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. 2025 Apr 25;15(1):14518.
doi: 10.1038/s41598-025-98552-5.

A NLP analysis of digital demand for healthcare jobs in China

Yirui Chen  1 , Xinrui Zhan  1 , Wencan Yang  1 , Xueying Yan  1 , Yuxin Du  1 , Tieniu Zhao  2
Affiliations

A NLP analysis of digital demand for healthcare jobs in China

Yirui Chen et al. Sci Rep. .

Abstract

The rapid growth of the healthcare industry in China has led to a significant talent gap, particularly in the areas of digital skills and management expertise. This study aims to bridge this gap by analyzing healthcare job listings using natural language processing (NLP) techniques to identify specific skills and management capabilities in high demand. We collected 58,732 healthcare job listings from eight major recruitment websites in China, focusing on positions requiring a bachelor's degree or higher and posted within the last year. To extract relevant information from job descriptions, including required skills, qualifications, and roles, we employed an AI agent based on the latest ChatGPT model. The model was fine-tuned using advanced Prompt-Tuning techniques to adapt it to the specific context of healthcare job listings. This involved designing task-specific prompts, preprocessing the data to remove duplicates and normalize text, and training the model using the Hugging Face Transformers library. The analysis revealed a strong demand for technical skills such as data analysis, AI and machine learning, and technology integration. Compliance and data privacy skills were also highly demanded, reflecting the healthcare sector's commitment to regulatory adherence and data security. Additionally, management and leadership skills were identified as critical. Regional disparities were observed, with higher demand for digital skills in urban areas such as Beijing and Shanghai compared to rural regions. Emerging roles such as "digital health strategist" and "chief data officer" were also identified, highlighting the need for interdisciplinary collaboration and innovation. This study provides valuable insights into the current and future talent demands in the healthcare industry. By leveraging NLP techniques to analyze job listings, we can identify specific skill gaps and develop targeted strategies for talent development and recruitment. This research contributes to the understanding of the healthcare talent gap and offers practical recommendations for policymakers, healthcare providers, and educational institutions to ensure a sustainable and skilled workforce in the healthcare sector. Future research should explore additional data sources and qualitative methods to gain a more comprehensive understanding of healthcare talent needs globally.

Keywords: Digital skills in healthcare; Job analysis in China; Medical talent gap; Natural language processing.

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Conflict of interest statement

Declarations. Competing interests: The authors declare no competing interests.

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Semantic network diagram.
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