A grammar-based approach to model the patient´s clinical trajectory after a mild traumatic brain injury

Despite the significant amount of longitudinal information that Electronic Health Records (EHRs) include, modeling the progression of a particular disease is still a challenging task. Generally, when the trajectory of a cohort of patients is analyzed some patients take similar paths from/to a certain clinical disease while others take vastly different paths. Most existing approaches to analyze trajectories of a patient have focused on a specific disease with the intention of being able to predict whether a new patient will develop a similar diagnosis or not. This paper presents a novel approach to identifying the trajectory of patients by modeling the clinical path as an automata and using grammar induction to reduce the graph. The resulting reduced model represents the common trajectory for the patients without incorporating events that are specific to a particular patient. The proposed model has been tested with 5,000 patients that have sustained a mild traumatic brain injury (mTBI) and have developed post-traumatic stress disorder (PTSD). The model has produced a trajectory indicating the common clinical path that those patients take from their first mTBI to their first diagnosis of PTSD.