Patient Data Unification and Standardization System

A healthcare provider with an expanding network faces significant issues with siloed, inconsistent, and duplicate patient data originating from diverse sources such as hospitals, outpatient clinics, insurance companies, and EMR systems. This fragmentation hampers effective patient care, delays treatments, and compromises data accuracy, leading to potential malpractice risks.

A large healthcare organization with multiple medical facilities and data sources seeking to improve patient data accuracy and accessibility.

• Develop a comprehensive system to centralize and unify patient data from multiple sources.
• Enhance data quality through cleansing and standardization to ensure consistency across the organization.
• Implement record linkage and identification algorithms to create accurate golden patient records, reducing duplicates and inaccuracies.
• Improve operational efficiency by enabling quick access to complete patient histories for healthcare practitioners.
• Support cross-organizational healthcare reporting and analytics to inform better decision-making and patient outcomes.

• Data Collection Module: Ingests patient data from various external and internal sources such as hospital databases, EMR systems, claims, and payor data.
• Data Cleansing and Standardization: Utilizes NLP and rule-based mapping to ensure consistent data entry, formatting, and terminology.
• Record Linkage and Deduplication: Uses algorithms and manual validation to identify and merge duplicate records, creating reliable patient profiles.
• Golden Record Management: Stores authoritative, merged patient records with secure access controls for operational and analytical use.
• Data Validation Tools: Enables data stewards to manually review, map, and unmap records to maintain data integrity.

• Hospital Information Systems (HIS) databases
• Electronic Medical Record (EMR) systems
• Insurance claims platforms
• Payor data feeds

• Scalability to support increasing data volume from multiple sources
• High data processing throughput to ensure real-time or near-real-time updates
• Compliance with healthcare data privacy regulations (e.g., HIPAA)
• Robust security measures for sensitive patient information
• Availability and fault-tolerance to ensure continuous system operation

The implementation of this patient data unification solution is expected to significantly improve data accuracy by eliminating duplicates and incorrect information, thereby enhancing patient safety and care quality. Operational efficiency will be increased as healthcare practitioners gain access to complete and reliable patient histories, enabling faster decision-making. Moreover, improved data quality and unified reporting will support organizational analytics and strategic planning, reducing data management overhead and enabling better health outcomes.