A decision support framework for optimizing tube utilization in laboratory tests

In this project, the intern will design a decision support framework for optimizing tube utilization in laboratory tests. Given a prescription, the framework automates the tube selection process and outputs low cost tube configurations. The framework is designed to be easily adapted to different lab configurations. It consists of three processes, namely data profile configuration, tube optimization and solution prioritization. Data profile configuration process will formulate code and machine configuration files as the inputs to the tube optimization process. Solutions generated by tube optimization will then be evaluated by the solution prioritization process based on business and operational rules and preferences. Once integrated with mobile devices, users can obtain the optimized tube configuration in a real time manner by a simple scanning on the prescription. The proposed framework optimizes the tube utilization, reduces the cost throughout the whole laboratory testing process and saves time for agency, nurses and patients.

Faculty Supervisor:

Chun Wang


Jie Gao






Medical devices




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