Integrated Data Architecture for Genomic Pedigree Analysis in Rare Disease Assessment: A Systems Approach

Abstract

Genomic pedigree information used in healthcare systems has the potential to change the diagnosis and treatment of rare diseases. Existing electronic health records systems have significant issues with genetic data capacity, especially intertwined family relationships, necessary to conduct a complete evaluation. This framework tackles the underlying informatics issues by providing standardized data models, advanced inheritance pattern modeling, and interoperable exchange protocols. Healthcare organizations can represent multi-generational genetic information more appropriately by digitizing the traditional documentation of pedigrees and developing semantically rich data models. Artificial intelligence augments such possibilities with pattern recognition, predictive analytics, and natural language processing, and raises significant ethical concerns around privacy and algorithmic fairness. The inherent implementation of genetic information into clinical practices under the influence of a proper decision support system and the employment of secure exchange mechanisms is showing considerable enhancements in the efficiency and accuracy of diagnosis processes. This integrated system connects a broad spectrum of data streams, which allows getting closer to true molecular insights into uncommon genetic illnesses and reduces the duration required to make a diagnosis and improve patient outcomes.

Keywords: Genomic Data Integration, Pedigree Analysis, Electronic Health Records, Clinical Decision Support, Rare Disease Diagnosis