Predicting drug overdose and death after “before medically advised” hospital discharge
Risk prediction models may help clinicians and hospitals identify patients who might benefit from intensive support to prevent death or illict drug overdose after BMA discharge.
Authors
- Daniel Daly‐Grafstein (ORCID: https://orcid.org/0000-0002-2331-5991)
- Jennifer R. Lyden (ORCID: https://orcid.org/0000-0001-8403-9815)
- Benjamin Kaasa
- Alexis Crabtree (ORCID: https://orcid.org/0000-0002-1876-4354)
- Amanda Slaunwhite (ORCID: https://orcid.org/0000-0002-1355-0031)
- John A. Staples (ORCID: https://orcid.org/0000-0003-1397-1503)
- Hiten Naik (ORCID: https://orcid.org/0000-0002-5193-4618)
- Mayesha Khan (ORCID: https://orcid.org/0000-0002-3937-8874)
- Trudy Nasmith
- Jeffrey R. Brubacher (ORCID: https://orcid.org/0000-0002-4866-4231)
- Jessica Moe (ORCID: https://orcid.org/0000-0001-9557-1671)
- Xiao Hu
Institutions
- Provincial Health Services Authority (CA)
- University of Toronto (CA)
- Beilstein-Institut (DE)
- Denver Health Medical Center (US)
- BC Centre for Disease Control (CA)
- British Columbia Centre on Substance Use (CA)
- Denver Public Health (US)
- Institute of Population and Public Health (CA)
- Centre for Advancing Health Outcomes (CA)
- University of Colorado Denver (US)
Publication Details
- Journal
- Canadian Medical Association Journal
- Published
- 2025-11-10
- DOI
- https://doi.org/10.1503/cmaj.250492
- Primary Topic
- Cardiac, Anesthesia and Surgical Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 0.00