REDCap Public Health Research Data Capture Training Course

Course overview

Public health programmes depend on timely, defensible data from surveillance sites, clinics, laboratories, community teams and partner organisations. Yet many REDCap projects are built as basic forms rather than governed data-capture systems: eligibility logic is inconsistent, identifiers are exposed, follow-up records cannot be linked reliably, offline fieldwork creates duplicates, and exports require extensive cleaning before analysis. This course enables practitioners to design and manage REDCap projects that support outbreak investigations, service evaluations, population surveys, registries and implementation research while meeting practical requirements for data quality, privacy and auditability.

Participants build advanced REDCap capabilities for public health research operations. They configure longitudinal projects, repeating instruments, events and arms; create branching logic, calculated fields, action tags and automated survey invitations; apply data access groups and user-rights controls; and use Data Quality rules, record locking and logging to govern data collection. The course also covers instruments for informed consent, pseudonymised participant IDs, sensitive health and social-care variables, fieldworker workflows, mobile offline collection, API-enabled exchange, reporting and reproducible export preparation.

Teaching combines instructor-led demonstrations with guided configuration in a REDCap training environment. Each day uses realistic public health scenarios, including contact follow-up, community survey recruitment and multi-site service monitoring. Participants progressively build a governed REDCap project and finish with a project build pack: a data dictionary, instrument specification, longitudinal workflow map, access-control plan, quality-control rules and export plan that can be adapted for their own service or study.

The course is designed for professionals who already work with research, surveillance, evaluation or service data and need to move beyond basic REDCap form building. It is equally relevant to staff responsible for designing projects and to those who must assure that a project is safe, usable and ready for analysis.

Course objectives

By the end of this course, participants will be able to:

• Design a REDCap data dictionary with validated fields, coded response options, calculated variables and field annotations
• Configure longitudinal events, arms, repeating instruments and repeating instances for follow-up-based public health studies
• Build branching logic, action tags and automated survey invitations for participant-specific data-collection workflows
• Implement pseudonymised identifiers, Data Access Groups, user rights and record locking for controlled multi-site access
• Create informed-consent, eligibility and adverse-event instruments appropriate to public health research governance
• Apply REDCap Data Quality rules, discrepancy workflows and audit-log review to identify and resolve data issues
• Configure REDCap Mobile App workflows for offline community or field-based data capture and synchronisation
• Produce a deployable REDCap project build pack containing a data dictionary, workflow map, access plan and export specification

Benefits of attending

Target competencies

Who should attend

• Public Health Researchers — who design studies and need reliable participant-level data collection
• Research Data Managers — who configure, govern and quality-assure REDCap projects across teams
• Clinical Research Coordinators — who manage consent, screening, follow-up and study visit records
• Epidemiologists — who require structured surveillance and outbreak-investigation datasets
• Monitoring and Evaluation Officers — who collect programme indicators across services, sites or communities
• Health and Social Care Service Improvement Leads — who need auditable data for evaluations and implementation projects

Requirements and prerequisites

Participants should have experience working with public health, clinical, research, surveillance or service-evaluation data and be comfortable with concepts such as variables, response codes, identifiers, missing data and basic data confidentiality. Prior use of REDCap is expected at the level of creating or editing a simple project, instrument or report; participants should know how to navigate a web-based data-capture system. Familiarity with Excel or CSV files is useful for reviewing data dictionaries and exports. SQL, R, Python, statistical modelling and API programming are not required. A personal REDCap administrator account is not required because a training environment is provided.

Training methodology

The five-day programme alternates focused instructor demonstrations with guided builds in a REDCap training instance. Participants configure instruments from a public health case dataset, then test each other’s projects as fieldworkers, site coordinators and data managers. Workshops cover data dictionaries, longitudinal setup, consent workflows, access controls, mobile collection, quality rules and exports. Small-group reviews examine design trade-offs for sensitive data and multi-site studies. On the final day, each participant applies the methods to a project build pack and receives structured instructor feedback.

Course outline

Day 1: Designing public health REDCap projects

• REDCap project types and public health use cases
• Translating a protocol into a data-collection workflow
• Data dictionary structure and variable naming conventions
• Field types, validation settings and coded response values
• Required fields, missingness codes and unknown responses
• Calculated fields and standardised derived variables
• Instrument design for screening, enrolment and baseline assessment

Workshop: Build a baseline and eligibility instrument for a community respiratory-disease surveillance study and produce an initial REDCap data dictionary.

Day 2: Longitudinal follow-up and participant workflows

• Longitudinal projects, arms and event definitions
• Assigning instruments to events in the event grid
• Repeating instruments and repeating events
• Record identifiers and pseudonymised participant ID design
• Branching logic for eligibility and clinical pathways
• Action tags for field display, defaults and data protection
• Automated survey invitations and alert notification logic

Workshop: Configure enrolment, weekly follow-up and outcome events for a contact-monitoring project, including repeat follow-up forms and automated invitations.

Day 3: Governance, privacy and multi-site control

• User rights, roles and least-privilege access design
• Data Access Groups for clinics, regions and partner sites
• Identifier fields, de-identification and pseudonymisation approaches
• Informed-consent documentation and e-consent workflow options
• Record locking, electronic signatures and approval checkpoints
• REDCap logging and audit-trail review
• Sensitive-variable handling for safeguarding and social-care data

Workshop: Create an access-control matrix and configure Data Access Groups, user roles and record-locking rules for a multi-site maternal health evaluation.

Day 4: Field collection, quality assurance and interoperability

• REDCap Mobile App setup and offline data-collection workflows
• Data resolution workflow and mobile synchronisation controls
• Data Quality module rules and custom discrepancy checks
• Missing-data review and query-management procedures
• Reports, dashboards and operational monitoring views
• CSV export options, field labels and coded-value preparation
• REDCap API concepts and CDISC ODM data exchange

Workshop: Test an offline household survey workflow, synchronise records, run Data Quality rules and document a discrepancy-resolution log.

Day 5: Deployment-ready REDCap project delivery

• User acceptance testing scripts and role-based test cases
• Version control for data dictionaries and instrument changes
• Production migration and change-management procedures
• Data collection status monitoring and escalation thresholds
• Export specifications for epidemiology and evaluation analysis
• Project documentation for governance and handover
• REDCap project review against a public health readiness checklist

Workshop: Complete and present a deployment-ready project build pack containing the data dictionary, workflow map, access plan, test script and export specification.

Tools & standards covered

REDCap, REDCap Mobile App, CDISC ODM, HL7 FHIR

A typical training day

Live online deliveries follow the same structure in the East Africa Time zone, with shorter screen blocks and longer breaks.

What the fee includes

How you can take this course

Certification

Participants who complete the full five days receive the Skillset Development Certificate of Completion, stating the course title, course code, dates and delivery format — suitable for professional-development records and employer reimbursement.

Frequently asked questions