The Transformative Role of Data Engineering in Addressing Health Inequities: A Technical Perspective

Data engineering has emerged as a transformative force in addressing global health inequities, offering sophisticated solutions to persistent disparities in healthcare delivery. By leveraging advanced data integration architectures, machine learning algorithms, and real-time monitoring systems, healthcare organizations can better identify and address systemic barriers affecting marginalized populations. From cloud-native implementations to quantum computing applications, modern technical frameworks enable more precise resource allocation, improved patient matching, and enhanced predictive capabilities. The integration of social determinants of health data, coupled with privacy-preserving technologies and explainable AI models, facilitates a more comprehensive understanding of healthcare challenges while maintaining data security and patient trust. Through multidisciplinary approaches and innovative technical solutions, data engineering methodologies are reshaping healthcare delivery systems to create more equitable outcomes across diverse populations.

Authors

Publication Details

Journal
Journal of Computer Science and Technology Studies
Published
2025-04-24
DOI
https://doi.org/10.32996/jcsts.2025.7.2.34
Primary Topic
Public Health Policies and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

The Transformative Role of Data Engineering in Addressing Health Inequities: A Technical Perspective

Dipen Vasudev Patel
1 links
Journal of Computer Science and Technology Studies
Public Health Policies and Education
article

The Transformative Role of Data Engineering in Addressing Health Inequities: A Technical Perspective

Dipen Vasudev Patel
article en

Abstract

Data engineering has emerged as a transformative force in addressing global health inequities, offering sophisticated solutions to persistent disparities in healthcare delivery. By leveraging advanced data integration architectures, machine learning algorithms, and real-time monitoring systems, healthcare organizations can better identify and address systemic barriers affecting marginalized populations. From cloud-native implementations to quantum computing applications, modern technical frameworks enable more precise resource allocation, improved patient matching, and enhanced predictive capabilities. The integration of social determinants of health data, coupled with privacy-preserving technologies and explainable AI models, facilitates a more comprehensive understanding of healthcare challenges while maintaining data security and patient trust. Through multidisciplinary approaches and innovative technical solutions, data engineering methodologies are reshaping healthcare delivery systems to create more equitable outcomes across diverse populations.

Journal of Computer Science and Technology StudiesVol. 7(2)
Openalex Percentile: Top 86%
Public Health Policies and Education
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The Transformative Role of Data Engineering in Addressing Health Inequities: A Technical Perspective — Dipen Vasudev Patel · Journal of Computer Science and Technology Studies (2025) | TGRS Research Map | TGRS