Time-Based Comorbidity in Patients Diagnosed with Tobacco Use Disorder

Abstract

Healthcare is one of the promising fields where Big Data tools and techniques can have the highest impact. One of the key problems in the healthcare sector is to analyze impact of comorbidities. Comorbidity is a medical condition when a patient develops multiple diseases simultaneously. The research on finding comorbidities over time is rare. In this paper, our focus is to find time-based comorbidities in the patients diagnosed with Tobacco Use Disorder (TUD). First, we explain a generalized process to find chronological comorbidities. Then, we analyze electronic medical records of patients diagnosed with Tobacco Use Disorder from the hospitals in the West South-Central region of United States (1999–2013). Specifically, we discover comorbidities in the TUD patients across three hospital visits. We also compare the results with the patients who never developed TUD. We found interesting results indicating that some comorbidities are different in TUD and non-TUD patients over time, but not others. The knowledge about the time-based comorbidities can help physicians take preemptive actions to prevent future diseases.