibility to critical trial data and operations milestones, while it meets the changing trial demands of CROs and Sponsors. CTMS offers several benefits including:

    • Benefit from a secure, stable and centralized access to
    • multiple sites, trials, and programs
    • Collect and manage patient and trial administration data in an efficient manner
    • Reduce trial administration costs in a dramatic fashion
    • Monitor, schedule, sign and submit trip reports electronically

    The DCC uses the Argus Safety System as an advanced and comprehensive adverse events (AE) management system.  Argus is a secure, web-based application provides a platform of end-to-end pharmacovigilance solutions designed to ensure regulatory compliance. The beneficial attributes of the system include:

    • Clinical vs. Safety database
    • Manual identification of discrepancies
    • Query generation/resolution
    • Database modification
    • Repetition, until perfect

    Our Quality Control process is intended to ensure that all data meets the specified requirements of cleanness. QC activities may be initiated as soon as the first set of Case Report Forms (CRFs) pages has been entered. Throughout the course of the study, samples of the database will be compared with corresponding in-house CRFs, DCFs, and SDCFs. The sample will consist of randomly selected CRFs based on the following formula:

    • 10% of the CRFs with a minimum of 3 when the total patient enrollment
    • is £ 120 and a number equal to (2 + the square root of n),
    • where n = total enrollment > 120).
    • If an error rate [>.05%] is detected, additional action may be
    • required to ensure data quality.

    Our CDS&I team aims to provide services that streamline the start-up, implementation and reporting of database functions for clinical and translational research across the research community.

  • Data Management Services


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    Protocol review

    We review the protocol to make sure that the information within the protocol will collect the necessary data that is inclusive for that study.

    • Sample size
    • Study duration
    • Quality Assurance
    • Schedule of assessments
    • Assessments to be used as source


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    Manual of Procedures (MOP)

    The MOP transforms the study protocol into specific guidelines that describe the study organization, operational definitions of the data, participant recruitment, screening, enrollment, randomization, and follow-up procedures, data collection methods, data flow, case report forms, and quality control procedures.
    This document is used when multiple sites are conducting the same protocol.

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    Case Report Form (CRFs)Development

    The Case Report Form (CRF)regardless if it is a paper or electronic is the tool used by the sponsor of the clinical trial to collect data from each participating site. All data on each patient participating in a clinical trial are held and/or documented in the CRF, including adverse events.

    Develop the design of CRFs
    • Protocol adherence
    • Accuracy of text
    • Ease of database set-up
    • User friendliness


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    Validation Specification Document

    A process where data is checked for accuracy and inconsistencies after validation is completed. Data discrepancy management includes reviewing discrepancies, investigating the reason, and resolving them with documentary proof or declaring them as irresolvable. If a discrepancy can not be resolved with the data being used, then a data query (Also known as a Data Clarification Form (DCF)) is sent to the site to resolve this issue.

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    Database Set-Up (Oracle Clinical (OC) and REDCap

    Oracle Clinical is a secure, web-based, clinical research software system that provides an integrated Clinical Data Management (CDM) and Remote Data Capture (RDC) solution. It is the first validated clinical research system at the Data Coordinating Center (DCC) which is maintained as a 21 CFR Part 11 compliant system.

    • Execution of individual validation procedures
    • Batch validation
    • Queries entered into the database
    • Sites answers the queries in the database
    • Query resolution checked in the database
    • Query is closed


    Research Electronic Data Capture (REDCap) is a secure, web-based application designed to support electronic data capture for clinical research studies. REDCap is a manual data cleaning process.

    • Screen review/testing
    • Site entry of data
    • Manual data review with listings
    • Manual Data Clarification Forms (DCFs) sent
    • Manually review the database for changes from the sites


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    Production Database

    The database is put into production after the database set-up has been completed and finalized. Some or all of the following activities can be performed depending on the type of database (OC or REDCap).

    • Data entered into the database
    • Review of all discrepancies
    • Data Clarification Form (DCF) creation (electronic or manually)
    • DCF resolution
    • Database modification


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    Clinical Trial Management System (CTMS)

    CTMS Siebel, a secure, web-based clinical trial management software platform to maintain a centralized trial management database for all investigators. It is essential to have a clinical trial management system (CTMS) that will provide on-the-fly visibility to critical trial data and operations milestones, while it meets the changing trial demands of CROs and Sponsors.

    • Benefit from a secure, stable and centralized access to multiple sites, trials, and programs
    • Collect and manage patient and trial administration data zin an efficient manner
    • Reduce trial administration costs in a dramatic fashion
    • Monitor, schedule, sign and submit trip reports electronically


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    Argus Safety and Argus Interchange System

    Here at DCC we use the Argus Safety System as an advanced and comprehensive adverse events (AE) management system. Argus is a secure, web-based application provides a platform of end-to-end pharmacovigilance solutions designed to ensure regulatory compliance.

    • Clinical vs. Safety database
    • Manual identification of discrepancies
    • Query generation/resolution
    • Database modification
    • Repeat until perfect


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    Quality Control (QC)

    QC is a process intended to ensure that all data meets the specified requirements of cleanness. QC may be initiated as soon as the first set of CRF pages has been entered. Throughout the course of the study, samples of the database will be compared with corresponding in-house CRFs, DCFs, and SDCFs. The sample will consist of randomly selected CRFs based on the following formula:

    10% of the CRFs with a minimum of 3 when the total patient enrollment is  120 and a number equal to (2 + the square root of n), where n = total enrollment > 120). If an error rate [>.05%] is detected, additional action may be required to ensure data quality.

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    Database Lock

    All expected information is in house or accounted for:

    • Case Report Forms completed or information entered into the database
    • Data Clarification Forms
    • Medical coding approved (if applicable)
    • SAE Reconciliation (if applicable)
    • Final Batch Validation/line listing review
    • Quality Control (QC)
    • Safety/Efficacy discrepancies resolved (if applicable)


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