Cargando…
1018. Using prediction modeling to inform risk-adjustment strategy for hospital antimicrobial use: Can we predict who gets an inpatient antimicrobial?
BACKGROUND: Hospital antimicrobial stewardship program (ASP) assessments based on comparisons of antimicrobial use (AU) among multiple hospitals are difficult to interpret without risk-adjustment for patient case-mix. We aimed to determine whether variables of varying complexity, derived retrospecti...
Autores principales: | Moehring, Rebekah W, Phelan, Matthew, Lofgren, Eric, Nelson, Alicia, Neuhauser, Melinda M, Hicks, Lauri, Dodds Ashley, Elizabeth, Anderson, Deverick J, Goldstein, Benjamin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6811028/ http://dx.doi.org/10.1093/ofid/ofz360.882 |
Ejemplares similares
-
1019. Defining electronic patient phenotypes to inform risk-adjustment strategies in hospital antimicrobial use comparisons
por: Moehring, Rebekah W, et al.
Publicado: (2019) -
Inpatient plus Post-discharge Durations of Therapy to Identify Antimicrobial Stewardship Opportunities at Transitions of Care
por: Dyer, April, et al.
Publicado: (2017) -
1823. Signal or Noise? A Comparison of Methods to Identify Outliers in Antimicrobial Use (AU)
por: Moehring, Rebekah W, et al.
Publicado: (2018) -
Development of a Machine Learning Model Using Electronic Health Record Data to Identify Antibiotic Use Among Hospitalized Patients
por: Moehring, Rebekah W., et al.
Publicado: (2021) -
1629. Targeted Antimicrobial Use Admission Provides an Actionable Denominator for Antimicrobial Stewardship Programs Evaluating Inpatient Length of Therapy
por: Dyer, April, et al.
Publicado: (2018)