Personal Health Large Language Models and the Negotiation of Medical Authority in Clinical Care: Opportunities, Risks, and Governance - Scorecard - MDSpire

Personal Health Large Language Models and the Negotiation of Medical Authority in Clinical Care: Opportunities, Risks, and Governance

  • By

  • Wenyi Xie

  • Jialin Liu

  • Siru Liu

  • June 25, 2026

  • 0 min

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Clinical Scorecard: Navigating Medical Authority in Clinical Practice: The Role of Personal Health Large Language Models and Their Implications for Governance and Risk Management

At a Glance

CategoryDetail
ConditionPersonal Health Large Language Models (PH-LLMs)
Key MechanismsSynthesize user-entered information, patient-generated health data, wearable data, and personal health records into personalized health narratives.
Target PopulationPatients using consumer-facing health technology.
Care SettingClinical encounters influenced by patient-generated health narratives.

Key Highlights

  • PH-LLMs differ from traditional EHR-tethered AI by being initiated by patients.
  • Functions of PH-LLMs range from low-risk health education to higher-risk chronic disease management.
  • The use of PH-LLMs may shift clinician-patient interactions toward a triadic model of authority.

Guideline-Based Recommendations

Diagnosis

    Management

      Monitoring & Follow-up

        Risks

        • Epistemic conflict, fragmentation of clinical truth, privacy and data-governance concerns, and diffusion of accountability.

        Patient & Prescribing Data

        Users of personal health technology and PH-LLMs.

        PH-LLMs may influence patient expectations and clinical decisions.

        Clinical Best Practices

        • Establish governance frameworks to ensure safety and accountability in PH-LLM use.
        • Integrate clinical arbitration and workflow considerations in the deployment of PH-LLMs.

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        Original Source(s)

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