@inproceedings{c7e1e088861d4facb4852400dcaa68ba,
title = "Availability of Structured Data Elements in Electronic Health Records for Supporting Patient Recruitment in Clinical Trials",
abstract = "Automated identification of eligible patients for clinical trials is an evident secondary use for electronic health records (EHR) data accumulated during routine care. This task requires relevant data elements to be both available in the EHR and in a structured form. This work analyzes these data quality dimensions of EHR data elements corresponding to a selection of frequent eligibility criteria over a total of 436 patient records at 10 university hospitals within the MIRACUM consortium. Data elements from demographics, diagnosis and laboratory findings are typically structured with a completeness of 73 \% to 88 \% while medication as well as procedures are rather untructured with a completeness of only 44 \%. The results can be used to derive suggestions for data quality improvement measures with respect to patient recruitment as well as to serve as a baseline to quantify future developments.",
keywords = "Data Accuracy, Electronic Health Records, Patient Selection",
author = "Albert Vass and Ines Reinecke and Martin Boeker and Prokosch, \{Hans Ulrich\} and Christian Gulden",
note = "Publisher Copyright: {\textcopyright} 2022 International Medical Informatics Association (IMIA) and IOS Press.; 18th World Congress on Medical and Health Informatics: One World, One Health - Global Partnership for Digital Innovation, MEDINFO 2021 ; Conference date: 02-10-2021 Through 04-10-2021",
year = "2022",
month = jun,
day = "6",
doi = "10.3233/SHTI220046",
language = "English",
series = "Studies in Health Technology and Informatics",
publisher = "IOS Press BV",
pages = "130--134",
editor = "Paula Otero and Philip Scott and Martin, \{Susan Z.\} and Elaine Huesing",
booktitle = "MEDINFO 2021",
}