Real-World Integration of a Sepsis Deep Learning Technology Into Routine Clinical Care: Implementation Study.

ABSTRACT:

Background

Successful integrations of machine learning into routine clinical care are exceedingly rare, and barriers to its adoption are poorly characterized in the literature.

Objective

This study aims to report a quality improvement effort to integrate a deep learning sepsis detection and management platform, Sepsis Watch, into routine clinical care.

Methods

In 2016, a multidisciplinary team consisting of statisticians, data scientists, data engineers, and clinicians was assembled by the leadership of an academic health system to radically improve the detection and treatment of sepsis. This report of the quality improvement effort follows the learning health system framework to describe the problem assessment, design, development, implementation, and evaluation plan

SUBMITTER: Sendak MP 

PROVIDER: S-EPMC7391165 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature