Combining Machine Learning and Comparative Effectiveness Methodology to Study Primary Care Pharmacotherapy Pathways for Veterans With Depression.

Journal: Medical care

PMID: 40266632

Abstract

OBJECTIVES: To demonstrate an innovative method combining machine learning with comparative effectiveness research techniques and to investigate a hitherto unstudied question about the effectiveness of common prescribing patterns.

Authors

Ozgur Ozmen

Oak Ridge National Laboratory, Oak Ridge, TN.
Everett Rush

Oak Ridge National Laboratory, Oak Ridge, TN.
Byung H Park

Oak Ridge National Laboratory, Oak Ridge, TN.
Makoto Jones

VA Salt Lake City Health Care System.
Jodie Trafton

Department of Veterans Affairs, Washington, DC.
Lisa Brenner

Department of Veterans Affairs, Washington, DC.
Randall W Rupper

Department of Veterans Affairs, Washington, DC.
Merry Ward

Department of Veterans Affairs, Washington, DC.
Jonathan R Nebeker

Department of Veterans Affairs, Office of Health Informatics, USA.
Steven D Pizer

Department of Veterans Affairs, Washington, DC.

Keywords

Adult Antidepressive Agents Comparative Effectiveness Research Depressive Disorder, Major Female Humans Machine Learning Male Middle Aged Practice Patterns, Physicians' Primary Health Care Selective Serotonin Reuptake Inhibitors United States United States Department of Veterans Affairs Veterans

External Resources

View on PubMed Access via DOI PubMed (40266632)

Combining Machine Learning and Comparative Effectiveness Methodology to Study Primary Care Pharmacotherapy Pathways for Veterans With Depression.

Abstract

Authors

Keywords

External Resources

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