Although smart healthcare is advancing rapidly, its implementation still faces six key challenges: deployment issues, misalignment between technology and medical needs, ethical and regulatory concerns, social acceptance, data security, and data privacy. Specifically, high hardware requirements make it difficult for economically underdeveloped regions and primary healthcare institutions to deploy smart healthcare solutions. During research and development, technology often fails to align with real-world medical needs, preventing frontline healthcare demands from being fully met. Additionally, regulations often lag behind technological advancements, leading to unclear responsibilities in medical incidents, inadequate rights protection, and potential ethical risks. Patients and doctors may also take a cautious approach to adopting new technologies, slowing down widespread adoption. Furthermore, data security and privacy concerns are not just technical risks but also critical to maintaining patient trust and the long-term sustainability of the system.

This paper presents an implementation case study - intelligent cervical spine function assessment based on hand motion videos, detailing how it overcomes the six aforementioned challenges in its complete development lifecycle. Specifically, deployment challenges were addressed through lightweight technical solutions and smartphone-compatible assessment software for primary hospitals and communities. To prevent technology-demand mismatch, the research team maintained continuous communication with clinicians through regular collaborative meetings. Ethical and law compliance was ensured through strict adherence to regulatory requirements and ethical reviews. Social acceptance was enhanced through training sessions and popular science publicity activities Data security was strengthened through both technical safeguards and collaborative policy development with hospital partners. Patient privacy protection was institutionalized via standardized data collection and annotation protocols. These measures enabled the project's successful deployment, which provided free cervical spine screening services to numerous community populations, and was recognized in the "2022 Annual Case Collection on CCF Tech for Good".

Despite the persistent challenges of smart healthcare implementation, particularly in the era of rapidly evolving large models, techniques like knowledge distillation, knowledge infusion, and retrieval-augmented generation show promise for empowering small models to leverage the capabilities of large models, addressing the computational resource limitations of resource-constrained devices. This technical evolution may catalyze further advancement of smart healthcare in the large model era.