Machine learning evaluation of inequities and disparities associated with nurse sensitive indicator safety events.

Journal: Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing
PMID: 38773783

Abstract

PURPOSE: To use machine learning to examine health equity and clinical outcomes in patients who experienced a nurse sensitive indicator (NSI) event, defined as a fall, a hospital-acquired pressure injury (HAPI) or a hospital-acquired infection (HAI).

Authors

  • Erika R Georgantes
    Nursing Quality Management Coordinator, Nursing Quality, Stanford Health Care, Stanford, California, USA.
  • Fatma Gunturkun
    Quantitative Sciences Unit, Department of Medicine, Stanford University, Palo Alto, California.
  • T J McGreevy
    Quality Analytics, Stanford Health Care, Stanford, California, USA.
  • Mary E Lough
    Center for Evidence Based Practice and Implementation Science, Stanford Health Care, Stanford, California, USA.

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