Artificial intelligence in healthcare

Transforming Doctor-Patient Dynamics

The integration of AI fundamentally alters the doctor-patient relationship, traditionally characterized by information asymmetry (Ref. 47). AI empowers patients with unprecedented access to medical information, enabling them to conduct online symptom research and arrive with preliminary self-diagnoses. This challenges the doctor's traditional authority and strengthens patient autonomy, shifting decision-making power dynamics (Ref. 49, 50). The traditional dualistic interaction evolves into a doctor-AI-patient triad, where AI serves as an intermediary. While enhancing efficiency, this triad can also inadvertently increase physical and psychological distance, leading to potential trust crises and intensified disputes, especially in megacities (Ref. 52, 53, 54).

Megacity Context: Beijing's Unique Landscape

Beijing, a megacity with over 20 million permanent residents and a rapidly aging population (Ref. 27, 28), faces immense pressure on its healthcare system. Residents' high expectations, superior health literacy (44.6% in 2024), and a significant influx of non-local patients (12.80% of interprovincial patients in China) create complex, high-demand scenarios (Ref. 30, 31, 32). Medical resources are disproportionately concentrated in central areas, leading to overburdening of top-tier hospitals and a "siphoning" effect from community-level institutions (Ref. 33, 34).

Despite these challenges, Beijing's position as a global tech and innovation hub offers unique advantages. Its high R&D intensity (6.73%, first nationally), numerous universities, and strong policy support (e.g., Beijing Action Plan for Accelerating AI + Medical Health) facilitate AI integration (Ref. 41, 42, 44). Internet hospitals like PUMCH's (Ref. 40), telemedicine, and advanced clinical decision support systems are actively deployed to mitigate pressures and enhance public health management capabilities, making Beijing a crucial case study for AI in healthcare (Ref. 37, 38, 39).

Proactive Governance for AI Integration

Given the inevitability and profound impact of AI in healthcare, especially in megacities, proactive governance is crucial. This includes institutionalizing the doctor-AI-patient triad, where the doctor maintains primary decision-making authority while AI provides support. Leveraging megacity advantages, such as concentrated technological capital and talent, is key to pioneering AI integration that addresses systemic challenges like patient volume and resource distribution (Ref. 5.1, 5.2). Importantly, robust policy frameworks must be established to govern risks: clear laws for patient privacy and liability in medical disputes, ethical standards prioritizing patient interests, and strong regulatory oversight to proactively adjust relationships and mitigate issues arising from algorithmic discrimination and opacity (Ref. 5.3). The WHO emphasizes promoting universal access to these innovations while preventing inequity, underscoring the need for careful management.