Unified data integration and record identification framework for diverse data sources in healthcare demographics

Abstract

Challenges of bridging data from different sources with diverse data formats are faced by organizations in the modern data management environment. Problems with disparate data sources leading to different formats and inconsistencies mean it can be challenging to get the right matching of data records, especially when information errors such as typos are present. The current lack of a standard pattern for data integration and record identification presents a major problem in ensuring the accurate identification of individual records across disparate sources. The variations in data formats and the abundance of errors, such as typographical mistakes in names, dates of birth, and gender, add to the complexity of this problem. Organizations face the challenge of ensuring the correctness and consistency of data across multiple datasets without a formalized methodology.