This module teaches you to apply protocol criteria when documenting clinical findings—determining whether results meet inclusion thresholds, trigger exclusion, or require safety follow-up. You'll complete a simulated case report form in a virtual browser lab environment using Microsoft Excel, applying protocol criteria to participant data. This is the core operational skill coordinators perform at every screening and follow-up visit—translating clinical findings into protocol-compliant documentation.

This module walks you through the lifecycle of clinical trial data from the moment a finding is recorded at a study visit through entry into a database, query resolution, cleaning, and final database lock. You will describe this process through structured text box responses that demonstrate understanding of each stage. Coordinators interact with this data flow daily, and knowing what happens downstream from your entries helps you understand why accuracy and timeliness matter so much.

This module teaches you to respond to data queries in an electronic data capture workflow—locating source support, determining the correct response, and documenting corrections—then manage corrected records in a PHI-compliant SharePoint library. You'll practice this workflow through a guided hands-on activity using annotated EDC screenshots and structured source documents. Query resolution is one of the most frequent operational tasks coordinators perform, and doing it correctly prevents data quality issues from compounding toward a database lock.

This module teaches you to coordinate study visits—screening, enrollment, and follow-up—using protocol calendars built in Microsoft Excel within Teams. You will apply visit window calculations, track participant status, and verify that scheduling aligns with protocol-required timing. In a virtual browser lab, you will build a functioning protocol calendar that manages multiple participants across study visits. Coordinators live by their visit calendars—they are the tool that prevents missed visits, expired windows, and protocol deviations.

This module teaches you to organize and maintain study communication records—tracking issues, action items, and follow-up tasks across multiple stakeholders using a shared Excel spreadsheet in Microsoft Teams. You will build a communication log in a virtual browser lab that tracks outstanding issues, assigns ownership, and documents resolution. Clear communication tracking prevents items from falling through the cracks and demonstrates site organization during monitor visits.

This module teaches you to manage participant study records with the accuracy, security, and version control required by clinical research. You'll perform a supervised data entry exercise in a virtual browser lab—transcribing source data into Microsoft Excel, then uploading to SharePoint with proper naming conventions and version history. These procedures protect participant confidentiality and data integrity at every step and serve as the operational foundation for every record a coordinator touches.

This module teaches you to spot common data integrity risks that threaten study data quality—transcription errors, missing fields, duplicate entries, and unauthorized changes. You'll conduct a checklist review of sample study data in Microsoft Excel, identifying mistakes and potential integrity issues that may require escalation. Coordinators who catch integrity risks before monitors or data managers find them protect their site's reputation and prevent downstream data quality concerns.

This module explores how generative AI tools such as Copilot can support clinical data workflows—from drafting query response language to identifying patterns in data entry errors. Using a generative AI tool, you'll evaluate AI-generated outputs for accuracy, compliance, and appropriateness before applying them to clinical research tasks. Understanding AI's capabilities and boundaries is an emerging professional advantage—coordinators who can leverage AI responsibly while maintaining GCP compliance and PHI protections add measurable value to their study teams.

This project integrates clinical assessment planning, data management procedures, visit coordination, and communication tracking into a comprehensive operational plan for a simulated Phase III diabetes trial with 5 active participants. You'll build an assessment checklist, protocol calendar, communication log, and data-handling workflow using Microsoft Excel, Teams, and SharePoint. High-performing sites distinguish themselves through operational organization; this plan is what sponsors evaluate during quarterly reviews to determine whether your site earns future study opportunities.