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A comprehensive framework for data quality assessment in CER

The panel addresses the urgent need to ensure that comparative effectiveness research (CER) findings derived from diverse and distributed data sources are based on credible, high-quality data; and that the methods used to assess and report data quality are consistent, comprehensive, and available to...

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Detalles Bibliográficos
Autores principales: Holve, Erin, Kahn, Michael, Nahm, Meredith, Ryan, Patrick, Weiskopf, Nicole
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Informatics Association 201
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3845781/
https://www.ncbi.nlm.nih.gov/pubmed/24303241
Descripción
Sumario:The panel addresses the urgent need to ensure that comparative effectiveness research (CER) findings derived from diverse and distributed data sources are based on credible, high-quality data; and that the methods used to assess and report data quality are consistent, comprehensive, and available to data consumers. The panel consists of representatives from four teams leveraging electronic clinical data for CER, patient centered outcomes research (PCOR), and quality improvement (QI) and seeks to change the current paradigm where data quality assessment (DQA) is performed “behind the scenes” using one-off project specific methods. The panelists will present their process of harmonizing existing models for describing and measuring clinical data quality and will describe a comprehensive integrated framework for assessing and reporting DQA findings. The collaborative project is supported by the Electronic Data Methods (EDM) Forum, a three-year grant from the Agency for Healthcare Research and Quality (AHRQ) to facilitate learning and foster collaboration across a set of CER, PCOR, and QI projects designed to build infrastructure and methods for collecting and analyzing prospective data from electronic clinical data .