Verbesserung des Record Linkage f\"ur die Gesundheitsforschung in Deutschland

• URL: http://arxiv.org/abs/2312.10093v1
• Date: Thu, 14 Dec 2023 11:00:14 GMT
• Title: Verbesserung des Record Linkage f\"ur die Gesundheitsforschung in Deutschland
• Abstract summary: Record linkage enables the answering of scientific questions that cannot be addressed using single data sources. Due to the sensitivity of health data, there are strict legal requirements to prevent potential misuse. This paper discusses limitations and possibilities of various data linkage approaches tailored to different use cases.
• Score: 0.0838660459623437
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Record linkage means linking data from multiple sources. This approach enables the answering of scientific questions that cannot be addressed using single data sources due to limited variables. The potential of linked data for health research is enormous, as it can enhance prevention, treatment, and population health policies. Due the sensitivity of health data, there are strict legal requirements to prevent potential misuse. However, these requirements also limit the use of health data for research, thereby hindering innovations in prevention and care. Also, comprehensive Record linkage in Germany is often challenging due to lacking unique personal identifiers or interoperable solutions. Rather, the need to protect data is often weighed against the importance of research aiming at healthcare enhancements: for instance, data protection officers may demand the informed consent of individual study participants for data linkage, even when this is not mandatory. Furthermore, legal frameworks may be interpreted differently on varying occasions. Given both, technical and legal challenges, record linkage for health research in Germany falls behind the standards of other European countries. To ensure successful record linkage, case-specific solutions must be developed, tested, and modified as necessary before implementation. This paper discusses limitations and possibilities of various data linkage approaches tailored to different use cases in compliance with the European General Data Protection Regulation. It further describes requirements for achieving a more research-friendly approach to linking health data records in Germany. Additionally, it provides recommendations to legislators. The objective of this work is to improve record linkage for health research in Germany.

Related papers

• Die Verarbeitung medizinischer Forschungsdaten ohne datenschutzrechtliche Einwilligung: Der Korridor zwischen Anonymisierung und der Forschungsausnahme in Österreich [0.0]
  This article analyses options for data processing in the field of medical research without consent.<n>It describes the legal framework for anonymisation under the fern, the national Austrian implementation of the research exemption, and their interaction.
  arXiv  Detail & Related papers  (2025-09-02T15:51:33Z)
• Federated Learning in Healthcare: Model Misconducts, Security, Challenges, Applications, and Future Research Directions -- A Systematic Review [2.710010611878837]
  Federated Learning (FL) enables multiple healthcare institutions to collaboratively learn from decentralized data without sharing it. FL's scope in healthcare covers areas such as disease prediction, treatment customization, and clinical trial research. implementing FL poses challenges, including model convergence in non-IID data environments, communication overhead, and managing multi-institutional collaborations.
  arXiv  Detail & Related papers  (2024-05-22T16:59:50Z)
• Retrieval Augmented Thought Process for Private Data Handling in Healthcare [53.89406286212502]
  We introduce the Retrieval-Augmented Thought Process (RATP) RATP formulates the thought generation of Large Language Models (LLMs) On a private dataset of electronic medical records, RATP achieves 35% additional accuracy compared to in-context retrieval-augmented generation for the question-answering task.
  arXiv  Detail & Related papers  (2024-02-12T17:17:50Z)
• Balancing Privacy and Progress in Artificial Intelligence: Anonymization in Histopathology for Biomedical Research and Education [1.8078387709049526]
  Transferring medical data "as open as possible" poses a risk to patient privacy. Existing regulations push towards keeping medical data "as closed as necessary" to avoid re-identification risks. This paper explores the legal regulations and terminologies for medical data-sharing.
  arXiv  Detail & Related papers  (2023-07-18T16:53:07Z)
• A Comparative Audit of Privacy Policies from Healthcare Organizations in USA, UK and India [19.45392112573428]
  This paper presents a large-scale data-driven study to audit privacy policies from healthcare organizations in USA, UK, and India. First, we collected the privacy policies of thousands of healthcare organizations in these countries and cleaned this privacy policy data using a clustering-based mixed-method technique. Second, we adopted a summarization-based technique to uncover exact broad data practices across countries and notice important differences.
  arXiv  Detail & Related papers  (2023-06-20T14:21:37Z)
• The Design and Implementation of a National AI Platform for Public Healthcare in Italy: Implications for Semantics and Interoperability [62.997667081978825]
  The Italian National Health Service is adopting Artificial Intelligence through its technical agencies. Such a vast programme requires special care in formalising the knowledge domain. Questions have been raised about the impact that AI could have on patients, practitioners, and health systems.
  arXiv  Detail & Related papers  (2023-04-24T08:00:02Z)
• DeID-GPT: Zero-shot Medical Text De-Identification by GPT-4 [80.36535668574804]
  We develop a novel GPT4-enabled de-identification framework (DeID-GPT") Our developed DeID-GPT showed the highest accuracy and remarkable reliability in masking private information from the unstructured medical text. This study is one of the earliest to utilize ChatGPT and GPT-4 for medical text data processing and de-identification.
  arXiv  Detail & Related papers  (2023-03-20T11:34:37Z)
• GDPR Compliant Collection of Therapist-Patient-Dialogues [48.091760741427656]
  We elaborate on the challenges we faced in starting our collection of therapist-patient dialogues in a psychiatry clinic under the General Data Privacy Regulation of the European Union. We give an overview of each step in our procedure and point out the potential pitfalls to motivate further research in this field.
  arXiv  Detail & Related papers  (2022-11-22T15:51:10Z)
• Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset [46.156169284961045]
  We offer an approach to filtering grounded in law, which has directly addressed the tradeoffs in filtering material. First, we gather and make available the Pile of Law, a 256GB dataset of open-source English-language legal and administrative data. Second, we distill the legal norms that governments have developed to constrain the inclusion of toxic or private content into actionable lessons. Third, we show how the Pile of Law offers researchers the opportunity to learn such filtering rules directly from the data.
  arXiv  Detail & Related papers  (2022-07-01T06:25:15Z)
• A Review of Anonymization for Healthcare Data [0.30586855806896046]
  Health data is highly sensitive and subject to regulations such as General Data Protection Regulation ( General Data Protection Regulation ( General Data Protection Regulation ( General Data Protection Regulation ( General Data Protection Regulation ( General Data Protection Regulation ( General Data Protection Regulation ( General Data Protection Regulation ( General Data Protection Regulation ( General Data Protection Regulation ( General Data Protection Regulation ( General Data Protection Regulation ( General Data Protection Regulation ( General Data Protection Regulation ( General Data Protection Regulation ( General Data Protection Regulation ( General Data Protection Regulation ( General Data Protection Regulation ( General Data Protection Regulation ( General Data Protection Regulation ( General Data Protection Regulation ( General Data Protection Regulation ( General Data Protection Regulation (
  arXiv  Detail & Related papers  (2021-04-13T21:44:29Z)
• Revolutionizing Medical Data Sharing Using Advanced Privacy Enhancing Technologies: Technical, Legal and Ethical Synthesis [5.6324529994086845]
  Homomorphic Encryption and Secure Multiparty Computation (defined together as Multiparty Homomorphic Encryption or MHE) PETs provide a mathematical guarantee of privacy, with MHE providing performance advantage over separately using HE or SMC. We explain how MHE can reduce the reliance on customized contractual measures between institutions.
  arXiv  Detail & Related papers  (2020-10-27T17:03:28Z)
• Second layer data governance for permissioned blockchains: the privacy management challenge [58.720142291102135]
  In pandemic situations, such as the COVID-19 and Ebola outbreak, the action related to sharing health data is crucial to avoid the massive infection and decrease the number of deaths. In this sense, permissioned blockchain technology emerges to empower users to get their rights providing data ownership, transparency, and security through an immutable, unified, and distributed database ruled by smart contracts.
  arXiv  Detail & Related papers  (2020-10-22T13:19:38Z)
• COVI White Paper [67.04578448931741]
  Contact tracing is an essential tool to change the course of the Covid-19 pandemic. We present an overview of the rationale, design, ethical considerations and privacy strategy of COVI,' a Covid-19 public peer-to-peer contact tracing and risk awareness mobile application developed in Canada.
  arXiv  Detail & Related papers  (2020-05-18T07:40:49Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.