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Quality Assessment Framework of Clinical Routine Data for Secondary Use.
Cheng, Ka Yung; Böhm, Ruwen; Bulin, Claudia; Jandok, Birgit; Schreiweis, Björn.
Afiliación
  • Cheng KY; Institute for Medical Informatics and Statistics, Kiel University and University Hospital Schleswig-Holstein, Campus Kiel, Germany.
  • Böhm R; Department of Radiation Oncology, Kiel University and University Hospital Schleswig-Holstein, Campus Kiel, Germany.
  • Bulin C; Institute of Experimental and Clinical Pharmacology, Kiel University and University Hospital Schleswig-Holstein, Campus Kiel, Germany.
  • Jandok B; Institute for Medical Informatics and Statistics, Kiel University and University Hospital Schleswig-Holstein, Campus Kiel, Germany.
  • Schreiweis B; Institute for Medical Informatics and Statistics, Kiel University and University Hospital Schleswig-Holstein, Campus Kiel, Germany.
Stud Health Technol Inform ; 316: 100-104, 2024 Aug 22.
Article en En | MEDLINE | ID: mdl-39176684
ABSTRACT
To systematically and comprehensively identify data issues in large clinical datasets, we adopted a harmonized data quality assessment framework with Python scripts before integrating the data into FHIR® for secondary use. We also added a preliminary step of categorizing data fields within the database scheme to facilitate the implementation of the data quality framework. As a result, we demonstrated the efficiency and comprehensiveness of detecting data issues using the framework. In future steps, we plan to continually utilize the framework to identify data issues and develop strategies for improving our data quality.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Exactitud de los Datos Límite: Humans Idioma: En Revista: Stud Health Technol Inform Asunto de la revista: INFORMATICA MEDICA / PESQUISA EM SERVICOS DE SAUDE Año: 2024 Tipo del documento: Article País de afiliación: Alemania Pais de publicación: Países Bajos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Exactitud de los Datos Límite: Humans Idioma: En Revista: Stud Health Technol Inform Asunto de la revista: INFORMATICA MEDICA / PESQUISA EM SERVICOS DE SAUDE Año: 2024 Tipo del documento: Article País de afiliación: Alemania Pais de publicación: Países Bajos