This paper is in the following e-collection/theme issue:

Reviews in Medical Informatics (106) Advanced Data Analytics in eHealth (196) eHealth Infrastructures (420) Health Information Exchange (132) Information Models (42) Methods and Instruments in Medical Informatics (179) Ontologies, Classifications, and Coding (309) Policy (74) Quality Improvement (286) Secondary Use of Clinical Data for Research and Surveillance (453) Standards and Interoperability (121)

Published on in Vol 12 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/51560, first published .
Frameworks, Dimensions, Definitions of Aspects, and Assessment Methods for the Appraisal of Quality of Health Data for Secondary Use: Comprehensive Overview of Reviews

Frameworks, Dimensions, Definitions of Aspects, and Assessment Methods for the Appraisal of Quality of Health Data for Secondary Use: Comprehensive Overview of Reviews

Frameworks, Dimensions, Definitions of Aspects, and Assessment Methods for the Appraisal of Quality of Health Data for Secondary Use: Comprehensive Overview of Reviews

Authors of this article:

Jens Declerck1, 2 Author Orcid Image ;   Dipak Kalra1, 2 Author Orcid Image ;   Robert Vander Stichele3 Author Orcid Image ;   Pascal Coorevits1 Author Orcid Image
Article Authors Cited by (9) Tweetations (2) Metrics

Journals

  1. Hussein R, Balaur I, Burmann A, Ćwiek-Kupczyńska H, Gadiya Y, Ghosh S, Jayathissa P, Katsch F, Kremer A, Lähteenmäki J, Meng Z, Morasek K, C. Rancourt R, Satagopam V, Sauermann S, Scheider S, Stamm T, Muehlendyck C, Gribbon P. Getting ready for the European Health Data Space (EHDS): IDERHA's plan to align with the latest EHDS requirements for the secondary use of health data. Open Research Europe 2024;4:160 View
  2. Schwabe D, Becker K, Seyferth M, Klaß A, Schaeffter T. The METRIC-framework for assessing data quality for trustworthy AI in medicine: a systematic review. npj Digital Medicine 2024;7(1) View
  3. Priou S, Kempf E, Jankovic M, Lamé G. “Goldmine” or “big mess”? An interview study on the challenges of designing, operating, and ensuring the durability of Clinical Data Warehouses in France and Belgium. Journal of the American Medical Informatics Association 2024;31(11):2699 View
  4. Declerck J, Vandenberk B, Deschepper M, Colpaert K, Cool L, Goemaere J, Bové M, Staelens F, De Meester K, Verbeke E, Smits E, De Decker C, Van Der Vekens N, Pauwels E, Vander Stichele R, Kalra D, Coorevits P. Building a Foundation for High-Quality Health Data: Multihospital Case Study in Belgium. JMIR Medical Informatics 2024;12:e60244 View
  5. Feige B, Benz F, Dressle R, Riemann D. About Digitalisation and AI, Data Protection, Data Exchange, Data Mining—Legal Constraints/Challenges Concerning Sleep Medicine. Journal of Sleep Research 2025;34(5) View
  6. Bouckley T, Myton-Katieva R, Peiris D, Nambiar D, Prince S, Bishop S, Cordery D, Hill F, Correll P, Feyer A, Schierhout G, Campain A. An assessment of data quality and sociodemographic variation in health service utilisation of general practice, emergency department and admitted services in a New South Wales linked health data asset: a retrospective cohort study of Lumos. BMJ Open 2025;15(7):e102055 View
  7. Hosseinzadeh E, Afkanpour M, Momeni M, Tabesh H. Data quality assessment in healthcare, dimensions, methods and tools: a systematic review. BMC Medical Informatics and Decision Making 2025;25(1) View
  8. Kim J, Hong D. Korea’s Bio Big Data Project: Importance and Challenges of Governance and Data Utilization. Healthcare Informatics Research 2025;31(3):226 View
  9. Nicholson N, Negrao Carvalho R, Štotl I. A FAIR Perspective on Data Quality Frameworks. Data 2025;10(9):136 View