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

Digital Health Reviews (1883) Clinical Informatics (1503) Quality/Credibility of eHealth Information and Trust Issues (685) mHealth for Data Collection and Research (1290) Big Data (320) Electronic Health Records (1425) Quality Improvement (314) Health Care Quality and Health Services Research (372) Digital Health Reporting Standards, Quality and Transparency in e-Research (164) Health Information Governance (54)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/57615, first published .
Data Quality Dashboard showing charts and tables with business metrics.

Data Quality–Driven Improvement in Health Care: Systematic Literature Review

Data Quality–Driven Improvement in Health Care: Systematic Literature Review

Authors of this article:

Anthony Lighterness1 Author Orcid Image ;   Michael Adcock1 Author Orcid Image ;   Lauren Abigail Scanlon1 Author Orcid Image ;   Gareth Price2 Author Orcid Image
Article Authors Cited by (13) Tweetations Metrics

Journals

  1. Hubert P, Kasprzak J, Kazmaier L, Knaier L, Fey T, Heinemann V, Nasseh D. Is source data verification a valid tool to improve data quality of tumour documentation data? A critical assessment. Health Information Management Journal 2026;55(2):284 View
  2. Sanz Gómez S, Guija J, Giner L. Potential duplicate cases in the official suicide statistics reported by the Spanish National Statistics Institute (INE). Spanish Journal of Psychiatry and Mental Health 2025 View
  3. Azriani D, Agustian D, Zuhairini Y, Yulita I, Dhamayanti M. Prediction models for stunting at 2-years-old from Indonesian newborn population. BMC Pediatrics 2025;25(1) View
  4. Prybutok V, Prybutok G. Data-Driven Insights in Healthcare. Healthcare 2025;13(21):2658 View
  5. Wang J, Lin A, Huang Y, Li G, Chen T, Sun C, Qian W, Ren S, Wong H, Ding Y, Zhang L. Medical Data as a Key Asset in the Digital Health Era: A Framework for Challenges and Strategies. iMetaMed 2025;1(2) View
  6. Guillen-Aguinaga M, Aguinaga-Ontoso E, Guillen-Aguinaga L, Guillen-Grima F, Aguinaga-Ontoso I. Data Quality in the Age of AI: A Review of Governance, Ethics, and the FAIR Principles. Data 2025;10(12):201 View
  7. Brown S, Van Hemelrijck M, Price G, Oppong F, Verhoeff J, Faivre-Finn C. Novel methodologies for clinical research in radiation oncology: Time to think outside of the box? A narrative review. Radiotherapy and Oncology 2025:111311 View
  8. Arroyo-Ruales W, Soria-Poma X. Modelo de Inteligencia artificial para el diagnóstico del dengue. Revista Científica Ciencia y Método 2026;4(1):1 View
  9. Zhang Y, Li W, Zhang C, Wang Y, Feng S. Reforming hospital management education with the P-MASE pedagogy: a randomized controlled trial. BMC Medical Education 2026;26(1) View
  10. Choi Y, Kim J, Won J, Kim K, Kim Y, Choi W, Kim B, Yoo J, Chung N, Lee J, Kang H, Choi I, Lee H. Design and evaluation of an automated pediatric acute lymphoblastic leukemia registry from clinical data warehouses. BMC Medical Informatics and Decision Making 2026;26(1) View
  11. Kühnel B, Schneiderbauer S, Lange S, Wilhelm D, Friess H, Feith M, Ehmer U, Bassermann F, Holch J, Munker S, Neumann J, Werner J, Stein H, Fey T, Mansmann U, Algül H, Berger‐Thürmel K, Maurer H, Nasseh D. Development and Release of the Munich UICC Staging Tool (MUST): Advancing UICC Staging in Real‐World Data With Insights From Pancreatic and Stomach Cancer. International Journal of Cancer 2026 View
  12. Valdez-Ortiz R, Pedrero R, Jiménez E, Juárez J, Navarro Ramírez A, Romo Vázquez J, Sánchez B, Casas Aparicio G, Mendoza A, Muñoz Pérez P, Terán G, Madero M. Implementation of the AAMATES Platform as a National Registry for Stage 5 Chronic Kidney Disease in Mexico. Kidney Medicine 2026:101396 View
  13. Nagel E, Roman Y. Strengthening the evidence base for precision medicine through the utilization of real-world data and real-world evidence: a narrative review from the U.S. perspective. Personalized Medicine 2026:1 View