Clinical Decision Support Using Colored Petri Nets: a Case Study on Cancer Infusion Therapy

We consider a drug infusion scenario in which a drug is delivered through an infusion pump to a patient, whose vital parameters are monitored via a bedside monitor. Drug infusion therapies are based on clinical protocols that are drug-specific and very diversified. The burden of their proper application on several patients lies, most of the times, on nursing staff alone. With the aim of making the choices safe and prompt and limiting human errors, we build a system that suggests the proper action based on the protocol and the status of the patient. Given the high variability of protocols, it is important to choose a flexible structure. We choose Hierarchical Colored Petri Nets (HCPN), a mathematical formalism for describing discrete event dynamic systems, which is, in fact, modular, expressive and admits a graphic representation. Cancer infusion therapy is the case study considered, as that clinical scenario is likely to become critical from a staff/patient ratio point of view, since the number of patients is continuously growing.