EHRtemporalVariability: delineating temporal data-set shifts in electronic health records.

ABSTRACT:

Background

Temporal variability in health-care processes or protocols is intrinsic to medicine. Such variability can potentially introduce dataset shifts, a data quality issue when reusing electronic health records (EHRs) for secondary purposes. Temporal data-set shifts can present as trends, as well as abrupt or seasonal changes in the statistical distributions of data over time. The latter are particularly complicated to address in multimodal and highly coded data. These changes, if not delineated, can harm population and data-driven research, such as machine learning. Given that biomedical research repositories are increasingly being populated with large sets of historical data from EHRs, there is a need for specific software methods to help delineate temporal data-set shifts to

SUBMITTER: Saez C 

PROVIDER: S-EPMC7391413 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature