External evaluation of the Dynamic Criticality Index: A machine learning model to predict future need for ICU care in hospitalized pediatric patients.

ABSTRACT:

Objective

To assess the single site performance of the Dynamic Criticality Index (CI-D) models developed from a multi-institutional database to predict future care. Secondarily, to assess future care-location predictions in a single institution when CI-D models are re-developed using single-site data with identical variables and modeling methods. Four CI-D models were assessed for predicting care locations >6-12 hours, >12-18 hours, >18-24 hours, and >24-30 hours in the future.

Design

Prognostic study comparing multi-institutional CI-D models' performance in a single-site electronic health record dataset to an institution-specific CI-D model developed using identical variables and modelling methods. The institution did not participate in the multi-institutional dataset.

P

SUBMITTER: Patel AK 

PROVIDER: S-EPMC10824440 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature