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Review Article Open Access December 26, 2021

Designing Scalable Healthcare Data Pipelines for Multi-Hospital Networks

Sasi Kumar Kolla 1,*
1
Independent Researcher, USA
Publihed in: Current Research in Public Health (Volume 1, Issue 1, 2021)
Page(s): 1-14
DOI: 10.31586/wjcmr.2021.1376
Received
October 02, 2021
Revised
November 09, 2021
Accepted
December 22, 2021
Published
December 26, 2021
Keywords
Health Data Analytics; Healthcare Data Pipeline; Clinical Decision-Making Support; Data Governance; Healthcare Data Silos; HTAP
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright: Copyright © The Author(s), 2021. Published by Scientific Publications
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APA Style
Kolla, S. K. (2021). Designing Scalable Healthcare Data Pipelines for Multi-Hospital Networks. Current Research in Public Health, 1(1), 1-14. https://doi.org/10.31586/wjcmr.2021.1376
ACS Style
Kolla, S. K. Designing Scalable Healthcare Data Pipelines for Multi-Hospital Networks. Current Research in Public Health 2021 1(1), 1-14. https://doi.org/10.31586/wjcmr.2021.1376
Chicago/Turabian Style
Kolla, Sasi Kumar. 2021. "Designing Scalable Healthcare Data Pipelines for Multi-Hospital Networks". Current Research in Public Health 1, no. 1: 1-14. https://doi.org/10.31586/wjcmr.2021.1376
AMA Style
Kolla SK. Designing Scalable Healthcare Data Pipelines for Multi-Hospital Networks. Current Research in Public Health. 2021; 1(1):1-14. https://doi.org/10.31586/wjcmr.2021.1376 
@Article{crph1376,
AUTHOR = {Kolla, Sasi Kumar},
TITLE = {Designing Scalable Healthcare Data Pipelines for Multi-Hospital Networks},
JOURNAL = {Current Research in Public Health},
VOLUME = {1},
YEAR = {2021},
NUMBER = {1},
PAGES = {1-14},
URL = {https://www.scipublications.com/journal/index.php/WJCMR/article/view/1376},
ISSN = {2831-5162},
DOI = {10.31586/wjcmr.2021.1376},
ABSTRACT = {Healthcare is increasingly recognized as a data-intensive industry. Multi-hospital networks, among other organizations, face mounting operational and governance challenges because of rigid data-integration pipelines that support all data sources and destinations in the network. These pipelines have become difficult to modify, causing them to lag behind the changing needs of the clinical operation. Scalable data-pipeline architectures better support clinical decision making, optimize hospital operations, ease data quality and compliance concerns, and contribute to improved patient outcomes. Meeting scalability goals requires breaking up monolithic data-integration pipelines into smaller decoupled components and aligning service-level agreements of pipeline components and source systems. Parallelization and adoption of distributed data-warehouse technology mitigate the burden of ingesting data into a multi-hospital network. However, latency requirements still warrant the construction of separate pipelines for data ingress from clinical devices, electronic health records, and external laboratory-information systems. Healthcare associations recommend near real-time data availability for a growing list of clinical and operational applications. Mishandling the real-time ingestion of data from clinical devices, in particular, compromises availability and performance. Scalable architectural patterns for real-time streaming Ingestion from heterogeneous data sources, transport processes, and back-end processing structures are detailed.},
}
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AB  - Healthcare is increasingly recognized as a data-intensive industry. Multi-hospital networks, among other organizations, face mounting operational and governance challenges because of rigid data-integration pipelines that support all data sources and destinations in the network. These pipelines have become difficult to modify, causing them to lag behind the changing needs of the clinical operation. Scalable data-pipeline architectures better support clinical decision making, optimize hospital operations, ease data quality and compliance concerns, and contribute to improved patient outcomes. Meeting scalability goals requires breaking up monolithic data-integration pipelines into smaller decoupled components and aligning service-level agreements of pipeline components and source systems. Parallelization and adoption of distributed data-warehouse technology mitigate the burden of ingesting data into a multi-hospital network. However, latency requirements still warrant the construction of separate pipelines for data ingress from clinical devices, electronic health records, and external laboratory-information systems. Healthcare associations recommend near real-time data availability for a growing list of clinical and operational applications. Mishandling the real-time ingestion of data from clinical devices, in particular, compromises availability and performance. Scalable architectural patterns for real-time streaming Ingestion from heterogeneous data sources, transport processes, and back-end processing structures are detailed.
DO  - Designing Scalable Healthcare Data Pipelines for Multi-Hospital Networks
TI  - 10.31586/wjcmr.2021.1376
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