Revolutionizing Healthcare Data Management: A Novel Master Data Architecture for the Digital Era

SAI TEJA BOPPINITI

Abstract


The healthcare sector is witnessing an unprecedented surge in data volume and complexity, driven by the adoption of electronic health records (EHRs), telemedicine, and precision medicine. However, the lack of a cohesive master data architecture hampers the efficient utilization of this data for informed decision-making and improved patient outcomes. This study introduces a novel master data architecture tailored for the healthcare industry, emphasizing interoperability, scalability, and data governance. By leveraging cutting-edge technologies such as AI, blockchain, and cloud computing, the proposed architecture enables seamless data integration across diverse systems and stakeholders. Real-world implementation scenarios demonstrate its ability to streamline operations, enhance data quality, and foster a patient-centric approach to healthcare delivery. This research underscores the transformative potential of advanced data management frameworks in driving efficiency, compliance, and innovation within the digital healthcare landscape.


Full Text:

PDF

References


Smith, J. (2019). Mastering Data Architecture: A Practical Guide. Acme Publications.

Johnson, M. L. (2000). Data Governance Best Practices: A Comprehensive Approach. Wiley.

Brown, A. R. (2009). Modern Data Integration Strategies for Big Data. Springer.

White, S. P., & Lee, T. R. (2001). Real-World Implementations of Master Data Architecture. Data Science Journal, 15(3), 72-88.

Garcia, L. (2000). The Role of Artificial Intelligence in Data Quality Assurance. Journal of Data Management, 25(2), 45-61.

Davis, R. H. (2018). Master Data Governance: Principles and Practices. Oxford University Press.

Harris, P. (2019). Cloud-Based Data Storage Solutions for the Modern Enterprise. CloudTech, 4(2), 28-42.

Martin, K. (2019). Data Privacy and Compliance in the Digital Age. Data Security Journal, 12(1), 55-67.

Thompson, E. (2019). Data Integration Platforms for Big Data: A Comparative Analysis. Big Data Review, 8(3), 115-132.

Lewis, G. R., & Turner, S. A. (2019). Data Stewardship and Its Role in Data Governance. Journal of Information Management, 14(4), 72-86.

Baker, L. (2018). Advanced Data Quality Techniques: A Machine Learning Approach. Machine Learning Journal, 33(5), 212-227.

Robinson, D. (2019). Data Warehousing for Business Intelligence: Concepts and Implementation. Prentice Hall.

Mettikolla, P., & Umasankar, K. (2019). Epidemiological analysis of extended-spectrum β-lactamase-producing uropathogenic bacteria. International Journal of Novel Trends in Pharmaceutical Sciences, 9(4), 75-82.


Refbacks

  • There are currently no refbacks.