Replicating medication trend studies using ad hoc information extraction in a clinical data warehouse

Please always quote using this URN: urn:nbn:de:bvb:20-opus-200409
  • Background Medication trend studies show the changes of medication over the years and may be replicated using a clinical Data Warehouse (CDW). Even nowadays, a lot of the patient information, like medication data, in the EHR is stored in the format of free text. As the conventional approach of information extraction (IE) demands a high developmental effort, we used ad hoc IE instead. This technique queries information and extracts it on the fly from texts contained in the CDW. Methods We present a generalizable approach of ad hoc IE forBackground Medication trend studies show the changes of medication over the years and may be replicated using a clinical Data Warehouse (CDW). Even nowadays, a lot of the patient information, like medication data, in the EHR is stored in the format of free text. As the conventional approach of information extraction (IE) demands a high developmental effort, we used ad hoc IE instead. This technique queries information and extracts it on the fly from texts contained in the CDW. Methods We present a generalizable approach of ad hoc IE for pharmacotherapy (medications and their daily dosage) presented in hospital discharge letters. We added import and query features to the CDW system, like error tolerant queries to deal with misspellings and proximity search for the extraction of the daily dosage. During the data integration process in the CDW, negated, historical and non-patient context data are filtered. For the replication studies, we used a drug list grouped by ATC (Anatomical Therapeutic Chemical Classification System) codes as input for queries to the CDW. Results We achieve an F1 score of 0.983 (precision 0.997, recall 0.970) for extracting medication from discharge letters and an F1 score of 0.974 (precision 0.977, recall 0.972) for extracting the dosage. We replicated three published medical trend studies for hypertension, atrial fibrillation and chronic kidney disease. Overall, 93% of the main findings could be replicated, 68% of sub-findings, and 75% of all findings. One study could be completely replicated with all main and sub-findings. Conclusion A novel approach for ad hoc IE is presented. It is very suitable for basic medical texts like discharge letters and finding reports. Ad hoc IE is by definition more limited than conventional IE and does not claim to replace it, but it substantially exceeds the search capabilities of many CDWs and it is convenient to conduct replication studies fast and with high quality.show moreshow less

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Metadaten
Author: Georg Dietrich, Jonathan Krebs, Leon Liman, Georg Fette, Maximilian Ertl, Mathias Kaspar, Stefan Störk, Frank Puppe
URN:urn:nbn:de:bvb:20-opus-200409
Document Type:Journal article
Faculties:Fakultät für Mathematik und Informatik / Institut für Informatik
Medizinische Fakultät / Medizinische Klinik und Poliklinik I
Language:English
Parent Title (English):BMC Medical Informatics and Decision Making
Year of Completion:2019
Volume:19
Pagenumber:15
Source:BMC Medical Informatics and Decision Making (2019) 19:15 https://doi.org/10.1186/s12911-018-0729-0
DOI:https://doi.org/10.1186/s12911-018-0729-0
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Tag:data warehouse; information extraction; medication extraction
Release Date:2020/05/15
Collections:Open-Access-Publikationsfonds / Förderzeitraum 2019
Licence (German):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International