Practice Exploration on the Integrated Clinical-Rehabilitation Treatment Scheme Based on the Quality Function Deployment Model

Background To improve clinical rehabilitation efficacy, prognosis and reduce costs, our department developed rehabilitation software in 2021. By 2024, it ran over 400,000 times with > 95% order completion rate. The implementation of Diagnosis Related Groups payment reform in 2022 further demanded refined rehabilitation management for cost-quality dual control. Objective To explore the optimisation of an integrated clinical-rehabilitation management scheme using the quality function deployment model, and improve medical services’ quality. Methods A Kano questionnaire survey was conducted to understand users’ demands for integrated clinical rehabilitation and to determine the importance of these demands. The Quality House method of the quality function deployment model was applied to convert user demands into quality characteristic elements of integrated clinical-rehabilitation management, and the priority of improvement for each quality characteristic was determined using an independent scoring method. Results The scheme was optimised by focusing on the eight most important quality characteristics and a ranking of demand relevance. Finally, integrated clinical-rehabilitation management was optimised through these measures: improving the clinical decision support system knowledge base, establishing dynamic early warning and automatic medical insurance verification mechanisms, deepening the interconnection between rehabilitation treatment software and the electronic medical record system, refining the cooperation model between clinical departments and rehabilitation departments, and simplifying the rehabilitation workflow. After optimisation, the correct identification rate of rehabilitation contraindications, reminder rate of abnormal vital signs, reminder rate of critical values, and completion rate of rehabilitation records increased. However, the primary review failure rate of medical items, time consumption of rehabilitation treatment arrangement, and error rate of rehabilitation treatment arrangement decreased. All differences were statistically significant ( P  < 0.05). Conclusion The optimised management scheme based on the quality function deployment model meets clinical practice requirements. It ultimately improves medical services’ quality and efficiency, indicating a promising avenue for the adoption of this model.