ArticleScientific reports2025
A NLP analysis of digital demand for healthcare jobs in China.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Article
- Body fat percentage and hypertension risk: A population-based observational and Mendelian randomization study.Medicine · 2026Observational
- Article
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Authors and funding
6 authors.
Funding
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.
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Registered trials
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