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A Framework and Standardized Methodology for Developing Minimum Clinical Datasets

The concept of the minimum dataset (MDS) is taking on an increasingly important role in healthcare. In the current environment of health information exchange and universal implementation of electronic health records, work related to the development of one specific type of MDS, the minimum clinical d...

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Detalles Bibliográficos
Autores principales: Svensson-Ranallo, Piper A., Adam, Terrence J., Sainfort, François
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Informatics Association 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3248746/
https://www.ncbi.nlm.nih.gov/pubmed/22211180
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author Svensson-Ranallo, Piper A.
Adam, Terrence J.
Sainfort, François
author_facet Svensson-Ranallo, Piper A.
Adam, Terrence J.
Sainfort, François
author_sort Svensson-Ranallo, Piper A.
collection PubMed
description The concept of the minimum dataset (MDS) is taking on an increasingly important role in healthcare. In the current environment of health information exchange and universal implementation of electronic health records, work related to the development of one specific type of MDS, the minimum clinical dataset (MCDS), is beginning to permeate the literature. While there is currently no unified definition of either an MDS or an MCDS, an MDS is generally agreed to be a coherent set of explicitly defined data elements. Despite the growing body of literature on MCDSs, very little empirical evidence exists in the literature related to best methods for developing them. The primary objective of the current study is to fill this gap. By presenting a streamlined approach to the development of MCDSs the current study attempts to provide individuals and organizations with a coherent methodology and framework for developing a high quality MCDS.
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spelling pubmed-32487462011-12-30 A Framework and Standardized Methodology for Developing Minimum Clinical Datasets Svensson-Ranallo, Piper A. Adam, Terrence J. Sainfort, François AMIA Jt Summits Transl Sci Proc Articles The concept of the minimum dataset (MDS) is taking on an increasingly important role in healthcare. In the current environment of health information exchange and universal implementation of electronic health records, work related to the development of one specific type of MDS, the minimum clinical dataset (MCDS), is beginning to permeate the literature. While there is currently no unified definition of either an MDS or an MCDS, an MDS is generally agreed to be a coherent set of explicitly defined data elements. Despite the growing body of literature on MCDSs, very little empirical evidence exists in the literature related to best methods for developing them. The primary objective of the current study is to fill this gap. By presenting a streamlined approach to the development of MCDSs the current study attempts to provide individuals and organizations with a coherent methodology and framework for developing a high quality MCDS. American Medical Informatics Association 2011-03-07 /pmc/articles/PMC3248746/ /pubmed/22211180 Text en ©2011 AMIA - All rights reserved. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose
spellingShingle Articles
Svensson-Ranallo, Piper A.
Adam, Terrence J.
Sainfort, François
A Framework and Standardized Methodology for Developing Minimum Clinical Datasets
title A Framework and Standardized Methodology for Developing Minimum Clinical Datasets
title_full A Framework and Standardized Methodology for Developing Minimum Clinical Datasets
title_fullStr A Framework and Standardized Methodology for Developing Minimum Clinical Datasets
title_full_unstemmed A Framework and Standardized Methodology for Developing Minimum Clinical Datasets
title_short A Framework and Standardized Methodology for Developing Minimum Clinical Datasets
title_sort framework and standardized methodology for developing minimum clinical datasets
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3248746/
https://www.ncbi.nlm.nih.gov/pubmed/22211180
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