%0 Journal Article %1 7d1bbeed3c7a44d5890c1fc53bee0947 %A Hoffmann, Katja %A Peng, Yuan %A Schlosser, Tobias %A Stolze, Gabriel %A Langner, Holger %A Susky, Marcel %A Meyer, Trixy %A Ritter, Marc %A Kowerko, Danny %A Kakkassery, Vinodh %A Wolfien, Markus %A Sedlmayr, Martin %D 2024 %I IOS Press, Amsterdam u. a. %J Studies in health technology and informatics %K topic_lifescience zno %P 139--145 %R 10.3233/SHTI240849 %T Towards Standardizing Ophthalmic Data for Seamless Interoperability in Eye Care %V 317 %X INTRODUCTION: Seamless interoperability of ophthalmic clinical data is beneficial for improving patient care and advancing research through the integration of data from various sources. Such consolidation increases the amount of data available, leading to more robust statistical analyses, and improving the accuracy and reliability of artificial intelligence models. However, the lack of consistent, harmonized data formats and meanings (syntactic and semantic interoperability) poses a significant challenge in sharing ophthalmic data.METHODS: The Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR), a standard for the exchange of healthcare data, emerges as a promising solution. To facilitate cross-site data exchange in research, the German Medical Informatics Initiative (MII) has developed a core data set (CDS) based on FHIR.RESULTS: This work investigates the suitability of the MII CDS specifications for exchanging ophthalmic clinical data necessary to train and validate a specific machine learning model designed for predicting visual acuity. In interdisciplinary collaborations, we identified and categorized the required ophthalmic clinical data and explored the possibility of its mapping to FHIR using the MII CDS specifications.DISCUSSION: We found that the current FHIR MII CDS specifications do not completely accommodate the ophthalmic clinical data we investigated, indicating that the creation of an extension module is essential.

@article{7d1bbeed3c7a44d5890c1fc53bee0947, abstract = {INTRODUCTION: Seamless interoperability of ophthalmic clinical data is beneficial for improving patient care and advancing research through the integration of data from various sources. Such consolidation increases the amount of data available, leading to more robust statistical analyses, and improving the accuracy and reliability of artificial intelligence models. However, the lack of consistent, harmonized data formats and meanings (syntactic and semantic interoperability) poses a significant challenge in sharing ophthalmic data.METHODS: The Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR), a standard for the exchange of healthcare data, emerges as a promising solution. To facilitate cross-site data exchange in research, the German Medical Informatics Initiative (MII) has developed a core data set (CDS) based on FHIR.RESULTS: This work investigates the suitability of the MII CDS specifications for exchanging ophthalmic clinical data necessary to train and validate a specific machine learning model designed for predicting visual acuity. In interdisciplinary collaborations, we identified and categorized the required ophthalmic clinical data and explored the possibility of its mapping to FHIR using the MII CDS specifications.DISCUSSION: We found that the current FHIR MII CDS specifications do not completely accommodate the ophthalmic clinical data we investigated, indicating that the creation of an extension module is essential.}, added-at = {2024-11-28T16:27:18.000+0100}, author = {Hoffmann, Katja and Peng, Yuan and Schlosser, Tobias and Stolze, Gabriel and Langner, Holger and Susky, Marcel and Meyer, Trixy and Ritter, Marc and Kowerko, Danny and Kakkassery, Vinodh and Wolfien, Markus and Sedlmayr, Martin}, biburl = {https://puma.scadsai.uni-leipzig.de/bibtex/22276d43fcbed127592912b6d95a86f60/scadsfct}, day = 30, doi = {10.3233/SHTI240849}, interhash = {d2fcd6b22b887c7ceb0dc28e683a2344}, intrahash = {2276d43fcbed127592912b6d95a86f60}, issn = {0926-9630}, journal = {Studies in health technology and informatics}, keywords = {topic_lifescience zno}, language = {English}, month = aug, note = {Publisher Copyright: {\textcopyright} 2024 The Authors.}, pages = {139--145}, publisher = {IOS Press, Amsterdam [u. a.]}, timestamp = {2025-03-12T15:06:48.000+0100}, title = {Towards Standardizing Ophthalmic Data for Seamless Interoperability in Eye Care}, volume = 317, year = 2024 }