Advancing Medical Reporting with Concordance Analysis POC

Background:

In the medical field, the accuracy of diagnostic reports is paramount. Our project aimed to implement a Proof of Concept (POC) to assess the concordance between radiology and pathology reports, which is critical for accurate diagnosis and treatment planning.

Challenge:

The challenge was to extract and compare data from structured radiology and pathology reports accurately. The goal was to develop a system that could assign a concordance score to the results, which would then be included in a new, integrated report.

Solution:

We developed a POC using the following technology stack:

• Backend Development: .NET 5.0 for server-side logic
• Frontend Development: HTML, JavaScript, CSS, and Angular for the user interface
• Database: MySQL for data storage
• Cloud Services: AWS for hosting and scalability
• Healthcare Interoperability: FHIR for ensuring compliance with healthcare data standards

Implementation:

The system extracts data from existing structured reports and uses a set of predefined rules to compare the findings. It then calculates a concordance score reflecting the degree of agreement between the radiology and pathology reports.

Results:

The POC demonstrated:

• Improved Report Accuracy: The concordance score provided a quantifiable measure of report reliability.
• Enhanced Clinical Decision-Making: Clinicians could make better-informed decisions with integrated reports that highlighted concordance.
• Streamlined Reporting Process: The automated comparison reduced manual review time and potential for human error.

Conclusion:

The concordance analysis POC marks a significant step forward in medical reporting. By leveraging a robust technology stack and the FHIR standard, we have created a tool that not only improves the accuracy of medical reports but also supports clinicians in delivering high-quality patient care.