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    <completedYear/>
    <publishedYear>2025</publishedYear>
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    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>9</pageNumber>
    <edition/>
    <issue/>
    <volume>25</volume>
    <type>article</type>
    <publisherName>BMC</publisherName>
    <publisherPlace/>
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    <publishedDate>2025-05-14</publishedDate>
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    <title language="eng">Sharing health data for research purposes: results of a population survey in Germany</title>
    <abstract language="eng">BACKGROUND: Increased use of health data has the potential to improve both health care and health policies. Several recent policy initiatives at the European and German legislative levels aim to increase the primary and secondary use of health data. However, little is known about general population views on health data access for research. Most studies are based on subsets defined by specific illnesses.&#13;
METHODS: We commissioned a national computer-assisted dual-frame telephone survey (landline and mobile). Logit estimation models were used to identify predictors of willingness to provide access to health data to different organizations (universities in Germany, universities worldwide, German government organizations, pharmaceutical companies).&#13;
RESULTS: A high willingness to share health data for research purposes is observed, depending on the specific data recipient. The willingness is highest for research at universities in Germany and German governmental organizations, and lowest regarding research by pharmaceutical companies. The main drivers for sharing health data are the level of trust in public institutions, the respondents' assessment of the seriousness and likelihood of data misuse, and the level of digital literacy. Age, gender, and level of education have small effects and do not determine the willingness to share health data for all organizations.&#13;
CONCLUSION: We present evidence from a random sample of the German population. The results indicate widespread support among the population for providing access to health data for research purposes. Similar to findings in other countries, the willingness depends strongly on the recipient of the data. This paper evaluates the impact of various determinants - identified in previous qualitative and quantitative research - on the willingness of the German population to share health data. While previous studies have found that patients are generally more willing to share health data, we found that the presence of a medical precondition does not translate into respondents' unequivocal support for health data sharing. We identify privacy concerns, general trust, and digital literacy as key factors influencing the willingness to share health data. Therefore, policymakers and stakeholders need to ensure and communicate the necessary privacy protection measures to increase the willingness of the German population to share health data.</abstract>
    <parentTitle language="eng">BMC health services research</parentTitle>
    <identifier type="doi">10.1186/s12913-025-12706-9</identifier>
    <identifier type="pmid">40369578</identifier>
    <identifier type="urn">urn:nbn:de:bvb:898-opus4-81622</identifier>
    <note>Corresponding author der OTH Regensburg: Caroline Dotter</note>
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    <enrichment key="CorrespondingAuthor">Caroline Dotter</enrichment>
    <licence>Creative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International</licence>
    <author>Caroline Dotter</author>
    <author>Sonja Haug</author>
    <author>Rainer Schnell</author>
    <author>Georgios Raptis</author>
    <author>Karsten Weber</author>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="institutes" number="FakSoz">Fakultät Sozial- und Gesundheitswissenschaften</collection>
    <collection role="oaweg" number="">Gold Open Access- Erstveröffentlichung in einem/als Open-Access-Medium</collection>
    <collection role="persons" number="raptisehealth">Raptis, Georgios (Prof. Dr.) - eHealth Lab</collection>
    <collection role="persons" number="weberlate">Weber, Karsten (Prof. Dr.) - Labor für Technikfolgenabschätzung und Angewandte Ethik</collection>
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    <collection role="institutes" number="">Institut für Sozialforschung und Technikfolgenabschätzung (IST)</collection>
    <collection role="institutes" number="">Labor Empirische Sozialforschung</collection>
    <collection role="institutes" number="">Labor für Technikfolgenabschätzung und Angewandte Ethik (LaTe)</collection>
    <collection role="persons" number="hauglasofo">Haug, Sonja (Prof. Dr.) - Labor Empirische Sozialforschung</collection>
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    <thesisPublisher>Ostbayerische Technische Hochschule Regensburg</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-oth-regensburg/files/8162/Dotter_BMC_2025.pdf</file>
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  <doc>
    <id>8704</id>
    <completedYear/>
    <publishedYear>2026</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>20</volume>
    <type>article</type>
    <publisherName>Elsevier</publisherName>
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    <title language="eng">Developing a smart and scalable tool for histopathological education—PATe 2.0</title>
    <abstract language="eng">Digital microscopy plays a crucial role in pathology education, providing scalable and standardized access to learning resources. In response, we present PATe 2.0, a scalable redeveloped web-application of the former PATe system from 2015. PATe 2.0 was developed using an agile, iterative process and built on a microservices architecture to ensure modularity, scalability, and reliability. It integrates a modern web-based user interface optimized for desktop and tablet use and automates key workflows such as whole-slide image uploads and processing. Performance tests demonstrated that PATe 2.0 significantly reduces tile request times compared to PATe, despite handling larger tiles. The platform supports open formats like DICOM and OpenSlide, enhancing its interoperability and adaptability across institutions. PATe 2.0 represents a robust digital microscopy solution in pathology education enhancing usability, performance, and flexibility. Its design enables future integration of research algorithms and highlights it as a pivotal tool for advancing pathology education and research.</abstract>
    <parentTitle language="eng">Journal of Pathology Informatics</parentTitle>
    <identifier type="issn">2153-3539</identifier>
    <identifier type="doi">10.1016/j.jpi.2025.100535</identifier>
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    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Lina Winter</author>
    <author>Annalena Artinger</author>
    <author>Hendrik Böck</author>
    <author>Vignesh Ramakrishnan</author>
    <author>Bruno Reible</author>
    <author>Jan Albin</author>
    <author>Peter J. Schüffler</author>
    <author>Georgios Raptis</author>
    <author>Christoph Brochhausen</author>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="institutes" number="RCBE">Regensburg Center of Biomedical Engineering - RCBE</collection>
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    <collection role="persons" number="raptisehealth">Raptis, Georgios (Prof. Dr.) - eHealth Lab</collection>
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    <collection role="othforschungsschwerpunkt" number="">Digitale Transformation</collection>
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