Reducing COPD Readmissions: A Causal Bayesian Network Model - IEEE Journals

S. Lee and S. Wang and P. Bain and C. Baker and T. Kundinger and C. Sommers and J. Li
This paper introduces a causal Bayesian network model to study readmissions reduction for chronic obstructive pulmonary disease (COPD) patients. The model employs a Bayesian network learning method and adopts domain knowledge. Using this model, we analyze the impacts of critical variables on a patient's readmission risk by manipulation of such variables. Through this analysis, effective intervention options to reduce readmission can be identified, which can provide a quantitative tool for designing personalized interventions to reduce COPD readmissions.
Posted 21 Oct 2018 · Link