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Adverse Event Detection and Monitoring with AI

Article Summary: 

  • Adverse event detection through monitoring and AI tools benefits both the patient experience and the business. 
  • Conversation data is a valuable source of insights that help highlight issues in compliance, processes, and communication. 
  • Innovative tools like AI help identify instances of disruption and find trends in the patient experience through an omnichannel analysis of recorded contact center and hub conversations. 
  • AI can help improve adverse event detection by: 
    • Uncovering sources of friction 
    • Identifying trends and patterns  
    • Maintaining regulatory compliance 

What if there was a valuable source of insights for detection monitoring that lives within organizations already? 

Adverse event detection helps patients receive better care, gives leaders insights on products, and ensures regulatory bodies set mandates of accountability appropriately. Historically, pharma has lacked practical and productive ways to monitor and detect adverse events at scale.  

However, patient conversations unlock rich and reliable insights from contact centers, hub vendors, and omnichannel feedback – where patients organically discuss their experiences with drug and product quality, including the space to share complaints.  

Through innovative technology such as natural language understanding (NLU), machine learning (ML) algorithms, and generative AI (GenAI) tools, pharma leaders and hub vendors can analyze conversation data to identify instances of adverse events, such as unexpected side effects, drug interactions, or product malfunctions that occur in the patient population – thusly affecting regulatory compliance. 

AI is the ability to dive deeper into emerging trends. By analyzing conversation data, leaders can proactively detect adverse events and factors causing them before they become widespread problems creating market breakdowns and compliance risk. Detecting these events has a direct impact on brand perception, revenue management, and risks in the patient journey

Using Conversation Data Proactively for Detection

Continuous monitoring of conversation data is essential for identifying potential issues early and quickly addressing them. Immediate, ongoing feedback provides pharma leaders with data on the safety and quality of their products to maintain streamlined management for reporting and quality assurance. 

Without an efficient way to detect them, underreporting and nonreporting adverse events can: 

  • Harm patient health 
  • Disrupt product delivery 
  • Tarnish brand reputation 
  • Create legal liability  
  • Induce large penalties and fines 

Manually monitoring adverse events can be a daunting task, especially when dealing with large amounts of data. According to Oracle Life Sciences eBook, “The Next Domino”, large pharma companies handle about 700 adverse events each year. AI has the power to help increase the effectiveness and efficiency of these processes – addressing regulatory guidance for immediate action by supporting agents and leaders in routine adverse event monitoring that eases the burden on the company. 

Using AI to monitor and detect adverse events can improve the patient experience and ensure the safety and efficacy of pharmaceutical products and drugs. By leveraging the power of conversations through intentional, industry-specific intelligence platforms, pharma can gain valuable insights that may have otherwise gone unnoticed, leading to better outcomes and safety for patients. 

Checklist: 5 Benefits of Using AI to Scale Pharma Market Insights

Reliable Adverse Events Insights for Accurate Reporting

Detecting and addressing these events can be challenging, especially when relying solely on traditional methods of data collection and analysis that often don’t: 

  • Provide actionable insights 
  • Highlight trends impacting the patient experience 
  • Allow pharma to proactively detect adverse events for accurate and up-to-date reporting 

These insights can also help organizations identify other points of friction in the patient journey that contribute to disruptions and breakdowns affecting care (the Eddy Effect) that put compliance at risk. 

By turning contact centers and hubs into insight centers, organizations can gain valuable insights that enable them to address issues proactively and efficiently, ultimately improving the patient experience and enhancing the quality of care in real-time while minimizing a negative market impact (such as legal liability incurring penalties and fines) via inaccurate or incomplete compliance reporting. 

3 Ways AI Improves Adverse Event Detection and Monitoring

Adverse event detection and monitoring should be quickly and compliantly geared towards resolution, being proactive and responsive to disruptions to provide quality care for patients. Innovation in healthcare, such as AI, is making this process simpler and more efficient. There are three (3) ways that AI can help pharma leaders monitor and detect adverse events. 

  1. Uncover sources of friction. Points of friction along the patient journey may be causing patient complaints and adverse events, risking compliance efforts and patient health. By analyzing patient feedback and interactions, AI can identify issues or obstacles that your patients may be facing via process or by product. These insights can help you understand the challenges your patients are going through and take targeted action to address their concerns effectively. 
  2. Identify trends and patterns across multiple channels. Patients interact with healthcare in many ways, including telemedicine, emails, chats, and phone calls. AI can help you monitor these interactions across all channels to identify any trends that could lead to potentially serious outcomes. This proactive approach can help your brand by improving the mechanisms in place for communication and report management while keeping safety, security, and health at the forefront of each decision. 
  3. Maintain regulatory compliance with insights and reports. With additions and updates to regulations and reporting requirements, it can grow difficult to keep track of and find reliability in sharing metrics and findings. AI can help you stay on top of compliance issues and ensure that your brand, product, and services are providing patients with the care they seek and the accuracy necessary for regulatory reporting. This advantage of AI eases the daily burden of your company, making the mandated process more efficient and effective for reporting. 

With the power of AI, pharma leaders can find reliability and trust in monitoring and detecting adverse events. They benefit from AI adverse detection by developing an effective monitoring process that helps assure reliable reporting and abidance to compliance guidelines. By uncovering sources of friction, identifying trends and patterns, and maintaining regulatory compliance, conversation data can be utilized to proactively improve perception, communication, and adverse event reporting – improving the overall patient experience. 

Related Resources

Delivering Conversational Data Insights to Life Sciences | From Adverse Events to Patient-Centric Approaches | Scaling Regulatory Monitoring without Added Cost | Investment in Reliable AI | 3 Ways AI is Changing Listening | Anticipating the Next Era of AI | The Eddy Effect


About Authenticx

Authenticx is the new standard for humanizing conversational intelligence in healthcare by analyzing millions of customer interactions (like voice, chat, or emails) to surface immersive and intelligent insights at scale. Authenticx was founded to aggregate, analyze and activate customer interaction data to surface transformational opportunities in healthcare. Using existing data that’s likely being stored and ignored in your organization, Authenticx reveals hidden barriers, motivators, and strategies so healthcare organizations can make confident, data-backed decisions. In 2023, Authenticx was ranked No. 349 on the Inc. 5000 recognized as one of America and Indiana’s fastest-growing private companies. 

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