Modernizing U.S. Healthcare Financial Systems: A Unified HIGLAS Data Lakehouse for National Efficiency and Accountability

The modernization of healthcare financial management systems represents a critical transformation in addressing escalating costs and administrative inefficiencies within the United States healthcare sector. The HealthCare Integrated General Ledger Accounting System (HIGLAS) emerges as a pivotal solution through implementation of unified data lakehouse architecture that consolidates fragmented financial platforms into cohesive, high-performance systems. Traditional healthcare financial infrastructures demonstrate significant limitations through siloed data management, delayed analytics capabilities, and complex regulatory compliance requirements that impede operational effectiveness and increase administrative burden. The proposed lakehouse architecture combines scalability advantages of data lakes with performance characteristics of traditional data warehouses, enabling comprehensive integration of financial transactions, clinical information, and operational metrics within secure, compliant environments. Implementation demonstrates substantial improvements in operational efficiency through automated data integration processes, real-time analytics capabilities, and enhanced fraud detection mechanisms that significantly reduce manual reconciliation requirements while improving accuracy and transparency. The system addresses critical challenges including data fragmentation across multiple platforms, real-time processing limitations, and evolving regulatory compliance demands through cloud-native technologies that support elastic scaling and automated quality monitoring. Enhanced fraud detection capabilities leverage machine learning algorithms and cross-system correlation to identify sophisticated schemes while comprehensive audit trails support regulatory compliance and forensic investigations. The transformation establishes foundations for industry-wide adoption of similar architectures, driving standardization efforts and collaborative initiatives that benefit the entire healthcare ecosystem through improved interoperability and reduced integration costs.

Authors

Institutions

Publication Details

Journal
International Journal of Computing and Engineering
Published
2025-07-18
DOI
https://doi.org/10.47941/ijce.2976
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Modernizing U.S. Healthcare Financial Systems: A Unified HIGLAS Data Lakehouse for National Efficiency and Accountability

Surender Kusumba
International Journal of Computing and Engineering
Big Data and Business Intelligence
article

Modernizing U.S. Healthcare Financial Systems: A Unified HIGLAS Data Lakehouse for National Efficiency and Accountability

Surender Kusumba
article en

Abstract

The modernization of healthcare financial management systems represents a critical transformation in addressing escalating costs and administrative inefficiencies within the United States healthcare sector. The HealthCare Integrated General Ledger Accounting System (HIGLAS) emerges as a pivotal solution through implementation of unified data lakehouse architecture that consolidates fragmented financial platforms into cohesive, high-performance systems. Traditional healthcare financial infrastructures demonstrate significant limitations through siloed data management, delayed analytics capabilities, and complex regulatory compliance requirements that impede operational effectiveness and increase administrative burden. The proposed lakehouse architecture combines scalability advantages of data lakes with performance characteristics of traditional data warehouses, enabling comprehensive integration of financial transactions, clinical information, and operational metrics within secure, compliant environments. Implementation demonstrates substantial improvements in operational efficiency through automated data integration processes, real-time analytics capabilities, and enhanced fraud detection mechanisms that significantly reduce manual reconciliation requirements while improving accuracy and transparency. The system addresses critical challenges including data fragmentation across multiple platforms, real-time processing limitations, and evolving regulatory compliance demands through cloud-native technologies that support elastic scaling and automated quality monitoring. Enhanced fraud detection capabilities leverage machine learning algorithms and cross-system correlation to identify sophisticated schemes while comprehensive audit trails support regulatory compliance and forensic investigations. The transformation establishes foundations for industry-wide adoption of similar architectures, driving standardization efforts and collaborative initiatives that benefit the entire healthcare ecosystem through improved interoperability and reduced integration costs.

International Journal of Computing and EngineeringVol. 7(12)
TRX Systems (United States) (US)
Openalex Percentile: Top 66%
Big Data and Business Intelligence
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.