Using automated electronic medical record data extraction to model ALS survival and progression.

ABSTRACT:

Background

To assess the feasibility of using automated capture of Electronic Medical Record (EMR) data to build predictive models for amyotrophic lateral sclerosis (ALS) outcomes.

Methods

We used an Informatics for Integrating Biology and the Bedside search discovery tool to identify and extract data from 354 ALS patients from the University of Kansas Medical Center EMR. The completeness and integrity of the data extraction were verified by manual chart review. A linear mixed model was used to model disease progression. Cox proportional hazards models were used to investigate the effects of BMI, gender, and age on survival.

Results

Data extracted from the EMR was sufficient to create simple models of disease progression and survival. Several key variables of interest

SUBMITTER: Karanevich AG 

PROVIDER: S-EPMC6295028 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature