An exploratory data quality analysis of time series physiologic signals using a large-scale intensive care unit database.

ABSTRACT: Physiological data, such as heart rate and blood pressure, are critical to clinical decision-making in the intensive care unit (ICU). Vital signs data, which are available from electronic health records, can be used to diagnose and predict important clinical outcomes; While there have been some reports on the data quality of nurse-verified vital sign data, little has been reported on the data quality of higher frequency time-series vital signs acquired in ICUs, that would enable such predictive modeling. In this study, we assessed the data quality issues, defined as the completeness, accuracy, and timeliness, of minute-by-minute time series vital signs data within the MIMIC-III data set, captured from 16009 patient-ICU stays and corresponding to 9410 unique adult patients. We measured data

SUBMITTER: Afshar AS 

PROVIDER: S-EPMC8327372 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature