AUTHOR=Panahiazar Maryam , Bishara Andrew M. , Chern Yorick , Alizadehsani Roohallah , Islam Sheikh M. Shariful , Hadley Dexter , Arnaout Rima , Beygui Ramin E. 

TITLE=Gender-based time discrepancy in diagnosis of coronary artery disease based on data analytics of electronic medical records

JOURNAL=Frontiers in Cardiovascular Medicine

VOLUME=Volume 9 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/cardiovascular-medicine/articles/10.3389/fcvm.2022.969325

DOI=10.3389/fcvm.2022.969325

ISSN=2297-055X

ABSTRACT=Background: Women continue to have worse Coronary Artery Disease (CAD) outcomes than men. The causes of this discrepancy have yet to be fully elucidated. The main objective of this study is to detect gender discrepancies in the diagnosis and treatment of CAD. Methods: We used data analytics to risk stratify ~32,000 patients with CAD of the total 960,129 patients treated at UCSF Medical Center during eight years. We implemented a multidimensional data analytics framework to trace patients from admission through treatment to create a set of the path of events. Events are any medications, noninvasive and invasive procedures. 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. Finally, we applied statistical analysis to determine differences in time between diagnosis and treatment steps for men and women. Results: There is a significant time difference from the first time of admission to diagnostic Cardiac Catheterization between genders (p-value=0.000119).
In contrast, the time difference from diagnostic Cardiac Catheterization to CABG is not statistically significant. Conclusion: Women had longer intervals between their first physician encounter indicative of CAD and their first diagnostic cardiac catheterization than men significantly. Avoiding the delay in diagnosis may provide on-time treatment and a better outcome for patients at risk. And finally, we conclude the study with the impact of the study on improving patient care with early detection and managing individual patients at risk of rapid progression of CAD.