Prediction tool for discharge disposition and 30-day readmission using electronic health records among patients hospitalized for traumatic brain injury
We developed and validated predictive models using EHR data, culminating in a practical tool that may enhance the management of patients hospitalized with TBI by supporting personalized discharge planning and risk stratification.
Authors
- Tianjian Zhou (ORCID: https://orcid.org/0000-0002-7196-4232)
- Jessica Edelstein (ORCID: https://orcid.org/0000-0002-2210-7365)
- Deana B. Davalos (ORCID: https://orcid.org/0000-0003-2727-3634)
- Amanda Hoffman (ORCID: https://orcid.org/0009-0009-9186-5301)
- James E. Graham (ORCID: https://orcid.org/0000-0003-4300-1129)
- Haonan Wang (ORCID: https://orcid.org/0000-0003-3590-7633)
- Davis Davalos-DeLosh
- Amartya K. Maulik
Institutions
- University of Colorado Hospital (US)
- Shirley Ryan AbilityLab (US)
- University of Colorado Boulder (US)
- University of Colorado Denver (US)
- Colorado State University (US)
Publication Details
- Journal
- Frontiers in Neurology
- Published
- 2025-06-16
- DOI
- https://doi.org/10.3389/fneur.2025.1581176
- Citations
- 1
- Primary Topic
- Emergency and Acute Care Studies
- Type
- article
- Field-Weighted Citation Impact
- 2.25
Funders
- Colorado State University