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Creating a Medication Therapy Observational Research Database from an Electronic Medical Record: Challenges and Data Curation.
Rödle, Wolfgang; Prokosch, Hans-Ulrich; Neumann, Eva; Toni, Irmgard; Haering-Zahn, Julia; Neubert, Antje; Eberl, Sonja.
Affiliation
  • Rödle W; Chair of Medical Informatics, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany.
  • Prokosch HU; Chair of Medical Informatics, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany.
  • Neumann E; Dr Margarete Fischer Bosch Institute of Clinical Pharmacology, Stuttgart, Germany.
  • Toni I; Departmant of Paediatrics and Adolescent Medicine, Universitätsklinikum Erlangen, Erlangen, Germany.
  • Haering-Zahn J; Departmant of Paediatrics and Adolescent Medicine, Universitätsklinikum Erlangen, Erlangen, Germany.
  • Neubert A; Departmant of Paediatrics and Adolescent Medicine, Universitätsklinikum Erlangen, Erlangen, Germany.
  • Eberl S; Departmant of Paediatrics and Adolescent Medicine, Universitätsklinikum Erlangen, Erlangen, Germany.
Appl Clin Inform ; 15(1): 111-118, 2024 01.
Article in En | MEDLINE | ID: mdl-38325408
ABSTRACT

BACKGROUND:

Observational research has shown its potential to complement experimental research and clinical trials by secondary use of treatment data from hospital care processes. It can also be applied to better understand pediatric drug utilization for establishing safer drug therapy. Clinical documentation processes often limit data quality in pediatric medical records requiring data curation steps, which are mostly underestimated.

OBJECTIVES:

The objectives of this study were to transform and curate data from a departmental electronic medical record into an observational research database. We particularly aim at identifying data quality problems, illustrating reasons for such problems and describing the systematic data curation process established to create high-quality data for observational research.

METHODS:

Data were extracted from an electronic medical record used by four wards of a German university children's hospital from April 2012 to June 2020. A four-step data preparation, mapping, and curation process was established. Data quality of the generated dataset was firstly assessed following an established 3 × 3 Data Quality Assessment guideline and secondly by comparing a sample subset of the database with an existing gold standard.

RESULTS:

The generated dataset consists of 770,158 medication dispensations associated with 89,955 different drug exposures from 21,285 clinical encounters. A total of 6,840 different narrative drug therapy descriptions were mapped to 1,139 standard terms for drug exposures. Regarding the quality criterion correctness, the database was consistent and had overall a high agreement with our gold standard.

CONCLUSION:

Despite large amounts of freetext descriptions and contextual knowledge implicitly included in the electronic medical record, we were able to identify relevant data quality issues and to establish a semi-automated data curation process leading to a high-quality observational research database. Because of inconsistent dosage information in the original documentation this database is limited to a drug utilization database without detailed dosage information.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Electronic Health Records / Data Curation Type of study: Guideline / Observational_studies / Prognostic_studies Limits: Child / Humans Language: En Journal: Appl Clin Inform Year: 2024 Type: Article Affiliation country: Germany

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Electronic Health Records / Data Curation Type of study: Guideline / Observational_studies / Prognostic_studies Limits: Child / Humans Language: En Journal: Appl Clin Inform Year: 2024 Type: Article Affiliation country: Germany