Lea Holtrup, Julian Varghese, Alexander K Schuster, Broder Poschkamp, Christopher Hampf, Dagmar Waltemath, Leonie Wahle, Myriam Lipprandt, David A Merle, Philipp Berens, Oliver Kohlbacher, Vinodh Kakkassery, Martin Bartos, Focke Ziemssen, Thomas Wendt, Katja Hoffmann, Nicole Eter
{"title":"[EyeMatics--利用可互操作的医疗信息学对真实世界数据进行多中心数据评估]。","authors":"Lea Holtrup, Julian Varghese, Alexander K Schuster, Broder Poschkamp, Christopher Hampf, Dagmar Waltemath, Leonie Wahle, Myriam Lipprandt, David A Merle, Philipp Berens, Oliver Kohlbacher, Vinodh Kakkassery, Martin Bartos, Focke Ziemssen, Thomas Wendt, Katja Hoffmann, Nicole Eter","doi":"10.1007/s00347-024-02135-0","DOIUrl":null,"url":null,"abstract":"<p><p>The evaluation of real-world data (RWD) enables insights to be gained from a wide range of patient data collected in routine clinical practice. In addition, multicenter analyses represent a broad and representative patient population and have the potential to capture the actual treatment situation. As a basis for this, the definition of datasets and an infrastructure for data exchange is necessary. Data integration centers (DIC) have already been established at (university) hospitals throughout Germany in order to extract RWD for scientific analyses from the various source systems and integrate them into research-compatible data infrastructures. The project described here aims to demonstrate the added value of this data integration using a case of application in ophthalmology, defining a core dataset as an ophthalmology extension module and establishing a cross-site data exchange infrastructure. As a first step, the treatment success of eye diseases treated with intravitreal injection (IVI) should be improved. To achieve this goal a dashboard for clinical data is provided that clearly visualizes the merged data. Furthermore, algorithms will be developed to identify new imaging biomarkers that can be used for treatment monitoring and predict treatment outcomes.</p>","PeriodicalId":72808,"journal":{"name":"Die Ophthalmologie","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"[EyeMatics-Multicenter data evaluation of real-world data with interoperable medical informatics].\",\"authors\":\"Lea Holtrup, Julian Varghese, Alexander K Schuster, Broder Poschkamp, Christopher Hampf, Dagmar Waltemath, Leonie Wahle, Myriam Lipprandt, David A Merle, Philipp Berens, Oliver Kohlbacher, Vinodh Kakkassery, Martin Bartos, Focke Ziemssen, Thomas Wendt, Katja Hoffmann, Nicole Eter\",\"doi\":\"10.1007/s00347-024-02135-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The evaluation of real-world data (RWD) enables insights to be gained from a wide range of patient data collected in routine clinical practice. In addition, multicenter analyses represent a broad and representative patient population and have the potential to capture the actual treatment situation. As a basis for this, the definition of datasets and an infrastructure for data exchange is necessary. Data integration centers (DIC) have already been established at (university) hospitals throughout Germany in order to extract RWD for scientific analyses from the various source systems and integrate them into research-compatible data infrastructures. The project described here aims to demonstrate the added value of this data integration using a case of application in ophthalmology, defining a core dataset as an ophthalmology extension module and establishing a cross-site data exchange infrastructure. As a first step, the treatment success of eye diseases treated with intravitreal injection (IVI) should be improved. To achieve this goal a dashboard for clinical data is provided that clearly visualizes the merged data. Furthermore, algorithms will be developed to identify new imaging biomarkers that can be used for treatment monitoring and predict treatment outcomes.</p>\",\"PeriodicalId\":72808,\"journal\":{\"name\":\"Die Ophthalmologie\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-11-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Die Ophthalmologie\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s00347-024-02135-0\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Die Ophthalmologie","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s00347-024-02135-0","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
[EyeMatics-Multicenter data evaluation of real-world data with interoperable medical informatics].
The evaluation of real-world data (RWD) enables insights to be gained from a wide range of patient data collected in routine clinical practice. In addition, multicenter analyses represent a broad and representative patient population and have the potential to capture the actual treatment situation. As a basis for this, the definition of datasets and an infrastructure for data exchange is necessary. Data integration centers (DIC) have already been established at (university) hospitals throughout Germany in order to extract RWD for scientific analyses from the various source systems and integrate them into research-compatible data infrastructures. The project described here aims to demonstrate the added value of this data integration using a case of application in ophthalmology, defining a core dataset as an ophthalmology extension module and establishing a cross-site data exchange infrastructure. As a first step, the treatment success of eye diseases treated with intravitreal injection (IVI) should be improved. To achieve this goal a dashboard for clinical data is provided that clearly visualizes the merged data. Furthermore, algorithms will be developed to identify new imaging biomarkers that can be used for treatment monitoring and predict treatment outcomes.