The challenge: Making HTA understandable to everyone

Health technology assessments (HTAs) play a critical role in determining which treatments and innovations are adopted within healthcare systems. However, the technical language and complexity of HTA reports often make them inaccessible to patients and caregivers — the very individuals whose lives these decisions affect the most.

Plain Language Summaries (PLS) are designed to close this gap. They can translate HTA findings into clear, patient-friendly language, empowering people to engage meaningfully in healthcare decisions. Yet, producing high-quality PLS documents is a slow and resource-intensive process. Teams must balance scientific rigor with readability, cultural sensitivity, and accuracy — a demanding task that limits scalability.

This is where artificial intelligence (AI) offers a transformative opportunity.

The study: Can generative AI help bridge the communication gap?

At ISPOR Europe 2025, we presented a pioneering study exploring whether generative AI can create accurate and patient-friendly summaries from complex HTA documents.

Using a NICE Highly Specialized Technologies (HST) guidance on onasemnogene abeparvovec (a gene therapy for spinal muscular atrophy), the team tested Google Gemini, a large language model, to generate a full PLS automatically.

The AI-generated summary was evaluated across 18 quality measures covering readability, accuracy, relevance, and tone. A “human-in-the-loop” reviewer ensured alignment with patient communication standards and European HTA Regulation principles — integrating transparency and patient empowerment into the assessment.

The results: Speed meets substance

The results were striking. The AI produced an eight-page (2,570-word) PLS in just 15 seconds, structured around all key HTA components — disease context, treatment mechanism, clinical effectiveness, safety, and patient impact.

Across 18 evaluation criteria, the PLS achieved an average score of 8.27/10, reflecting strong alignment with plain language and patient-centered communication standards.

• Mechanism simplicity (9.2/10) and plain language explanation (8.9/10) were top-performing categories, demonstrating Gemini’s ability to simplify complex gene therapy concepts without sacrificing accuracy.
• The document met CEFR B1 readability, ensuring accessibility for non-specialist audiences.

However, the AI struggled with target population clarity (6.8/10) and unmet need articulation (6.5/10) — areas requiring deeper contextual and emotional nuance. These findings underscore the importance of maintaining a human role in refining and validating AI outputs, especially when tailoring content for specific patient groups.

The implications: Toward patient-centered HTA with AI

The study demonstrates that AI can accelerate and enhance the creation of patient-friendly HTA communications, promoting inclusivity and transparency in healthcare decision-making. But it also emphasizes that AI should complement, not replace, human expertise.

Generative AI tools like Gemini can help:

• Scale patient engagement, enabling broader and faster dissemination of accessible HTA information.
• Support regulatory compliance, aligning with EU HTA Regulation principles of transparency and participation.
• Enhance health literacy, fostering more equitable and informed patient involvement.

Yet, meaningful adoption requires:

• Human-in-the-loop systems to verify accuracy, tone, and contextual relevance.
• Prompt optimization to capture nuances like unmet needs or cultural differences.
• Ongoing validation to ensure reliability and regulatory alignment.

The conclusion: AI as a partner in patient empowerment

This work highlights how AI, when thoughtfully integrated, can make HTA more human-centered, transparent, and inclusive. Rather than automating empathy, it can help scale understanding — bringing patients into the conversation, not leaving them behind.

As HTA continues to evolve under new European regulations, embedding AI into communication workflows may mark a key step toward a truly patient-centered future — where every individual can understand, question, and contribute to the health decisions that shape their lives.

Interested in learning more?

Read the abstract published at ISPOR EUROPE 2025: “Can Generative AI Deliver Patient-Friendly Summaries? A Case Study Using NICE Guidance for Spinal Muscular Atrophy” by Manuel Cossio and Ramiro E. Gilardino.

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