Development and validation of an EHR-based risk prediction model for geriatric patients undergoing urgent and emergency surgery
We developed a model to accurately predict major postoperative complications in geriatric patients undergoing urgent or emergency surgery using the patient's own existing EHR data. EHR implementation of this model could efficiently support clinicians' surgical risk assessment and perioperative decision-making discussions in this vulnerable patient population.
Authors
- Jie Huang (ORCID: https://orcid.org/0000-0002-4096-5128)
- Bradley R. Cohn
- Mary Reed (ORCID: https://orcid.org/0000-0002-9986-9499)
- Robert W. Chang (ORCID: https://orcid.org/0000-0003-2765-9537)
- Judith C.F. Hwang
- Edward N. Yap (ORCID: https://orcid.org/0000-0001-7992-5572)
- Jie-Wei Chiu
Institutions
- Kaiser Permanente (US)
- University of California, San Francisco (US)
- Kaiser Permanente Vallejo Medical Center (US)
- Colorado Permanente Medical Group (US)
- Kaiser Permanente South San Francisco Medical Center (US)
Publication Details
- Journal
- BMC Anesthesiology
- Published
- 2025-01-27
- DOI
- https://doi.org/10.1186/s12871-024-02880-4
- Citations
- 6
- Primary Topic
- Cardiac, Anesthesia and Surgical Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 8.33