A Machine Learning Method for Allocating Scarce COVID-19 Monoclonal Antibodies
This retrospective cohort study proposes and tests a PLT method, which can be linked to a electronic health record data platform to improve real-time allocation of scarce treatments. Use of this PLT-based allocation method would have likely resulted in fewer hospitalizations across a population than were observed in usual care, with greater expected reductions than a commonly used point system.
Authors
- David Mayer (ORCID: https://orcid.org/0000-0002-6056-9771)
- Bethany M. Kwan (ORCID: https://orcid.org/0000-0002-4013-5618)
- Adit A. Ginde (ORCID: https://orcid.org/0000-0003-2325-206X)
- Neil R. Aggarwal (ORCID: https://orcid.org/0000-0002-0922-8824)
- Jennifer L. Peers
- Nichole E. Carlson (ORCID: https://orcid.org/0000-0003-0679-6663)
- Laurel Beaty (ORCID: https://orcid.org/0000-0001-8021-7872)
- Tellen D. Bennett (ORCID: https://orcid.org/0000-0003-1483-4236)
- Kyle C. Molina (ORCID: https://orcid.org/0000-0002-6764-5984)
- Lindsey E. Fish (ORCID: https://orcid.org/0000-0003-2931-0654)
- Mika K. Hamer (ORCID: https://orcid.org/0000-0003-2234-1095)
- Mengli Xiao (ORCID: https://orcid.org/0000-0003-4974-3588)
- Matthew K. Wynia
Institutions
- Colorado School of Public Health (US)
- Denver Health Medical Center (US)
- University of Colorado Anschutz Medical Campus (US)
- University of Colorado Denver (US)
Publication Details
- Journal
- JAMA Health Forum
- Published
- 2024-09-13
- DOI
- https://doi.org/10.1001/jamahealthforum.2024.2884
- Citations
- 3
- Primary Topic
- SARS-CoV-2 and COVID-19 Research
- Type
- article
- Field-Weighted Citation Impact
- 1.17