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In vivo Structural Assessments of Ocular Disease in Rodent Models using Optical Coherence Tomography

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Towards Standardizing Ophthalmic Data for Seamless Interoperability in Eye Care.

Katja Hoffmann¹, Yuan Peng¹, Tobias Schlosser²

¹Institute for Medical Informatics and Biometry, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.

Studies in Health Technology and Informatics

|September 5, 2024

Summary

Sharing ophthalmic clinical data for AI requires standardized formats. Current Health Level Seven (HL7) Fast Healthcare Interoperability Resources (FHIR) specifications, using the German Medical Informatics Initiative (MII) core data set (CDS), need extensions for comprehensive ophthalmic data exchange.

Keywords:

Data Exchange Data Standardization HL7 FHIR Interoperability Ophthalmology

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Area of Science:

Ophthalmic informatics
Health data standardization
Machine learning in ophthalmology

Background:

Interoperability of ophthalmic clinical data is crucial for enhancing patient care and research.
Lack of standardized data formats hinders data sharing and the development of AI models in ophthalmology.
Health Level Seven (HL7) Fast Healthcare Interoperability Resources (FHIR) offers a potential solution for healthcare data exchange.

Purpose of the Study:

To assess the suitability of German Medical Informatics Initiative (MII) core data set (CDS) specifications based on FHIR for ophthalmic clinical data exchange.
To identify and categorize ophthalmic data required for training and validating a visual acuity prediction machine learning model.
To explore mapping ophthalmic data to FHIR using MII CDS specifications.

Main Methods:

Interdisciplinary collaboration to identify and categorize essential ophthalmic clinical data.
Investigation of the German Medical Informatics Initiative (MII) core data set (CDS) specifications for FHIR-based data exchange.
Exploration of data mapping possibilities within the FHIR framework.

Main Results:

The current FHIR MII CDS specifications are insufficient for completely accommodating the investigated ophthalmic clinical data.
An extension module is necessary to fully support the exchange of ophthalmic data for AI model development.
Gaps were identified in the MII CDS for specific ophthalmic data elements.

Conclusions:

The existing FHIR MII CDS requires augmentation to effectively support ophthalmic data interoperability.
Development of an extension module is essential for seamless integration of ophthalmic data into FHIR-based systems.
Standardization efforts must specifically address the unique requirements of ophthalmic clinical data for advancing AI in eye care.