Informative missingness: What can we learn from patterns in missing laboratory data in the electronic health record?

ABSTRACT:

Background

In electronic health records, patterns of missing laboratory test results could capture patients' course of disease as well as ​​reflect clinician's concerns or worries for possible conditions. These patterns are often understudied and overlooked. This study aims to identify informative patterns of missingness among laboratory data collected across 15 healthcare system sites in three countries for COVID-19 inpatients.

Methods

We collected and analyzed demographic, diagnosis, and laboratory data for 69,939 patients with positive COVID-19 PCR tests across three countries from 1 January 2020 through 30 September 2021. We analyzed missing laboratory measurements across sites, missingness stratification by demographic variables, temporal trends of missingness, correlat

SUBMITTER: Tan ALM 

PROVIDER: S-EPMC10849195 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature