Master Data Management System for Healthcare
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Solution Overview
Problem
Healthcare organizations face challenges in managing inconsistent and duplicate master data across multiple databases, leading to inefficiencies and operational problems due to the complexity of data reconciliation, especially after mergers and acquisitions, which affects customer satisfaction, operational efficiency, and regulatory compliance.
Innovation Solution
A computer-assisted method for master data management that includes receiving configuration information to define entity models, processing data from multiple sources, translating and synchronizing data using mapping, searching, and matching logic, and incorporating an ETL layer to manage and consolidate data across disparate databases, ensuring data consistency and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is stored in multiple customer databases by different organizations, then data availability and system independence are improved, but data consistency and quality deteriorate due to inconsistencies and duplicates
Solution Approach 1:
The patent introduces a master data management system as an intermediary layer between multiple customer databases. This system receives data from various source databases, processes and reconciles it, then stores the standardized master data in a central repository. The intermediary resolves conflicts and inconsistencies before data is stored, ensuring consistency across all databases while maintaining the independence of source systems.
Solution Approach 2:
The master data management system serves multiple functions simultaneously: it acts as a data receiver from various sources, a data reconciler that handles conflicts, a data standardizer that applies consistent formatting, and a data distributor to multiple databases. This multi-functional approach ensures data consistency across the entire organization while maintaining system independence.
2Measurement precision
If manual data reconciliation is performed across multiple databases, then data accuracy is improved, but processing time and operational complexity increase
Solution Approach 1:
The master data management system performs self-service data reconciliation by automatically comparing records across multiple databases, identifying duplicates and conflicts, and resolving them according to predefined rules. The system autonomously processes data without requiring manual intervention, thereby maintaining high data accuracy while significantly reducing processing time and operational complexity.
Solution Approach 2:
The patent replaces manual mechanical data reconciliation processes with automated computer-based processing. The system uses algorithms and software logic to automatically compare, match, and reconcile data records, substituting human manual operations with automated mechanisms that are both faster and more consistent, thereby reducing processing time while maintaining accuracy.
3Manufacturing precision
If comprehensive data processing and reconciliation is implemented, then data quality is improved, but system complexity and implementation difficulty increase
Solution Approach 1:
The master data management system segments the data processing function into distinct modular components: data reception modules for each source database, data processing modules for reconciliation and standardization, and data distribution modules to various target databases. This segmentation allows the complex data quality improvement process to be broken down into manageable, independent units that can be implemented and maintained more easily.
Solution Approach 2:
By introducing the master data management system as an intermediary layer, the patent simplifies the overall system architecture. Rather than requiring direct complex interactions between multiple databases, the intermediary handles all processing and reconciliation logic centrally, reducing the complexity of point-to-point connections and making the system easier to implement and maintain.
4Stability of the object's composition
If data synchronization across multiple databases is performed frequently, then data consistency is improved, but system performance and processing speed deteriorate
Solution Approach 1:
The master data management system performs preliminary data processing and reconciliation actions before data is stored in the master data repository. By pre-processing and validating data in advance, the system ensures that when data is subsequently synchronized to multiple databases, the process is faster and requires less processing time, as the heavy lifting has already been done.
Solution Approach 2:
The system implements self-service synchronization by automatically detecting changes in master data and propagating them to relevant source databases only when necessary. This on-demand approach maintains data consistency without requiring continuous frequent synchronization cycles, thereby improving processing speed while maintaining stability.
Data Source
AI summary
Some implementations may provide a computer-assisted method for master data management, the method including: receiving configuration information defining a model of entities, each entity encoding attributes of a prescriber of one or more healthcare products; receiving specification information defining mapping logic, searching logic, and matching logic, and merging logic for processing base entities and related entities of the model; receiving data from more than one source customer databases, the customer database including data encoding prescribers of healthcare products and being maintained by more than one organizations; translating the received data into staging data according to the mapping logic in the received specification information; generating master data by processing the staging data according to the searching logic, matching logic, and merging logic in the received specification information; and synchronizing at least a portion of the master data to at least one of the source customer databases.