Case Study

Scaling Clinical Research with an Automated Duplicate-Prevention Registry and Data Quality Workflows

Client

Industry

Region

North America, Asia Pacific, South America, EU (HIPAA & GDPR Compliant)

Overview

Clinical Research, a leading clinical research organization operating across multiple regions, faced serious risks caused by duplicate and professional subjects entering multiple studies under different identities. This led to compromised data integrity, regulatory concerns, and delays in study timelines. They also needed reliable Study/Protocol-wise visit tracking and a controlled process ensuring that only trained and certified site users could enter participant data.

To address these challenges, Prime Horizon Technologies delivered two integrated, high-security solutions.

Prime Horizon Technologies engineered CTSdatabase to serve as a centralized clinical trial subject registry. They designed it specifically to detect and prevent duplicate subjects without exposing private or identifiable information.

Anonymity by Design: Prime Horizon Technologies ensured the system maintains complete subject anonymity while identifying attempts by professional subjects to alter their presentation.
Investigative Insights: They provided investigators with a full history of a subject’s past study participation. They delivered actionable match insights that enable confident enrollment decisions.
Access Control: Prime Horizon Technologies enforced site-user training and certification requirements before any subject data can be entered.

Alongside this, Prime Horizon Technologies developed the Clinical Research Data Quality Program. They strengthened oversight of Study/Protocol-wise visit data and automated quality-control workflows. They significantly improved data accuracy and overall operational reliability across sites. Together, these platforms transformed the client’s clinical operations.

Technologies Used

Dot Net

Power Apps

DataBricks

Power Automate

EF Core

JWT Authentication

xUnit

Next.js

React

Azure Web App

React Query

Azure SQL

Redis Cache

Azure Application Insights

Azure Firewall

Azure DevOps

Power BI

NextAuth

.NET 8

MediatR

FluentValidation

IQVIA

Challenges & Solutions

Challenges Faced by the Client

High risk of duplicate and professional subjects enrolling across different clinical trial sites, threatening study integrity.
Need a secure, privacy-preserving identity verification mechanism without collecting or exposing personal information.
Complex multi-step workflows for rater surveillance, quality monitoring, and Study/Protocol-wise visit management.
Lack of real-time insights, making it difficult for site users, sponsors, and analysts to track operational KPIs.
Inconsistent or outdated data across systems, leading to reporting gaps and compliance risks.
Scalability limitations as the number of studies, sponsors, and trial sites continued to grow.
Need to ensure site-user training and certification compliance before allowing any study data entry.

Solutions provided by Prime Horizon Technologies

Prime Horizon implemented CTSdatabase, a centralized subject registry with advanced duplication-prevention logic to block repeat or professional subjects—while maintaining complete anonymity.
They enabled the management of Sponsor-wise and Study/Protocol-wise operations across all trial sites.
Developed secure authentication & authorization flows for Site Users, System Admins, and Sponsors with role-based access control.
Built a Clean Architecture + CQRS–based backend, ensuring long-term maintainability, modularity, and scalability.
Integrated Azure Application Insights for comprehensive logging, monitoring, and performance metrics.
Automated scientific and operational workflows through Azure DataBricks ETL pipelines and Power Platform integration.
Delivered dynamic Power BI dashboards for operational, analytical, and regulatory reporting across all stakeholder groups.
Implemented robust global error handling, structured logging, and complete API documentation for seamless operations.
Added compliance workflows ensuring site-user training and certification before data entry, reducing human-error risks.

Measurable Results

Increased efficiency

80% faster participant screening time due to automated checks.

Cost savings

Reduced operational costs by 50%

Growth metrics

The system now scales thousands of users across multiple clinical study networks without performance issues.

Time saved

Reduced manual data entry time by 60%.

Team Involvement

Resources	Count
Solution Architect	1
Backend Developers	2
Frontend Developers	2
Power Platform Developer	1
Project Manager	1
SQA	2

Core Features of CTSdatabase V4

Advanced duplicate-subject prevention with high-accuracy identity-matching logic.

Turn operational data into useful insight. We bring together dependable pipelines, clear reporting and accessible interfaces so teams can make informed decisions.

Real-time screening insights with actionable match reports for faster, safer enrollment decisions.

Custom Power BI dashboards for operational, sponsor-specific, and regulatory reporting

Turn operational data into useful insight. We bring together dependable pipelines, clear reporting and accessible interfaces so teams can make informed decisions.

Features of Clinical Research Data Quality Program

Comprehensive rater surveillance, performance tracking, and compliance monitoring

Automated Study/Protocol-wise data quality workflows that reduce manual effort and errors

User-friendly Power Apps web interface for site-level and sponsor-level operations

Scalable Azure DataBricks ETL pipelines for scientific, statistical, and operational data processing

Advanced analytical dashboards for real-time decision making and study oversight

Module: Sponsor Portal Dashboard

1. Protocol Violation Monitoring

This visualization offers sponsors immediate insight into why subjects are flagged or disqualified within a selected study. It aggregates specific rule violations to highlight common eligibility breaches, such as washout failures or active enrollment in other trials.

Visualizes total flag counts categorized by violation type (e.g., Age/BMI, Active in Another Study).
Includes interactive tooltips that display the specific flag name, count, and severity level.
Updates the dataset automatically whenever a different study is selected from the dashboard.

2. Cross-Therapeutic Indication Analysis

This visualization provides a breakdown of medical indications associated with matched subjects to track cross-study participation history. It helps sponsors identify if professional subjects are attempting to enroll across conflicting therapeutic areas, such as switching between Schizophrenia and Depression studies.

Visualizes the percentage distribution of matched indications (e.g., Schizophrenia, Depression, Migraine).
Labels each chart segment clearly with the specific indication name and its calculated percentage.
Updates the dataset automatically whenever a different study is selected from the dashboard.

Development Timeline

Prime Horizon Technologies initiated the development of this comprehensive clinical trial ecosystem in June 2023. The project is currently an ongoing engagement, characterized by continuous platform enhancements and the scaling of advanced features through a long-term strategic partnership.

Future Prospects

Planned integration with Azure ML: They are building predictive models to identify professional subject behavior.
Predictive Analytics: They are developing modules for predictive data quality scoring.
Cloud Optimization: They provide ongoing maintenance and cloud cost optimization.
Long-term Collaboration: They provide continued enhancements to the platform through an ongoing strategic partnership.

Collaborative software engineering, shaped around your priorities.

Secure Your Clinical Trial Data Integrity

Need to prevent duplicate subjects, improve data quality, or automate clinical research workflows? Talk to Prime Horizon’s healthcare technology team about building secure, compliant, and scalable clinical trial systems.

Tech Stack

Full