Medication prescriptions are an important intervention in the healthcare process. Computerized systems are increasingly used to enter and communicate prescriptions, so called Computerized Provider Order Entry (CPOE systems). Current CPOE systems use a varying degree of structuredness for entering and communicating prescriptions. They range from free text to completely structured entry. The benefit of structured prescription entry is that computers are able to (partially) interpret prescriptions and check their validity and safety, e.g., for example with respect to the latest medical practice guidelines and potential adverse drug events (drug interactions, allergies, etc.)
Another recently emerging use case for computer interpretable prescriptions are Adherence Monitoring and Improvement technologies. Such technologies are coming on the market to provide caregivers with feedback about how well patients manage to follow their prescriptions and to help patients with increasing their adherence to prescriptions. Adherence monitoring requires a formal, computer interpretable model of the meaning of prescriptions. No such model exists to date. Our lab has conducted research on this topic and proposed a first approach to close that gap. We developed a formalization of prescriptions based on the definition of a graph transformation system. This was done in the context of an honours thesis by Simon Diemert, supervised by Morgan Price and Jens Weber. A paper on this approach has been accepted to the 8th Intl. Conf. on Graph Transformations (ICGT) and will be presented In July in L’Aquila.