Background

In emergency care, healthcare workers face significant challenges due to the fragmented and varied formats of patient data. Specifically, physicians struggle with the limited access to the complex, interwoven relationships between prior doctors' notes, current vitals, and chest X-ray images. These data integration issues often result in extended wait times for diagnosis, increased healthcare costs, and delays in treatment, all of which collectively heighten patient risks.

Untapped Potential of EHR Systems

Despite the detailed patient profiles created by Electronic Health Record (EHR) systems, which include diagnostic results, radiology studies, and clinical notes, the full potential of these records for personalized patient care remains largely untapped. Current AI diagnostic tools are unable to fully leverage the diverse data types available, leading to significant gaps in the ability of healthcare providers to analyze and understand the complexities of healthcare data. This oversight impedes the advancement of personalized medicine and comprehensive patient care.