[et_pb_section fb_built=\u201e1\u201c _builder_version=\u201e4.16\u201c custom_padding=\u201e0px||0px||true\u201c da_disable_devices=\u201eoff|off|off\u201c locked=\u201eoff\u201c global_colors_info=\u201c{}\u201c da_is_popup=\u201eoff\u201c da_exit_intent=\u201eoff\u201c da_has_close=\u201eon\u201c da_alt_close=\u201eoff\u201c da_dark_close=\u201eoff\u201c da_not_modal=\u201eon\u201c da_is_singular=\u201eoff\u201c da_with_loader=\u201eoff\u201c da_has_shadow=\u201eon\u201c][et_pb_row _builder_version=\u201e4.18.0\u201c custom_padding=\u201e0px||||false|false\u201c global_colors_info=\u201c{}\u201c][et_pb_column type=\u201e4_4\u201c _builder_version=\u201e4.16\u201c custom_padding=\u201c|||\u201c global_colors_info=\u201c{}\u201c custom_padding__hover=\u201c|||\u201c][et_pb_post_title author=\u201eoff\u201c date=\u201eoff\u201c categories=\u201eoff\u201c comments=\u201eoff\u201c _builder_version=\u201e4.27.4\u201c _module_preset=\u201edefault\u201c title_font=\u201c|800|||||||\u201c global_colors_info=\u201c{}\u201c][\/et_pb_post_title][et_pb_text _builder_version=\u201e4.27.4\u201c header_font=\u201c|700|||||||\u201c header_4_letter_spacing=\u201e12px\u201c module_alignment=\u201ecenter\u201c saved_tabs=\u201eall\u201c locked=\u201eoff\u201c global_colors_info=\u201c{}\u201c]<\/p>\n
Together with the Fraun\u00adhofer Institute and the Berlin Institute for Health Research at Charit\u00e9, AI pioneer Insiders is deve\u00adlo\u00adping a solution for struc\u00adtu\u00adring medical data in the \u201cFHIR Starter\u201d project.<\/strong><\/p>\n [\/et_pb_text][et_pb_text _builder_version=\u201e4.27.4\u201c _module_preset=\u201edefault\u201c header_font=\u201c|700|||||||\u201c header_4_letter_spacing=\u201e12px\u201c module_alignment=\u201ecenter\u201c global_colors_info=\u201c{}\u201c]<\/p>\n Insiders is par\u00adti\u00adci\u00adpa\u00adting as a key tech\u00adno\u00adlogy partner in the FHIR Starter research project. The project is being led by the Fraun\u00adhofer Institute for Expe\u00adri\u00admental Software Engi\u00adnee\u00adring IESE and imple\u00admented in col\u00adla\u00adbo\u00adra\u00adtion with the Berlin Institute for Health Research at Charit\u00e9.<\/p>\n <\/p>\n Until now, medical infor\u00adma\u00adtion has often been exchanged via tra\u00addi\u00adtional doctor\u2019s letters in PDF format. The manual transfer of relevant data into practice manage\u00adment systems (PMS) or hospital infor\u00adma\u00adtion systems (HIS) is time-consuming and prone to errors. The aim of the \u201cFHIR-Starter\u201d project is to develop an inno\u00adva\u00adtive software service that uses arti\u00adfi\u00adcial <\/p>\n Key requi\u00adre\u00adments for the solution are to guarantee the quality and security of the struc\u00adtured data and to ensure GDPR-compliant pro\u00adces\u00adsing of sensitive medical data.<\/p>\n <\/p>\n FHIR-Starter is funded by the Federal Ministry for Economic Affairs and Energy with \u20ac1.64 million as part of the inno\u00adva\u00adtion com\u00adpe\u00adti\u00adtion \u201cGene\u00adra\u00adtive AI for SMEs.\u201d<\/p>\n <\/p>\n <\/p>\n <\/p>\n <\/p>\n As an expert in AI-supported document pro\u00adces\u00adsing, Insiders is par\u00adti\u00adcu\u00adlarly involved in the deve\u00adlo\u00adp\u00adment of the large language model (LLM), which, as a core component of the software, auto\u00adma\u00adti\u00adcally extracts relevant infor\u00adma\u00adtion from medical documents such as doctor\u2019s letters. This struc\u00adtured infor\u00adma\u00adtion is then converted into the stan\u00addar\u00addized FHIR format, <\/p>\n \u201cWe are lever\u00adaging our many years of expertise in AI-supported data extra\u00adc\u00adtion to automate the pro\u00adces\u00adsing of medical documents,\u201d explains Christian Sch\u00f6n, Product Owner OvAition at Insiders. \u201eBy deve\u00adlo\u00adping a powerful LLM, we are enabling medical data to be effi\u00adci\u00adently struc\u00adtured and made usable. The auto\u00adma\u00adtion of admi\u00adnis\u00adtra\u00adtive tasks reduces the workload on <\/p>\n In addition to deve\u00adlo\u00adping the LLM, Insiders is also involved in other key project tasks, including iden\u00adti\u00adfying relevant data, deve\u00adlo\u00adping a prototype, and publi\u00adshing sci\u00aden\u00adtific results at spe\u00adcia\u00adlist con\u00adfe\u00adrences.<\/p>\n <\/p>\n <\/p>\n <\/p>\n <\/p>\n The struc\u00adtured pro\u00adces\u00adsing of medical data opens up a wide range of pos\u00adsi\u00adbi\u00adli\u00adties: Hospitals and medical practices can optimize their processes in findings manage\u00adment and patient docu\u00admen\u00adta\u00adtion, medical research insti\u00adtutes gain easier access to relevant infor\u00adma\u00adtion, and patients benefit from more efficient and better care.<\/p>\n <\/p>\n Within the three-year project, which started in February 2025, Insiders is making an important con\u00adtri\u00adbu\u00adtion to the digi\u00adtiza\u00adtion of health\u00adcare in Germany.<\/p>\n [\/et_pb_text][et_pb_button button_url=\u201c@ET-DC@eyJkeW5hbWljIjp0cnVlLCJjb250ZW50IjoicG9zdF9saW5rX3VybF9wYWdlIiwic2V0dGluZ3MiOnsicG9zdF9pZCI6IjgxNjY2In19@\u201c url_new_window=\u201eon\u201c button_text=\u201eMore about Insiders AI\u201c button_alignment=\u201eleft\u201c _builder_version=\u201e4.27.4\u201c _dynamic_attributes=\u201ebutton_url\u201c _module_preset=\u201edefault\u201c custom_button=\u201eon\u201c button_text_color=\u201egcid-a1ce49c7-18bb-4621\u20138275-487db4ef4ea2\u201c locked=\u201eoff\u201c global_colors_info=\u201c{%22gcid-e57f936a-e1ef-478a-a91c-6dc2f7bf0652%22:%91%22button_text_color__hover%22%93,%22gcid-a1ce49c7-18bb-4621\u20138275-487db4ef4ea2%22:%91%22button_text_color%22%93}\u201c button_text_color__hover_enabled=\u201eon|hover\u201c button_text_color__hover=\u201e#000000\u201c button_bg_color__hover_enabled=\u201eon|hover\u201c][\/et_pb_button][et_pb_button button_url=\u201ehttps:\/\/www.iese.fraunhofer.de\/de\/referenz\/fhirstarter.html\u201c url_new_window=\u201eon\u201c button_text=\u201eMore about the FHIR Starter project\u201c button_alignment=\u201eleft\u201c disabled_on=\u201eoff|off|off\u201c _builder_version=\u201e4.27.4\u201c _module_preset=\u201edefault\u201c custom_button=\u201eon\u201c button_text_color=\u201egcid-a1ce49c7-18bb-4621\u20138275-487db4ef4ea2\u201c locked=\u201eoff\u201c global_colors_info=\u201c{%22gcid-e57f936a-e1ef-478a-a91c-6dc2f7bf0652%22:%91%22button_text_color__hover%22%93,%22gcid-a1ce49c7-18bb-4621\u20138275-487db4ef4ea2%22:%91%22button_text_color%22%93}\u201c button_text_color__hover_enabled=\u201eon|hover\u201c button_text_color__hover=\u201e#000000\u201c button_bg_color__hover_enabled=\u201eon|hover\u201c][\/et_pb_button][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":" Together with the Fraun\u00adhofer Institute and the Berlin Institute for Health Research at Charit\u00e9, AI pioneer Insiders is deve\u00adlo\u00adping a solution for struc\u00adtu\u00adring medical data in the \u201cFHIR Starter\u201d project.Insiders is par\u00adti\u00adci\u00adpa\u00adting as a key tech\u00adno\u00adlogy partner in the FHIR Starter research project. The project is being led by the Fraun\u00adhofer Institute for Expe\u00adri\u00admental Software [\u2026]<\/p>\n","protected":false},"author":20,"featured_media":82837,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"","wp_typography_post_enhancements_disabled":false,"_mbp_gutenberg_autopost":false,"footnotes":""},"categories":[677,2,109],"tags":[],"class_list":["post-88273","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-artificial-intelligence","category-blog-en","category-featured"],"acf":[],"_links":{"self":[{"href":"https:\/\/insiders.next-kmu.de\/en\/wp-json\/wp\/v2\/posts\/88273","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/insiders.next-kmu.de\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/insiders.next-kmu.de\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/insiders.next-kmu.de\/en\/wp-json\/wp\/v2\/users\/20"}],"replies":[{"embeddable":true,"href":"https:\/\/insiders.next-kmu.de\/en\/wp-json\/wp\/v2\/comments?post=88273"}],"version-history":[{"count":0,"href":"https:\/\/insiders.next-kmu.de\/en\/wp-json\/wp\/v2\/posts\/88273\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/insiders.next-kmu.de\/en\/wp-json\/wp\/v2\/media\/82837"}],"wp:attachment":[{"href":"https:\/\/insiders.next-kmu.de\/en\/wp-json\/wp\/v2\/media?parent=88273"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/insiders.next-kmu.de\/en\/wp-json\/wp\/v2\/categories?post=88273"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/insiders.next-kmu.de\/en\/wp-json\/wp\/v2\/tags?post=88273"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
By using large language models (LLMs) and natural language pro\u00adces\u00adsing (NLP), unstruc\u00adtured full-text documents are to be analyzed and converted into stan\u00addar\u00addized data struc\u00adtures. This enables seamless inte\u00adgra\u00adtion into existing IT systems in hospitals and practices, repre\u00adsen\u00adting a decisive step toward digi\u00adtiza\u00adtion and auto\u00adma\u00adtion in the health\u00adcare sector.<\/p>\nInsiders takes on deve\u00adlo\u00adp\u00adment of large language model<\/h3>\n
which was developed spe\u00adci\u00adfi\u00adcally for the exchange of health data and gives the project its name.<\/p>\n
medical pro\u00adfes\u00adsio\u00adnals and minimizes errors. This allows doctors to con\u00adcen\u00adtrate on their core task again \u2013 providing the best possible care for their patients.\u201c<\/p>\nVersatile appli\u00adca\u00adtions for a digital future<\/h3>\n