A Trend of Eight-Years Big Data Analytics of Electronic Medical Records to Review and Study Diagnosis and Treatment of Coronary Artery Disease in Different Genders

Background: Cardiovascular Disease (CVD) and Coronary Artery Disease (CAD) in particular, is one of the leading causes of death, morbidity, and mortality in the United States. Notably, women continue to have worse outcomes than men. The causes of these discrepancies have yet to be fully elucidated. The main objective of this study is to detect gender discrepancies in outcome using data analytics to risk stratify ~ 32,000 patients with CAD of the total 960,129 patients treated at UCSF Medical Center during an eight years. As an implementation of clinical care, this study’s long-term goal is to improve precision diagnosis and ultimately management of CAD for both early detection and identification of patients at risk for rapid progression of the disease.Methods: We designed and implemented a multidimensional framework to trace patients from admission through treatment as a path of events. The time between events for a similar set of paths was calculated. Then the average waiting time for each step of the treatment was calculated for men and women. Finally, we applied statistical analysis to determine differences in time between diagnosis and treatment steps for men and women.Discussions: There were statistically significant gender-based differences in the common path of diagnosis and treatment of patients with CAD. The average time for women from the first visit to diagnostic Cardiac Catheterization was more than 2 months than for men (358.77 vs. 291.83 days). By contrast, the average time from diagnostic Cardiac Catheterization to treatment Cardiac Catheterization and Coronary Artery Bypass Grafting (CABG) was not significant. Women with CAD requiring revascularization have a significantly longer interval between their first physician encounter indicative of CVD and their first diagnostic cardiac catheterization compared to men. Avoiding the delay in diagnosis and treatment will provide a better outcome for patients at risk.