Lifting Hospital Electronic Health Record Data Treasures: Challenges and Opportunities.

ABSTRACT: Electronic health records (EHRs) have been successfully used in data science and machine learning projects. However, most of these data are collected for clinical use rather than for retrospective analysis. This means that researchers typically face many different issues when attempting to access and prepare the data for secondary use. We aimed to investigate how raw EHRs can be accessed and prepared in retrospective data science projects in a disciplined, effective, and efficient way. We report our experience and findings from a large-scale data science project analyzing routinely acquired retrospective data from the Kepler University Hospital in Linz, Austria. The project involved data collection from more than 150,000 patients over a period of 10 years. It included diverse data modaliti

SUBMITTER: Maletzky A 

PROVIDER: S-EPMC9636533 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature