Data Analytics of Electronic Medical Record to Study Racial Diversities in Cardiovascular Diagnosis and Treatment

The study of precision medicine that measures the effects of social, cultural, and environmental influences on health is essential to improve health outcomes. Race is a social concept used historically to divide, track, control populations, and reinforce social hierarchies. Beyond genetics, race is...

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Autores principales: PANAHIAZAR, Maryam, CHERN, Yorick, RIOJAS, Ramon, LATIF, Omar S., HADLEY, Dexter, BEYGUI, Ramin E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10342194/
https://www.ncbi.nlm.nih.gov/pubmed/35612140
http://dx.doi.org/10.3233/SHTI220519
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author PANAHIAZAR, Maryam
CHERN, Yorick
RIOJAS, Ramon
LATIF, Omar S.
HADLEY, Dexter
BEYGUI, Ramin E.
author_facet PANAHIAZAR, Maryam
CHERN, Yorick
RIOJAS, Ramon
LATIF, Omar S.
HADLEY, Dexter
BEYGUI, Ramin E.
author_sort PANAHIAZAR, Maryam
collection PubMed
description The study of precision medicine that measures the effects of social, cultural, and environmental influences on health is essential to improve health outcomes. Race is a social concept used historically to divide, track, control populations, and reinforce social hierarchies. Beyond genetics, race is also a surrogate for other socioeconomic factors affecting patient outcomes. Our data analytics study aims to analyze the Electronic Medical Record (EMR) to study patients of different races in diagnosing and treating Coronary Artery Disease (CAD). We found no race discrepancies at the University of California San Francisco Medical Centers. This study opens several new hypotheses for further research in this crucial field.
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spelling pubmed-103421942023-07-13 Data Analytics of Electronic Medical Record to Study Racial Diversities in Cardiovascular Diagnosis and Treatment PANAHIAZAR, Maryam CHERN, Yorick RIOJAS, Ramon LATIF, Omar S. HADLEY, Dexter BEYGUI, Ramin E. Stud Health Technol Inform Article The study of precision medicine that measures the effects of social, cultural, and environmental influences on health is essential to improve health outcomes. Race is a social concept used historically to divide, track, control populations, and reinforce social hierarchies. Beyond genetics, race is also a surrogate for other socioeconomic factors affecting patient outcomes. Our data analytics study aims to analyze the Electronic Medical Record (EMR) to study patients of different races in diagnosing and treating Coronary Artery Disease (CAD). We found no race discrepancies at the University of California San Francisco Medical Centers. This study opens several new hypotheses for further research in this crucial field. 2022-05-25 /pmc/articles/PMC10342194/ /pubmed/35612140 http://dx.doi.org/10.3233/SHTI220519 Text en https://creativecommons.org/licenses/by-nc/4.0/This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0).
spellingShingle Article
PANAHIAZAR, Maryam
CHERN, Yorick
RIOJAS, Ramon
LATIF, Omar S.
HADLEY, Dexter
BEYGUI, Ramin E.
Data Analytics of Electronic Medical Record to Study Racial Diversities in Cardiovascular Diagnosis and Treatment
title Data Analytics of Electronic Medical Record to Study Racial Diversities in Cardiovascular Diagnosis and Treatment
title_full Data Analytics of Electronic Medical Record to Study Racial Diversities in Cardiovascular Diagnosis and Treatment
title_fullStr Data Analytics of Electronic Medical Record to Study Racial Diversities in Cardiovascular Diagnosis and Treatment
title_full_unstemmed Data Analytics of Electronic Medical Record to Study Racial Diversities in Cardiovascular Diagnosis and Treatment
title_short Data Analytics of Electronic Medical Record to Study Racial Diversities in Cardiovascular Diagnosis and Treatment
title_sort data analytics of electronic medical record to study racial diversities in cardiovascular diagnosis and treatment
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10342194/
https://www.ncbi.nlm.nih.gov/pubmed/35612140
http://dx.doi.org/10.3233/SHTI220519
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