A rule engine-based medical examination intelligent reservation and resource scheduling system
The intelligent appointment and resource scheduling system for medical examinations based on a rules engine solves the problems of uneven resource allocation, rigid appointment process, and difficulty in multi-system collaboration in medical examinations. It realizes dynamic optimization of resources and full-process collaboration, thereby improving the efficiency and intelligence level of medical services.
Patent Information
- Application Number
- CN202610317612.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-03-16
- Publication Date
- 2026-06-16
AI Technical Summary
The existing hospital medical examination appointment system suffers from problems such as localized shortages and idle resources, frequent appointment conflicts, multiple trips for patients, and the need for extensive manual intervention by medical staff. Furthermore, it lacks the ability to flexibly model and perform real-time calculations on complex medical rules, resulting in uneven resource allocation, rigid appointment processes, and difficulties in multi-system collaboration.
The system adopts a rule engine-based intelligent appointment and resource scheduling system for medical examinations, which includes modules for data collection, rule engine, intelligent appointment, resource scheduling, and process control. Through multi-source data resource pools, rule parsing, and dynamic matching, it generates resource scheduling strategies and appointment priority sequences, enabling personalized recommendations, conflict detection, and dynamic resource scheduling, thereby improving resource utilization and process collaboration.
It achieves dynamic optimization of resources and closed-loop collaboration throughout the entire process, shortens patient waiting time, reduces operating costs, improves the efficiency and intelligence level of medical services, and solves the problems of uneven resource allocation, rigid appointment process and difficulty in multi-system collaboration.
Smart Images

Figure CN122224440A_ABST
