Parameterizing time in electronic health record studies.

ABSTRACT:

Background

Fields like nonlinear physics offer methods for analyzing time series, but many methods require that the time series be stationary-no change in properties over time.Objective Medicine is far from stationary, but the challenge may be able to be ameliorated by reparameterizing time because clinicians tend to measure patients more frequently when they are ill and are more likely to vary.

Methods

We compared time parameterizations, measuring variability of rate of change and magnitude of change, and looking for homogeneity of bins of temporal separation between pairs of time points. We studied four common laboratory tests drawn from 25 years of electronic health records on 4 million patients.

Results

We found that sequence time-that is, simply counting the numb

SUBMITTER: Hripcsak G 

PROVIDER: S-EPMC6169471 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature