Using Encounter-Level Data for Risk-Adjustment of Antimicrobial Use Comparisons: Feasibility and Variable Selection
Expert adjudication required personnel effort and potentially introduced biases, yet did not produce results different from an agnostic approach. Risk-adjustment incorporating large encounter-level data and machine learning may prove feasible and meaningful in future hospital AU assessments.
Authors
- Danielle Doughman (ORCID: https://orcid.org/0000-0002-2052-4640)
- Congwen Zhao (ORCID: https://orcid.org/0000-0002-8540-6880)
- Eili Klein (ORCID: https://orcid.org/0000-0002-1304-5289)
- Deverick J. Anderson (ORCID: https://orcid.org/0000-0001-6882-5496)
- Sara E. Cosgrove (ORCID: https://orcid.org/0000-0001-9458-4331)
- Whitney R. Buckel (ORCID: https://orcid.org/0000-0001-9505-2572)
- William E. Trick (ORCID: https://orcid.org/0000-0002-3243-5098)
- Elizabeth Dodds Ashley (ORCID: https://orcid.org/0000-0002-4213-6104)
- Benjamin Alan Goldstein (ORCID: https://orcid.org/0000-0001-5261-3632)
- Rachel Addison
- Rebekah W. Moehring (ORCID: https://orcid.org/0000-0001-7741-6029)
- Michael J. Smith (ORCID: https://orcid.org/0000-0001-6947-099X)
- Emily S Spivak (ORCID: https://orcid.org/0000-0002-4314-9644)
- Michael E Yarrington (ORCID: https://orcid.org/0000-0003-3186-1519)
- David J. Weber (ORCID: https://orcid.org/0000-0003-1726-4435)
- Carlos A.Q. Santos (ORCID: https://orcid.org/0000-0002-6224-0371)
Institutions
- Intermountain Healthcare (US)
- Johns Hopkins University (US)
- Duke University (US)
- University of Utah (US)
- Johns Hopkins Medicine (US)
- University of North Carolina Hospitals (US)
- Duke University Hospital (US)
- Cook County Health and Hospitals System (US)
- Rush University (US)
Publication Details
- Journal
- Clinical Infectious Diseases
- Published
- 2025-12-11
- DOI
- https://doi.org/10.1093/cid/ciaf682
- Citations
- 1
- Primary Topic
- Antibiotic Use and Resistance
- Type
- article
- Field-Weighted Citation Impact
- 1.26