Frequent Emergency Medical Services Utilization Among Older Patients: Exploration and Automatic Identification Using Natural Language Processing
An NLP-based model using EMS text data could improve the identification of frequent users. Integration of such tools into prehospital care systems may support earlier identification and tailored intervention strategies for older people frequent in use of acute care.
Authors
- Laura Măruşter (ORCID: https://orcid.org/0000-0002-6588-7648)
- Hidde Dijkstra (ORCID: https://orcid.org/0000-0002-3173-6841)
- Annemarieke de Jonghe
- Maaike A. Pouw (ORCID: https://orcid.org/0000-0003-3618-1838)
- Bert Dercksen (ORCID: https://orcid.org/0000-0003-2892-0020)
- Durk-Jouke van der Zee (ORCID: https://orcid.org/0000-0001-9754-1193)
- Barbara C van Munster
- Eduard-Raul Kőntős
Institutions
- University Medical Center Groningen (NL)
- University of Groningen (NL)
- University of Applied Sciences Utrecht (NL)
- Utrecht University (NL)
- Tergooi (NL)
Publication Details
- Journal
- Journal of the American Medical Directors Association
- Published
- 2025-09-27
- DOI
- https://doi.org/10.1016/j.jamda.2025.105814
- Citations
- 1
- Primary Topic
- Emergency and Acute Care Studies
- Type
- article
- Field-Weighted Citation Impact
- 2.25
Funders
- Universitair Medisch Centrum Groningen