Use runtime verification to improve the quality of medical care practice

Clinical guidelines and decision support systems (DSS) play an important role in daily practices of medicine. Many text-based guidelines have been encoded for work-flow simulation of DSS to automate health care. During the collaboration with Carle hospital to develop a DSS, we identify that, for some complex and life-critical diseases, it is highly desirable to automatically rigorously verify some complex temporal properties in guidelines, which brings new challenges to current simulation based DSS with limited support of automatical formal verification and real-time data analysis. In this paper, we conduct the first study on applying runtime verification to cooperate with current DSS based on real-time data. Within the proposed technique, a user-friendly domain specific language, named DRTV, is designed to specify vital real-time data sampled by medical devices and temporal properties originated from clinical guidelines. Some interfaces are developed for data acquisition and communication. Then, for medical practice scenarios described in DRTV model, we will automatically generate event sequences and runtime property verifier automata. If a temporal property violates, real-time warnings will be produced by the formal verifier and passed to medical DSS. We have used DRTV to specify different kinds of medical care scenarios, and applied the proposed technique to assist existing DSS. As presented in experiment results, in terms of warning detection, it outperforms the only use of DSS or human inspection, and improves the quality of clinical health care of hospital