Stefan Sauermann

Stefan Sauermann

University of Applied Sciences Technikum Wien
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Stefan Sauermann has a total of 31 co-authors. Here are the top co-authors by number of shared publications:

Latest Publications

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    Bridging Gaps in Standards for the Secondary Use of Health Data: Exploratory Standard, Tool Assessment, and Feasibility Study

    by Jaleh Shoshtarian Malak, Leonie von Berlin, Irina Balaur, Rada Hussein, Philip Gribbon, Yojana Gadiya, Somayeh Abedian, Andreas Kremer, Stefan Sauermann, Francisco J Núñez-Benjumea, et al.

    Background: Standards for the secondary use of health data remain under development and do not comprehensively address specific categories of health data. Existing health data and interoperability standards are primarily designed for the primary use of health care, leaving gaps in their applicability for research, regulatory and decision-making. This research is part of the Integration of Heterogeneous Data and Evidence Towards Regulatory and Health Technology Assessment Acceptance (IDERHA) project, which creates a federated processing environment for secondary health care use cases. Objective: This study aims to recommend a set of standards and tools to support harmonization objectives in the secondary use of health data. The proposed standards establish a shared representation model for data providers and stakeholders, improving data adherence to findable, accessible, interoperable, and reusable (FAIR) principles and interoperability. Methods: In this exploratory assessment and feasibility study, we performed a consensus-based evaluation of health data standards and harmonization tools across major health-data categories. State-of-the-art standards from different standard-producing organizations were evaluated based on community adoption, technical suitability, and alignment with European Health Data Space requirements. Data-harmonization tools were tested in a pilot experiment using synthetic Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM)–based data to assess the quality and feasibility of applying harmonization workflows within IDERHA. We also assessed the inherent adherence to FAIR principles of the OMOP-CDM, identifying its strengths in semantic interoperability and data reuse. Finally, we addressed the datasets handling challenges (metadata discoverability, global identifiers, access control, and licensing), which are not inherently solvable by bare data description standards, through complementary mechanisms implemented in IDERHA. Results: We recommend a set of standards to support the secondary use of heterogeneous health data across clinical, imaging, genomic, socioeconomic, environmental, and patient-reported outcome measure (PROM)/patient-reported experience measure (PREM) domains. This standards collection, centered on OMOP-CDM and complemented by established extensions, was paired with selected harmonization and quality-assessment tools. Feasibility testing on synthetic OMOP data confirmed the suitability of the tools for evaluating data quality, mapping accuracy, and extract, transform, and load. A lung-cancer use case demonstrated how diverse datasets can be harmonized and prepared for federated analysis. A FAIR-dataset maturity evaluation showed that integrating OMOP data into the IDERHA environment substantially improved adherence to FAIR principles—particularly in metadata completeness, interoperability, and hosting capabilities—supporting enhanced discoverability, accessibility, and reuse of standardized health data. Conclusions: By strengthening adherence to FAIR principles, this research facilitates the broader integration of standardized health data for regulatory processes and health technology assessment applications. The proposed standards and tools provide a comprehensive overview of existing approaches, while offering solutions that can be applied to other scenarios involving the secondary use of health data.

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    Bridging Gaps in Standards for the Secondary Use of Health Data: Towards Data Harmonization and FAIRness in IDERHA (Preprint)

    by Jaleh Shoshtarian Malak, Leonie von Berlin, Irina Balaur, Rada Hussein, Philip Gribbon, Yojana Gadiya, Somayeh Abedian, Andreas Kremer, Stefan Sauermann, Francisco J Núñez-Benjumea, et al.

    BACKGROUND Standards for the secondary use of health data are still under development and do not comprehensively address specific categories of health data. Existing health data and interoperability standards are primarily designed for the primary use of healthcare, leaving gaps in their applicability for research, regulatory and decision-making. This research is part of the IDERHA project, which creates a federated processing environment for secondary healthcare use cases aligned with EHDS regulations. OBJECTIVE This study aims to recommend a set of standards and tools to support harmonization objectives in the secondary use of health data. The proposed standards establish a shared representation model for data providers and stakeholders, improving data FAIRness and interoperability. METHODS A comprehensive review and selection of standards and harmonization tools were performed across major health-data categories. Standards from OHDSI/OMOP, HL7 FHIR, DICOM, DCAT-AP/HealthDCAT-AP, GA4GH, INSPIRE, CDISC, and others were evaluated based on community adoption, technical suitability, and alignment with EHDS requirements. Data-harmonization tools were tested in a pilot experiment using synthetic OMOP-CDM based data to assess readiness, quality, and feasibility of applying harmonization workflows within IDERHA. We also assessed the inherent FAIRness of OMOP CDM, identifying its strengths in semantic interoperability and data reuse, while addressing limitations related to metadata discoverability, global identifiers, access control, and licensing through complementary mechanisms implemented in IDERHA. RESULTS In this research, we recommend a set of standards to support the secondary use of heterogeneous health data across clinical, imaging, genomic, socioeconomic, environmental, and PROM/PREM domains. This standards collection, centered on OMOP CDM and complemented by established domain-specific specifications, was paired with selected harmonization and quality-assessment tools from the OHDSI and EHDEN ecosystems. Feasibility testing on synthetic OMOP data confirmed the suitability of tools for evaluating data quality, mapping accuracy, and ETL. A lung-cancer use case demonstrated how diverse datasets can be harmonized and prepared for federated analysis. FAIR-DSM evaluation showed that integrating OMOP data into the IDERHA environment substantially improved FAIRness—particularly in metadata completeness, interoperability, and hosting capabilities—supporting enhanced discoverability, accessibility, and reuse of standardized health data. CONCLUSIONS By strengthening adherence to FAIR principles, this research facilitates the broader integration of standardized health data for regulatory processes and health technology assessment (HTA) applications. The proposed set of standards and tools provides a comprehensive overview of existing approaches, while offering solutions that can be applied to other scenarios involving the secondary use of health data.

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    OMOP-on-FHIR: Integrating the Clinical Data Through FHIR Bundle to OMOP CDM

    by Prabath Jayathissa, Lukas Rohatsch, Stefan Sauermann, Rada Hussein

    The harmonization of the OMOP Common Data Model (CDM) with HL7 FHIR aims to enhance interoperability in clinical research by harmonizing diverse healthcare datasets. This process, referred to as OMOP-on-FHIR, leverages FHIR Bundles for real-time clinical data exchange and transforms these resources into OMOP CDM format using an ETL process. The ETL pipeline, facilitated by tools like XSLT, enables the extraction, transformation, and loading of data while maintaining semantic consistency. By bridging these two standards, OMOP-on-FHIR promotes the seamless exchange of data across clinical systems and research-oriented databases, supporting global health studies, advanced analytics, and personalized medicine. This methodology advances cross-border research by providing a standardized approach to data management and analysis, thereby improving healthcare outcomes.

    Cited by 5
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    eHealth and mHealth

    by Bernhard Neumayer, Stefan Sauermann, Sten Hanke

    EHealth (electronic health) and mHealth (mobile health) have been rapidly evolving in recent years, offering innovative solutions to healthcare challenges

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    Electro-mechanical Lung Simulator Using Polymer and Organic Human Lung Equivalents for Realistic Breathing Simulation

    by Richard Pasteka, Mathias Forjan, Stefan Sauermann, Andreas Drauschke

    Simulation models in respiratory research are increasingly used for medical product development and testing, especially because in-vivo models are coupled with a high degree of complexity and ethical concerns. This work introduces a respiratory simulation system, which is bridging the gap between the complex, real anatomical environment and the safe, cost-effective simulation methods. The presented electro-mechanical lung simulator, xPULM, combines in-silico, ex-vivo and mechanical respiratory approaches by realistically replicating an actively breathing human lung. The reproducibility of sinusoidal breathing simulations with xPULM was verified for selected breathing frequencies (10–18 bpm) and tidal volumes (400–600 ml) physiologically occurring during human breathing at rest. Human lung anatomy was modelled using latex bags and primed porcine lungs. High reproducibility of flow and pressure characteristics was shown by evaluating breathing cycles (nTotal = 3273) with highest standard deviation |3σ| for both, simplified lung equivalents ( $${{\boldsymbol{\mu }}}_{\dot{{\bf{V}}}}$$µV̇ = 23.98 ± 1.04 l/min, μP = −0.78 ± 0.63 hPa) and primed porcine lungs ( $${{\boldsymbol{\mu }}}_{\dot{{\bf{V}}}}$$µV̇ = 18.87 ± 2.49 l/min, μP = −21.13 ± 1.47 hPa). The adaptability of the breathing simulation parameters, coupled with the use of porcine lungs salvaged from a slaughterhouse process, represents an advancement towards anatomically and physiologically realistic modelling of human respiration.

    Cited by 27
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    Telemonitoring of Blood Glucose

    by Matthias Frohner, Markus Meyer, Klaus Donsa, Philipp Urbauer, Veronika David, Stefan Sauermann

    Cited by 1
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    Smart grid interoperability profiles development

    by Matthias Frohner, Marion Gottschalk, Gerald Franzl, Richard Pasteka, Mathias Uslar, Stefan Sauermann

    Interoperability in the Energy System is an important topic for the development of Smart Grids. In this paper we introduce a structured approach to solve the complex interoperability issues of connected systems and sub-systems based on experiences from the healthcare enterprise, where formerly rather closed systems were successfully migrated towards more open system. This approach combines well-established use case methodologies from the software development domain with benefits of the concept of integration profiles which can be found in the healthcare domain. The combination of the two methods is demonstrated by developing an integration profile for an application example from the Smart Grid domain; the virtual power plant operation use case. Using the presented method, a step-by-step guideline for implementers could be created. The profiling methodology seems to be an appropriate method to approach complex interoperability issues of Energy Systems and may be expanded to other fields.

    Cited by 6