Sequential portfolio decision model for epilepsy death risk reduction

Epilepsy is among the most frequent neurological diseases in the world affecting an estimated 43 million people. Thirty percent of epilepsy patients between the ages of 5 and 25 develop seizures related to illness or accidents involving an injury to the head. Decision making for prevention and care is crucial for fighting morbidity and mortality of such disease. Considering the multiplicity of diagnostic and treatment alternatives the best sequence of such alternatives should be the objective to detect for any pathologist and specialized physician in treating patients. Here, we introduce a portfolio decision model for the optimal detection of coupled diagnostic and treatment alternatives. The model is composed by two multicriteria decision analysis models which assess the risk of diagnostic and treatment alternatives as a function of alternative criteria, individual- and context-dependent criteria of patients. The minimization of the sequential risk considering all combinations of alternatives and their costs determine Pareto efficient frontiers that provide optimal solutions to decrease the mortality risk due to epilepsy for any resource level available. Preliminary results show that traditional diagnostic and treatment alternatives (i.e., EEG and ketogenic diet, respectively) are the highest scoring diagnostic alternative considering efficacy, potential risks of misdiagnosis, execution time, and time to process the results of the tests. This happens because of the limited data and application of the most recent innovative alternatives. The portfolio decision model is a very flexible model for formalizing pathology into systems pathology in a quantitative fashion. The approach is largely adoptable for any disease other than epilepsy and it makes physicians decision making transparent and quantitative based. The model emphasizes the strong importance to consider population health criteria, individual factors, and sequential decisions simultaneously for minimizing the systemic risk of diseases over time.