EHRSummarizer: A Privacy-Aware, FHIR-Native Architecture for Structured Clinical Summarization of Electronic Health Records

TL;DR

EHRSummarizer is a privacy-aware, FHIR-native system that creates structured clinical summaries from electronic health records to assist clinicians in chart review, emphasizing data security and configurability.

Contribution

The paper introduces EHRSummarizer, a novel architecture for secure, flexible, and structured clinical summarization directly integrated with FHIR standards.

Findings

Prototype demonstrates end-to-end functionality.

Configurable for data minimization and local deployment.

Focuses on evidence-based, safe summarization without diagnostic suggestions.

Abstract

Clinicians routinely navigate fragmented electronic health record (EHR) interfaces to assemble a coherent picture of a patient's problems, medications, recent encounters, and longitudinal trends. This work describes EHRSummarizer, a privacy-aware, FHIR-native reference architecture that retrieves a targeted set of high-yield FHIR R4 resources, normalizes them into a consistent clinical context package, and produces structured summaries intended to support structured chart review. The system can be configured for data minimization, stateless processing, and flexible deployment, including local inference within an organization's trust boundary. To mitigate the risk of unsupported or unsafe behavior, the summarization stage is constrained to evidence present in the retrieved context package, is intended to indicate missing or unavailable domains where feasible, and avoids diagnostic or treatment recommendations. Prototype demonstrations on synthetic and test FHIR environments illustrate end-to-end behavior and output formats; however, this manuscript does not report clinical outcomes or controlled workflow studies. We outline an evaluation plan centered on faithfulness, omission risk, temporal correctness, usability, and operational monitoring to guide future institutional assessments.