Potential of Machine Learning for Discharge Management Using Routine Health Insurance Data
Introduction: The use of artificial intelligence, particularly machine learning models, to develop predictive models from health insurance routine data is becoming increasingly common [ref:1], [ref:2]. However, it’s not always clear when and how to leverage the advantages [for full text, please go to the a.m. URL]
Authors
- T. Pollmann
- Zully Ritter (ORCID: https://orcid.org/0000-0002-1330-6178)
- Lisa Weller (ORCID: https://orcid.org/0000-0003-0560-7680)
- Anne-Christin Hauschild (ORCID: https://orcid.org/0000-0002-7499-4373)
- M. Mäurer (ORCID: https://orcid.org/0009-0009-7696-3931)
- Jacqueline Michelle Beinecke
- Matthias Kretzler
- Thomas Grobe
Institutions
- Justus-Liebig-Universität Gießen (DE)
- Improvement Service (GB)
- Universitätsmedizin Göttingen (DE)
Publication Details
- Journal
- German Medical Science (German Research Foundation)
- Published
- 2026-04-01
- DOI
- https://doi.org/10.3205/25gmds203
- Primary Topic
- Machine Learning in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00