Precision population analytics: population management at the point-of-care.

Journal: Journal of the American Medical Informatics Association : JAMIA

PMID: 33180897

Abstract

OBJECTIVE: To present clinicians at the point-of-care with real-world data on the effectiveness of various treatment options in a precision cohort of patients closely matched to the index patient.

Authors

Paul C Tang

Stanford Clinical Excellence Research Center, Stanford University, Stanford, California, USA.
Sarah Miller

IBM Research, USA.
Harry Stavropoulos

Center for Computational Health, IBM Research, Cambridge, Massachusetts, USA.
Uri Kartoun

Harvard Medical School, Boston, MA, USA.
John Zambrano

Atrius Health Academic Institute, Atrius Health, Boston, Massachusetts, USA.
Kenney Ng

Center for Computational Health, IBM Research, Yorktown Heights, NY, USA.

Keywords

Decision Making, Computer-Assisted Diabetes Mellitus, Type 2 Electronic Health Records Evidence-Based Medicine Humans Hyperlipidemias Hypertension Machine Learning Patient Care Management Practice Guidelines as Topic Treatment Outcome

External Resources

View on PubMed Access via DOI PubMed (33180897)

Precision population analytics: population management at the point-of-care.

Abstract

Authors

Keywords

External Resources

Popular Topics

Recent Journals