High resolution data modifies intensive care unit dialysis outcome predictions as compared with low resolution administrative data set.

ABSTRACT: High resolution clinical databases from electronic health records are increasingly being used in the field of health data science. Compared to traditional administrative databases and disease registries, these newer highly granular clinical datasets offer several advantages, including availability of detailed clinical information for machine learning and the ability to adjust for potential confounders in statistical models. The purpose of this study is to compare the analysis of the same clinical research question using an administrative database and an electronic health record database. The Nationwide Inpatient Sample (NIS) was used for the low-resolution model, and the eICU Collaborative Research Database (eICU) was used for the high-resolution model. A parallel cohort of patients admitt

SUBMITTER: Ziegler J 

PROVIDER: S-EPMC9931257 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature