International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 7, Issue 2 (March-April 2025) Submit your research before last 3 days of April to publish your research paper in the issue of March-April.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 7 Issue 2
March-April 2025

Submit your research paper

Indexing Partners
Academia Advanced Sciences Index Bielefeld Academic Search Engine CiteSeer DRJI Google Scholar Independent Search Engine & Directory Network ISI (International Scientific Indexing) Issuu Mendeley Research Networks
RefSeek ResearcherId - Thomson Reuters ResearchGate Scirus Scribd Semantic Scholar UTeM - Universiti Teknikal Malaysia Melaka Wiki for Call for Papers WorldCat Zenodo

A Technical Review Of Dynamic And Mixed Approach For Health Data Extraction, Transformation And Loading Process

Author(s) Adya Mishra
Country United States
Abstract Healthcare data originates from a diverse array of sources—including electronic health records (EHRs), laboratory systems, wearable devices, and unstructured clinical text—making its integration a complex endeavor. Traditional extraction, transformation, and loading (ETL) pipelines, though foundational, often struggle to keep pace with evolving data schemas, regulatory obligations, and the need for real-time insights. This paper provides a technical review of dynamic and mixed ETL strategies tailored specifically for health data. Dynamic approaches emphasize adaptive schema discovery, rule-based transformations, and metadata-driven designs that automatically adjust to new and updated data sources, reducing manual reconfiguration. Mixed ETL models integrate both real-time streaming and batch processing, enabling healthcare organizations to process time-critical clinical data immediately while performing more complex transformations on larger datasets at scheduled intervals. Key challenges—including data quality assurance, regulatory compliance, and the requirement for robust security—are addressed alongside recommended best practices for metadata management, rule engines, and orchestration tools. The review further highlights implementation considerations and future trends, such as AI-driven data integration, serverless architectures, and data mesh paradigms. By adopting these flexible, scalable ETL approaches, healthcare institutions can enhance the accuracy, timeliness, and security of patient data analytics—ultimately improving clinical decision-making and patient outcomes.
Keywords Electronic health records, Extraction, Transformation and loading
Field Engineering
Published In Volume 2, Issue 2, March-April 2020
Published On 2020-04-09
DOI https://doi.org/10.36948/ijfmr.2020.v02i02.35776
Short DOI https://doi.org/g82qxh
View / Download PDF File

Share this



E-ISSN 2582-2160
CrossRef

CrossRef DOI is assigned to each research paper published in our journal.

IJFMR DOI prefix is
10.36948/ijfmr

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 7 Isu 2Cover Page Vol 7 Isu 1Cover Page Vol 6 Isu 6

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About IJFMR
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics
Peer Review & Plagiarism 		Join as a Reviewer
Editors & Reviewers
Reviewer Referral Program
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us +91-9687-828-838 editor@ijfmr.com