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Generative AI in healthcare: redefining clinical practice through digital transformation.
Jackie Zhanbiao Li1,2, Xin Li3, Qifeng Wu4
1Curtin University Malaysia Faculty of Business, Miri, Malaysia. lizhanbiao123@163.com.
Health Economics Review
|June 27, 2026
Summary
Generative AI (GenAI) significantly improves healthcare effectiveness by enhancing diagnostics, efficiency, and patient satisfaction. Its impact is amplified in highly digitalized regions, offering practical implementation insights.
Area of Science:
- Health Informatics
- Artificial Intelligence in Healthcare
- Technology Diffusion
Background:
- Generative AI (GenAI) presents significant potential for healthcare transformation.
- The effectiveness and mechanisms of GenAI in healthcare require further investigation.
- Existing research has not sufficiently explored the application of GenAI in healthcare systems.
Purpose of the Study:
- To investigate the application effectiveness of GenAI in the healthcare sector.
- To explore the underlying mechanisms through which GenAI impacts healthcare.
- To provide insights for practical implementation and policy optimization of GenAI in healthcare.
Main Methods:
- Utilized a dataset of 1,440 samples from 160 hospitals across 31 provinces in China.
- Data collection period spanned from 2021 to 2024.
- Employed quantitative analysis to assess GenAI's impact and moderating factors.
Main Results:
- GenAI significantly enhances healthcare effectiveness, improving diagnostic accuracy, operational efficiency, and patient satisfaction.
- The positive effects of GenAI are moderated by the degree of industrial digitalization.
- Highly digitalized regions demonstrated greater effectiveness of GenAI applications.
Conclusions:
- GenAI is a powerful tool for improving healthcare outcomes and operational efficiency.
- Digital infrastructure is crucial for maximizing the benefits of GenAI in healthcare.
- Findings offer valuable insights for healthcare providers and policymakers regarding GenAI adoption.
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