Systematic review and longitudinal analysis of implementing Artificial Intelligence to predict clinical deterioration in adult hospitals: what is known and what remains uncertain.

ABSTRACT:

Objective

To identify factors influencing implementation of machine learning algorithms (MLAs) that predict clinical deterioration in hospitalized adult patients and relate these to a validated implementation framework.

Materials and methods

A systematic review of studies of implemented or trialed real-time clinical deterioration prediction MLAs was undertaken, which identified: how MLA implementation was measured; impact of MLAs on clinical processes and patient outcomes; and barriers, enablers and uncertainties within the implementation process. Review findings were then mapped to the SALIENT end-to-end implementation framework to identify the implementation stages at which these factors applied.

Results

Thirty-seven articles relating to 14 groups of MLAs were ident

SUBMITTER: van der Vegt AH 

PROVIDER: S-EPMC10797271 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature