Dataset Information

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

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 the UCSF Medical Center over an 8 year period. We implemented a multidimensional data analytics framework to trace patients from admission through treatment to create a path of events. Events are any medications or 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), while the time difference from diagnostic Cardiac Catheterization to CABG is not statistically significant.

Conclusion

Women had a significantly longer interval between their first physician encounter indicative of CAD and their first diagnostic cardiac catheterization compared to men. Avoiding this delay in diagnosis may provide more timely treatment and a better outcome for patients at risk. Finally, we conclude by discussing the impact of the study on improving patient care with early detection and managing individual patients at risk of rapid progression of CAD.

SUBMITTER: Panahiazar M

PROVIDER: S-EPMC9729739 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Panahiazar Maryam M Bishara Andrew M AM Chern Yorick Y Alizadehsani Roohallah R Islam Sheikh M Shariful SMS Hadley Dexter D Arnaout Rima R Beygui Ramin E RE

Frontiers in cardiovascular medicine 20221124

<h4>Background</h4>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.<h4>Methods</h4>We used data analytics to risk stratify ~32,000 patients with CAD of the total 960,129 patients treated at the UCSF Medical Center over an 8 year period. We implemented a multidimensional data analytics framework to tr ...[more]

PMID: 36505372

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Dataset Information

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

Background

Methods

Results

Conclusion

Publications

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

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