Development of a Machine Learning Model Using Electronic Health Record Data to Identify Antibiotic Use Among Hospitalized Patients

IMPORTANCE: Comparisons of antimicrobial use among hospitals are difficult to interpret owing to variations in patient case mix. Risk-adjustment strategies incorporating larger numbers of variables haves been proposed as a method to improve comparisons for antimicrobial stewardship assessments. OBJE...

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Detalles Bibliográficos
Autores principales: Moehring, Rebekah W., Phelan, Matthew, Lofgren, Eric, Nelson, Alicia, Dodds Ashley, Elizabeth, Anderson, Deverick J., Goldstein, Benjamin A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Association 2021
Materias:
Original Investigation
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8008288/
https://www.ncbi.nlm.nih.gov/pubmed/33779743
http://dx.doi.org/10.1001/jamanetworkopen.2021.3460

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8008288/
https://www.ncbi.nlm.nih.gov/pubmed/33779743
http://dx.doi.org/10.1001/jamanetworkopen.2021.3460

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