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Use of machine learning to predict clinical decision support compliance, reduce alert burden, and evaluate duplicate laboratory test ordering alerts
OBJECTIVES: While well-designed clinical decision support (CDS) alerts can improve patient care, utilization management, and population health, excessive alerting may be counterproductive, leading to clinician burden and alert fatigue. We sought to develop machine learning models to predict whether...
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| Publicado no: | JAMIA Open |
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| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Oxford University Press
2021
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7935497/ https://ncbi.nlm.nih.gov/pubmed/33709062 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/jamiaopen/ooab006 |
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