Process Automation. Simplified.

70% Faster Clinical Complaint Resolution

Streamline clinical complaints, validation and site personnel communication with AI to deliver faster resolution.

Princeton Blue’s Clinical Complaint Management solution uses Appian AI to improve complaint handling in clinical trials. AI automates complaint review, validation, and categorization, while allowing for human intervention when necessary, reducing processing time and improving accuracy in managing clinical complaints.

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    Business Drivers for Clinical Complaint Management

    In the pharmaceutical industry, effective management of clinical complaints is crucial for maintaining the integrity of clinical trials, ensuring patient safety, and complying with regulatory requirements. The following business drivers underscore the need for an advanced Clinical Complaint Management solution:

    • Patient Safety and Trust: Timely and effective resolution of clinical complaints is essential for maintaining patient safety and trust in clinical trials, which directly impacts participant retention and study success.
    • Operational Efficiency: The traditional complaint handling process is labor-intensive and time-consuming. Improving efficiency in this area can significantly reduce operational costs and accelerate trial timelines.
    • Data Integrity: Accurate documentation and analysis of complaints are crucial for maintaining data integrity in clinical trials. This data often informs critical decisions about trial protocols and drug safety.
    • Resource Optimization: With the increasing complexity of clinical trials, there’s a growing need to optimize human resources by automating routine tasks and allowing experts to focus on high-value activities.
    • Scalability: As pharmaceutical companies expand their clinical trial portfolios, they require solutions that can efficiently handle a growing volume of complaints across multiple studies and geographic locations.
    • Risk Mitigation: Proactive identification and resolution of recurring issues through effective complaint management can help mitigate risks in clinical trials and improve overall trial outcomes.
    • Continuous Improvement: Insights gained from comprehensive complaint analysis can drive process improvements, enhancing the quality of future clinical trials and drug development efforts.

    By addressing these business drivers, an advanced Clinical Complaint Management solution becomes essential for pharmaceutical companies aiming to maintain their competitive edge, ensure regulatory compliance, and deliver superior clinical trial experiences.

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      Challenges with the Clinical Complaint Process

      The clinical complaint process often faces several significant hurdles:

      Time-intensive manual work: Reviewing, validating and recording incoming complaints requires substantial human effort, leading to potential delays in processing.
      Information gaps: Complaints frequently lack all necessary information when they are reported. This requires time-consuming back-and-forth communication with site personnel.
      Time Consuming Document Processing: Skilled personnel spend considerable time on reading and analyzing documents, limiting their availability for more complex problem-solving.

      Error-prone data entry: Manual data entry and information transfer between
      systems increase the risk of errors in complaint records.

      Scalability issues: As clinical trials grow in number of sites, patients and complexity, managing an increasing volume of complaints often becomes a bottleneck.
      Delayed response times: The manual nature of the process can result in slower response times to site personnel, potentially affecting participant satisfaction and retention.
      Limited real-time visibility: Tracking the status of complaints across multiple trials and sites can be difficult, hindering effective management and reporting.

      Addressing these challenges is crucial for pharmaceutical companies to maintain efficient operations, ensure regulatory compliance, and uphold the quality and integrity of their clinical trials.

      Streamlining Clinical Complaint Management with AI

      Princeton Blue’s Clinical Complaint Management solution leverages Appian’s Gen AI technology to enhance the efficiency and accuracy of complaint handling in clinical trials. The system automates the initial processing of complaints by analyzing incoming emails, extracting relevant data, and categorizing issues. When information is incomplete, the AI interacts with site personnel to gather additional details, ensuring thorough documentation without manual intervention.

      This automation significantly reduces processing time and human error while allowing skilled personnel to focus on complex problem-solving and complaint resolution. The solution also provides real-time visibility through a Clinical Complaint Portal, enabling both clinical staff and site personnel to track complaint status easily. With its comprehensive dashboard for trend analysis and consistent AI-driven processing, the system supports regulatory compliance and facilitates continuous improvement in clinical trial management.

      Gen AI-driven clinical complaint workflow

      Key Features of the Solution

      AI Powered Analysis

      AI-Powered Analysis

      Automatically extracts and categorizes data from complaint emails, identifying missing information.
      Intelligent Workflow

      Intelligent Workflow

      Streamlines the complaint process from intake to closure, assigning tasks based on type and complexity.
      AI Driven Communication

      AI-Driven Communication

      Engages with site personnel to gather information and generates tailored responses.
      Enhanced Visibility

      Real-Time Tracking

      Appian Portal provides secure access for site personnel to view their complaint status without requiring Appian credentials.
      Smart Document Summary

      Smart Document Summary

      Gen AI summarizes emails and attachments to expedite the review process.
      Human Oversight Integration

      Human Oversight Integration

      Requests human review for low-confidence AI decisions, ensuring accuracy in complex cases.
      Performance Dashboard

      Performance Dashboard

      Displays key metrics including human effort saved, complaint types, and resolution times.
      Scalable Architecture

      Scalable Architecture

      Adapts to handle increasing volumes and complexities of complaints across growing trial portfolios.

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