2026面向未来的医疗调研报告_医患护视角下的_AI_17页_1mb

2026 Future Ready Healthcare Survey Report Summary

Core Content

The 2026 Future Ready Healthcare Survey Report by Wolters Kluwer explores the current and future use of AI in healthcare from the perspectives of patients, doctors, and nurses. It highlights the growing integration of AI into both clinical and personal healthcare workflows, while also identifying key challenges and areas for improvement.

Main Themes and Findings

1. AI as an Embedded Tool in Healthcare

• AI is becoming a routine part of the healthcare workflow, with over 80% of doctors and 76% of nurses using AI at least once a week for professional purposes.
• Patient use of AI is also increasing, with 81% of the youngest patients (18-24) and 56% of patients in their 30s and early 40s frequently bringing AI-generated information to medical appointments.
• The use of AI has significantly increased over the past three years, with doctors using it multiple times a day more than tripling since 2025.

2. Diverging Priorities in AI Adoption

• Clinicians focus on reducing administrative burdens, improving operational efficiency, and supporting clinical decision-making.
• Patients prioritize access to information, clarity, speed, and self-navigation capabilities in their healthcare journey.
• While both groups agree on the goal of better outcomes and smoother care experiences, they have different expectations for how AI should be used to achieve this.

3. Reshaping Clinical Dynamics

• AI is changing how patients and clinicians interact, with patients increasingly bringing their own research into clinical consultations.
• Clinicians are now more involved in interpreting and validating AI-generated information, which may affect their role and cognitive load.
• There is a strong alignment between patients and clinicians on the need for verification of AI outputs, with 78% of patients and 56% of clinicians expecting clinicians to double-check AI results.

4. Trust as a Critical Challenge

• Trust remains a major barrier to AI adoption, with clinicians and patients having different concerns.
• Clinicians are primarily worried about hallucinations, bias, and clinical deskilling (74% of clinicians are concerned about this).
• Patients are more concerned about data privacy, accountability, and transparency in AI use.
• Both groups emphasize the importance of human oversight in AI processes to prevent errors and maintain trust.

5. Governance and Transparency

• Governance of AI in healthcare is still underdeveloped, with most clinicians unaware of their organization's AI policies.
• Only 27% of doctors and nurses are aware of how their workplaces are addressing AI governance, up slightly from 2025.
• Clear labeling of AI-generated content and the inclusion of citations and sources are seen as critical to building trust.
• Clinicians and patients expect AI to be transparent and verifiable, with 72% of doctors and 59% of nurses wanting detailed reasoning behind AI outputs.

6. Concerns About Sponsored Content

• Both clinicians and patients are concerned about the potential for bias and influence from sponsored content within AI tools.
• Doctors are more cautious about commercial influence (77% express caution), particularly from pharmaceutical sponsors.
• Patients are especially wary of pharmaceutical sponsorship, with 70% indicating discomfort with its potential impact on clinical decisions.

7. Balancing AI Use and Human Roles

• AI is expected to support rather than replace human decision-making.
• There is a clear need to define boundaries for AI use to ensure it does not overstep into areas where human judgment is critical.
• Organizations must align their AI implementation strategies with both clinical workflows and patient expectations to avoid introducing new friction.

Key Information

• AI Use Trends: AI is now a common part of daily life for both clinicians and patients, with increasing frequency of use in both professional and personal contexts.
• Patient Expectations: Patients are using AI to understand diagnoses, research symptoms, and simplify medical jargon.
• Clinician Concerns: Clinicians are concerned about AI’s impact on clinical decision-making, deskilling, and bias.
• Trust and Transparency: Trust remains a significant hurdle, and both groups expect AI to be transparent, verifiable, and accountable.
• Governance Gaps: There is a lack of awareness and understanding of AI governance policies among clinicians, highlighting the need for better education and policy development.

Conclusion

The 2026 report underscores the transformative potential of AI in healthcare, but also the need for careful implementation and governance to ensure it enhances care without undermining trust or clinical integrity. As AI becomes more embedded in the healthcare ecosystem, aligning the expectations and roles of patients, clinicians, and health systems will be essential for realizing its full benefits.