2026生成式AI时代下的临床决策白皮书-欧洲医疗从业者的新兴行为信号洞察_20页_4mb

Summary of "Clinical Decision-Making in the Era of Generative AI"

Core Content

This white paper explores the integration of generative AI (GenAI) into clinical decision-making among healthcare professionals (HCPs) in Europe, focusing on its adoption patterns, usage behavior, and strategic implications for the pharmaceutical and life sciences industries. The study, conducted by IQVIA in December 2025, surveyed oncologists and general physicians across France, Germany, and the United Kingdom, revealing a significant shift in how clinicians access, interpret, and apply medical information.

Key Findings

• Widespread Adoption:

  • $85%$ of surveyed HCPs use GenAI in their work, with $92%$ of specialists like oncologists reporting usage.
  • $41%$ of HCPs use GenAI daily, and $73%$ engage with it at least weekly.
  • France leads in adoption ($91%$), followed by the UK ($88%$) and Germany ($79%$).

• Usage Patterns:

  • GenAI is used primarily to support clinical reasoning, literature review, and treatment evaluation, rather than for workflow automation.
  • Common use cases include disease information, guideline checks, and treatment comparisons.
  • Educational and diagnostic needs are the most frequent drivers of GenAI use, as seen in real prompts.

• Access Models:

  • Most HCPs access GenAI through personal devices and free plans.
  • Institutional funding for GenAI tools remains limited, with only a small minority having access through their organizations.
  • Free versions dominate, but personal subscriptions are increasing, indicating perceived value beyond casual use.

• Trust and Challenges:

  • High satisfaction with GenAI tools coexists with cautious trust, especially in decision-critical contexts.
  • Reliability and source transparency are the primary concerns, with unclear or undisclosed sources being the most cited issue.
  • HCPs are wary of the medical validity and accuracy of outputs, even when they are used as a support tool.

• Non-Users and Institutional Readiness:

  • Only $15%$ of HCPs do not use GenAI, but their concerns are consistent and reflect institutional readiness issues.
  • Common barriers include lack of perceived benefit, medico-legal uncertainty, privacy concerns, and absence of formal approval.
  • Institutional endorsement is a key trigger for broader adoption.

Strategic Implications

• Medical Affairs:

  • Must shift from being a "sole source of truth" to a strategic partner in an AI-mediated environment.
  • Should optimize scientific communication for AI interpretation to ensure peer-reviewed evidence is accurately conveyed.

• Commercial and Sales Operations:

  • Need to pivot toward high-value, personalized interactions that complement AI tools rather than replicate their functions.
  • The "pull" dynamic is emerging, where HCPs actively seek information and verify claims in real-time using GenAI.

• Content and Evidence Transparency:

  • Clear, structured, and scientifically rigorous content is essential to maintain integrity in AI-mediated workflows.
  • Evidence architecture becomes a strategic factor in how information is accurately transmitted and interpreted.

• Governance and Institutional Enablement:

  • Institutional governance and approval will play a critical role in the future integration of GenAI into clinical practice.
  • The current gap between individual adoption and institutional readiness presents both risk and opportunity for organizations.

What This Signals

• GenAI has moved from experimentation to operational integration within clinical workflows.
• It functions as a cognitive support tool, influencing how HCPs access and process medical knowledge.
• While widely used, it is not yet fully trusted in high-stakes clinical decisions.
• The shift in information-seeking behavior suggests that future engagement models must adapt to a more distributed, AI-assisted environment.

Conclusion

The paper underscores the need for pharmaceutical and life sciences organizations to align their strategies with the evolving role of GenAI in clinical practice. As HCPs increasingly rely on AI for support, the focus must shift toward ensuring medical rigor, transparency, and institutional governance to foster broader and more confident adoption.

Document Structure

• Executive Summary: Highlights the shift from experimental to routine use of GenAI in clinical decision-making.
• Survey Findings: Details adoption patterns, usage frequency, and access models across European countries.
• Usage Patterns: Explains how HCPs use GenAI for clinical thinking, not workflow automation.
• Trust and Institutional Readiness: Discusses concerns around reliability, transparency, and the role of institutional approval.
• Strategic Implications: Outlines the need for changes in medical affairs, commercial strategies, and content delivery.

Key Information

• GenAI Usage: $85%$ of HCPs use GenAI in their work, with oncologists being the most frequent users.
• Primary Use Cases: Disease education, literature review, guideline checks, and treatment support.
• Tools Used: ChatGPT is the most widely used, followed by Gemini, Copilot, Perplexity, and DeepSeek.
• Access Models: Most users rely on personal devices and free plans, with limited institutional support.
• Challenges: Reliability, source transparency, and medical specificity are the main concerns.
• Non-User Concerns: Focus on medico-legal uncertainty, privacy, and lack of formal approval.
• Future Outlook: Institutional enablement will be crucial in accelerating and formalizing GenAI integration into clinical practice.