Data Analytics of Electronic Health Records to Enhance Care of Coronary Artery Disease in Younger Women with Avoiding Possible Delay in Treatment

Maryam Panahiazar; Andrew M Bishara; Yorick Chern; Roohallah Alizadehsani; Omar S Latif; Dexter Hadley; Ramin E Beygui

doi:10.3233/SHTI220277

Data Analytics of Electronic Health Records to Enhance Care of Coronary Artery Disease in Younger Women with Avoiding Possible Delay in Treatment

Stud Health Technol Inform. 2022 Jun 6:290:1080-1081. doi: 10.3233/SHTI220277.

Authors

Maryam Panahiazar^{1

2}, Andrew M Bishara^{3

2}, Yorick Chern⁴, Roohallah Alizadehsani⁵, Omar S Latif⁶, Dexter Hadley⁷, Ramin E Beygui¹

Affiliations

¹ Department of Surgery, Division of Cardiothoracic Surgery, School of Medicine, University of California San Francisco, San Francisco, CA, USA.
² Bakar Computational Health Sciences Institute, School of Medicine, University of California San Francisco, San Francisco, CA, USA.
³ Department of Anesthesia and Perioperative Care, University of California San Francisco, San Francisco, CA, USA.
⁴ Department of Bioengineering, University of California Berkeley, Berkeley, CA, USA.
⁵ Institute for Intelligent Systems Research and Innovation, Deakin University, Australia.
⁶ Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA.
⁷ Department of Clinical Sciences, College of Medicine, University of Central Florida, Orlando, FL, USA.

Abstract

Early detection plays a key role to enhance the outcome for Coronary Artery Disease. We utilized a big data analytics platform on ∼32,000 patients to trace patients from the first encounter to CAD treatment. There are significant gender-based differences in patients younger than 60 from the time of the first encounter to Coronary Artery Bypass Grafting with a p-value=0.03. This recognition makes significant changes in outcome by avoiding delay in treatment.

Keywords: Coronary Artery Disease; Data Science; Electronic Health Records.

MeSH terms

Coronary Artery Bypass / adverse effects
Coronary Artery Disease* / diagnosis
Coronary Artery Disease* / surgery
Data Science
Electronic Health Records
Female
Humans
Risk Factors
Time-to-Treatment
Treatment Outcome

Grants and funding

U01 LM012675/LM/NLM NIH HHS/United States