Teaching Critical Thinking in the Age of AI: Safeguarding Clinical Reasoning in Healthcare Documentation

Abstract

AIM: To examine the implications of large language models (LLMs) in clinical documentation and explore strategies to preserve critical thinking among healthcare professionals in the age of artificial intelligence (AI). BACKGROUND: AI-powered documentation tools, particularly those using LLMs, are being rapidly adopted in healthcare to reduce administrative burden and enhance efficiency. However, concerns are emerging about their potential to undermine clinical reasoning, individualized care, and provider well-being. DISCUSSION: While AI offers substantial benefits, its overuse risks promoting automation complacency, exacerbating note bloat, and diminishing clinicians' critical thinking. Clinical documentation reflects a cognitive process central to diagnosis and care planning. Safeguarding this process requires targeted education in AI literacy, active verification of AI outputs, and deliberate training in reflective practice and clinical reasoning. CONCLUSION: AI must be integrated into clinical workflows with caution and transparency. Education and governance structures must prioritize critical thinking, accuracy, and ethical practice in documentation. IMPLICATIONS FOR NURSING PRACTICE AND HEALTH POLICY: Nurses must develop AI literacy and maintain active engagement in documentation to preserve high standards of care. Policymakers should mandate AI evaluation frameworks that include clinician cognitive load and safety, and embed AI and critical thinking education into all levels of health professional training.

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