Bridging Data Silos in Oncology with Modular Software for Federated Analysis on Fast Healthcare Interoperability Resources: Multisite Implementation Study
BackgroundReal-world data (RWD) from sources like administrative claims, electronic health records, and cancer registries offer insights into patient populations beyond the tightly regulated environment of randomized controlled trials. To leverage this and to advance cancer r...
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JMIR Publications
2025-04-01
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| Series: | Journal of Medical Internet Research |
| Online Access: | https://www.jmir.org/2025/1/e65681 |
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| author | Jasmin Ziegler Marcel Pascal Erpenbeck Timo Fuchs Anna Saibold Paul-Christian Volkmer Guenter Schmidt Johanna Eicher Peter Pallaoro Renata De Souza Falguera Fabio Aubele Marlien Hagedorn Ekaterina Vansovich Johannes Raffler Stephan Ringshandl Alexander Kerscher Julia Karolin Maurer Brigitte Kühnel Gerhard Schenkirsch Marvin Kampf Lorenz A Kapsner Hadieh Ghanbarian Helmut Spengler Iñaki Soto-Rey Fady Albashiti Dirk Hellwig Maximilian Ertl Georg Fette Detlef Kraska Martin Boeker Hans-Ulrich Prokosch Christian Gulden |
| author_facet | Jasmin Ziegler Marcel Pascal Erpenbeck Timo Fuchs Anna Saibold Paul-Christian Volkmer Guenter Schmidt Johanna Eicher Peter Pallaoro Renata De Souza Falguera Fabio Aubele Marlien Hagedorn Ekaterina Vansovich Johannes Raffler Stephan Ringshandl Alexander Kerscher Julia Karolin Maurer Brigitte Kühnel Gerhard Schenkirsch Marvin Kampf Lorenz A Kapsner Hadieh Ghanbarian Helmut Spengler Iñaki Soto-Rey Fady Albashiti Dirk Hellwig Maximilian Ertl Georg Fette Detlef Kraska Martin Boeker Hans-Ulrich Prokosch Christian Gulden |
| author_sort | Jasmin Ziegler |
| collection | DOAJ |
| description |
BackgroundReal-world data (RWD) from sources like administrative claims, electronic health records, and cancer registries offer insights into patient populations beyond the tightly regulated environment of randomized controlled trials. To leverage this and to advance cancer research, 6 university hospitals in Bavaria have established a joint research IT infrastructure.
ObjectiveThis study aimed to outline the design, implementation, and deployment of a modular data transformation pipeline that transforms oncological RWD into a Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) format and then into a tabular format in preparation for a federated analysis (FA) across the 6 Bavarian Cancer Research Center university hospitals.
MethodsTo harness RWD effectively, we designed a pipeline to convert the oncological basic dataset (oBDS) into HL7 FHIR format and prepare it for FA. The pipeline handles diverse IT infrastructures and systems while maintaining privacy by keeping data decentralized for analysis. To assess the functionality and validity of our implementation, we defined a cohort to address two specific medical research questions. We evaluated our findings by comparing the results of the FA with reports from the Bavarian Cancer Registry and the original data from local tumor documentation systems.
ResultsWe conducted an FA of 17,885 cancer cases from 2021/2022. Breast cancer was the most common diagnosis at 3 sites, prostate cancer ranked in the top 2 at 4 sites, and malignant melanoma was notably prevalent. Gender-specific trends showed larynx and esophagus cancers were more common in males, while breast and thyroid cancers were more frequent in females. Discrepancies between the Bavarian Cancer Registry and our data, such as higher rates of malignant melanoma (3400/63,771, 5.3% vs 1921/17,885, 10.7%) and lower representation of colorectal cancers (8100/63,771, 12.7% vs 1187/17,885, 6.6%) likely result from differences in the time periods analyzed (2019 vs 2021/2022) and the scope of data sources used. The Bavarian Cancer Registry reports approximately 3 times more cancer cases than the 6 university hospitals alone.
ConclusionsThe modular pipeline successfully transformed oncological RWD across 6 hospitals, and the federated approach preserved privacy while enabling comprehensive analysis. Future work will add support for recent oBDS versions, automate data quality checks, and integrate additional clinical data. Our findings highlight the potential of federated health data networks and lay the groundwork for future research that can leverage high-quality RWD, aiming to contribute valuable knowledge to the field of cancer research. |
| format | Article |
| id | doaj-art-31d994bf3748459587ea40fe9f14fb00 |
| institution | OA Journals |
| issn | 1438-8871 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | Journal of Medical Internet Research |
| spelling | doaj-art-31d994bf3748459587ea40fe9f14fb002025-08-20T02:26:33ZengJMIR PublicationsJournal of Medical Internet Research1438-88712025-04-0127e6568110.2196/65681Bridging Data Silos in Oncology with Modular Software for Federated Analysis on Fast Healthcare Interoperability Resources: Multisite Implementation StudyJasmin Zieglerhttps://orcid.org/0009-0005-5362-5228Marcel Pascal Erpenbeckhttps://orcid.org/0009-0007-5468-6510Timo Fuchshttps://orcid.org/0009-0002-3896-6786Anna Saiboldhttps://orcid.org/0009-0004-2088-1025Paul-Christian Volkmerhttps://orcid.org/0009-0007-0967-9696Guenter Schmidthttps://orcid.org/0009-0003-9151-3505Johanna Eicherhttps://orcid.org/0000-0003-4871-0282Peter Pallaorohttps://orcid.org/0000-0003-4808-0700Renata De Souza Falguerahttps://orcid.org/0000-0002-0475-4892Fabio Aubelehttps://orcid.org/0009-0006-9970-7058Marlien Hagedornhttps://orcid.org/0009-0002-6998-5429Ekaterina Vansovichhttps://orcid.org/0009-0003-6215-8049Johannes Rafflerhttps://orcid.org/0000-0003-2495-4020Stephan Ringshandlhttps://orcid.org/0000-0002-0544-4298Alexander Kerscherhttps://orcid.org/0000-0001-7742-570XJulia Karolin Maurerhttps://orcid.org/0009-0006-5340-2793Brigitte Kühnelhttps://orcid.org/0009-0008-1262-5290Gerhard Schenkirschhttps://orcid.org/0000-0003-0510-6069Marvin Kampfhttps://orcid.org/0000-0002-9108-0469Lorenz A Kapsnerhttps://orcid.org/0000-0003-1866-860XHadieh Ghanbarianhttps://orcid.org/0009-0009-2903-3504Helmut Spenglerhttps://orcid.org/0000-0002-1389-3755Iñaki Soto-Reyhttps://orcid.org/0000-0003-3061-5818Fady Albashitihttps://orcid.org/0000-0002-0671-152XDirk Hellwighttps://orcid.org/0000-0002-3056-0143Maximilian Ertlhttps://orcid.org/0000-0002-1290-9444Georg Fettehttps://orcid.org/0000-0002-0369-3805Detlef Kraskahttps://orcid.org/0000-0003-2174-2532Martin Boekerhttps://orcid.org/0000-0003-2972-2042Hans-Ulrich Prokoschhttps://orcid.org/0000-0001-6200-753XChristian Guldenhttps://orcid.org/0000-0003-1261-3691 BackgroundReal-world data (RWD) from sources like administrative claims, electronic health records, and cancer registries offer insights into patient populations beyond the tightly regulated environment of randomized controlled trials. To leverage this and to advance cancer research, 6 university hospitals in Bavaria have established a joint research IT infrastructure. ObjectiveThis study aimed to outline the design, implementation, and deployment of a modular data transformation pipeline that transforms oncological RWD into a Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) format and then into a tabular format in preparation for a federated analysis (FA) across the 6 Bavarian Cancer Research Center university hospitals. MethodsTo harness RWD effectively, we designed a pipeline to convert the oncological basic dataset (oBDS) into HL7 FHIR format and prepare it for FA. The pipeline handles diverse IT infrastructures and systems while maintaining privacy by keeping data decentralized for analysis. To assess the functionality and validity of our implementation, we defined a cohort to address two specific medical research questions. We evaluated our findings by comparing the results of the FA with reports from the Bavarian Cancer Registry and the original data from local tumor documentation systems. ResultsWe conducted an FA of 17,885 cancer cases from 2021/2022. Breast cancer was the most common diagnosis at 3 sites, prostate cancer ranked in the top 2 at 4 sites, and malignant melanoma was notably prevalent. Gender-specific trends showed larynx and esophagus cancers were more common in males, while breast and thyroid cancers were more frequent in females. Discrepancies between the Bavarian Cancer Registry and our data, such as higher rates of malignant melanoma (3400/63,771, 5.3% vs 1921/17,885, 10.7%) and lower representation of colorectal cancers (8100/63,771, 12.7% vs 1187/17,885, 6.6%) likely result from differences in the time periods analyzed (2019 vs 2021/2022) and the scope of data sources used. The Bavarian Cancer Registry reports approximately 3 times more cancer cases than the 6 university hospitals alone. ConclusionsThe modular pipeline successfully transformed oncological RWD across 6 hospitals, and the federated approach preserved privacy while enabling comprehensive analysis. Future work will add support for recent oBDS versions, automate data quality checks, and integrate additional clinical data. Our findings highlight the potential of federated health data networks and lay the groundwork for future research that can leverage high-quality RWD, aiming to contribute valuable knowledge to the field of cancer research.https://www.jmir.org/2025/1/e65681 |
| spellingShingle | Jasmin Ziegler Marcel Pascal Erpenbeck Timo Fuchs Anna Saibold Paul-Christian Volkmer Guenter Schmidt Johanna Eicher Peter Pallaoro Renata De Souza Falguera Fabio Aubele Marlien Hagedorn Ekaterina Vansovich Johannes Raffler Stephan Ringshandl Alexander Kerscher Julia Karolin Maurer Brigitte Kühnel Gerhard Schenkirsch Marvin Kampf Lorenz A Kapsner Hadieh Ghanbarian Helmut Spengler Iñaki Soto-Rey Fady Albashiti Dirk Hellwig Maximilian Ertl Georg Fette Detlef Kraska Martin Boeker Hans-Ulrich Prokosch Christian Gulden Bridging Data Silos in Oncology with Modular Software for Federated Analysis on Fast Healthcare Interoperability Resources: Multisite Implementation Study Journal of Medical Internet Research |
| title | Bridging Data Silos in Oncology with Modular Software for Federated Analysis on Fast Healthcare Interoperability Resources: Multisite Implementation Study |
| title_full | Bridging Data Silos in Oncology with Modular Software for Federated Analysis on Fast Healthcare Interoperability Resources: Multisite Implementation Study |
| title_fullStr | Bridging Data Silos in Oncology with Modular Software for Federated Analysis on Fast Healthcare Interoperability Resources: Multisite Implementation Study |
| title_full_unstemmed | Bridging Data Silos in Oncology with Modular Software for Federated Analysis on Fast Healthcare Interoperability Resources: Multisite Implementation Study |
| title_short | Bridging Data Silos in Oncology with Modular Software for Federated Analysis on Fast Healthcare Interoperability Resources: Multisite Implementation Study |
| title_sort | bridging data silos in oncology with modular software for federated analysis on fast healthcare interoperability resources multisite implementation study |
| url | https://www.jmir.org/2025/1/e65681 |
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