Transforming Hospital Promotion Models with Artificial Intelligence

From “Human” to “Artificial Intelligence”: Reconstructing Hospital Promotion Models

In the context of building a healthy China and the rapid increase in public health demands, hospitals must adapt their promotional strategies. Continuing to rely solely on human efforts in planning, production, publishing, monitoring, and maintenance will not meet the new requirements for health communication. Therefore, transitioning hospital promotion work to be empowered by artificial intelligence is urgent.

Current Status and Limitations of Hospital Promotion Models

1. Staffing Challenges: Hospital promotion departments often face staffing shortages. The creation of content such as copywriting, graphics, videos, and educational materials heavily relies on human effort, leading to long production cycles and limited output that fails to meet the growing demand for health education.

2. Precision and Effectiveness: The accuracy and effectiveness of health education content need improvement. Traditional methods often involve uniform releases and broad pushes without accurately identifying audience demographics, disease risks, health needs, or key concerns, making targeted and effective communication challenging.

3. Delayed Response in Review Processes: The reliance on manual browsing and screening results in slow detection, evaluation, and response to public opinion, causing hospitals to miss optimal windows for guiding public sentiment and leaving them reactive in crisis management.

4. Limited Content Variety: In an era rich with new media formats like short videos, live streams, infographics, and animations, sticking primarily to text and graphics results in a lack of innovation and appeal, compounded by high operational costs and heavy human workloads.

The Necessity of Reconstructing Hospital Promotion Models

Given the responsibilities of hospital promotion departments in the new era of health communication, transitioning from traditional human-driven models to AI-driven approaches is inevitable. This shift is driven by:

• The shortcomings in current hospital promotion practices necessitating reform.
• The increasing demands placed on medical education and health promotion as the Healthy China strategy progresses.
• The continuous advancement of society and technology, which compels hospitals to enhance and perfect their promotional models.

By leveraging artificial intelligence, various aspects such as tool assistance, intelligent review, precise distribution, educational graphic and video production, and public sentiment monitoring can significantly enhance work efficiency. Thus, reconstructing hospital promotion models is imperative.

Three Key Directions for Reconstructing Hospital Promotion Models

AI-Driven Educational Graphic Production and Review

Creating educational graphics traditionally requires substantial time for data collection, content brainstorming, and copywriting, making the process labor-intensive. Variations in professional skills and writing styles lead to inconsistent quality. AI can utilize natural language processing to automatically extract relevant information from vast medical literature and case files based on predefined themes and keywords, generating draft content. AI can also tailor language to different audiences, using simpler terms for general public communication while employing precise medical terminology for professional educational materials. Moreover, AI can automatically select suitable images and charts based on the content and promotional goals, ensuring compliance with medical knowledge and legal regulations during the review process.

AI-Driven Short Video Production and Review

Producing educational short videos in hospitals involves expensive equipment, skilled personnel, and lengthy production cycles. Each stage, from scriptwriting to filming and editing, requires significant human resources and expertise. AI can automatically generate engaging scripts based on educational themes, and with virtual character generation and animation technologies, it can create virtual doctors and nurses that perform according to the script without actual filming, significantly reducing costs and time. AI can also evaluate video quality across multiple dimensions, ensuring content accuracy and adherence to medical knowledge and promotional requirements during the review phase.

AI for Automatic Monitoring of Hospital Public Sentiment

Currently, public sentiment monitoring in hospitals relies on manual browsing of news websites and social media, making it inefficient and unable to capture sentiment information comprehensively and timely. AI can monitor sentiment dynamics in real-time across multiple channels, assess emotional tendencies, and analyze patient feedback on hospital services and medical quality. It can also predict potential crises based on sentiment trends and generate detailed reports for hospital management, providing valuable decision-making insights.

While AI presents opportunities for reconstructing hospital promotion models, challenges such as precision, reliability, algorithm limitations, and privacy concerns must be addressed during implementation. Overall, the shift from human to AI in hospital promotion is not merely a technological upgrade but a profound systemic transformation.