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Read Code Quality Assurance

Read Code Quality Assurance AbstractAs controlled clinical vocabularies assume an increasing role in modern clinical information systems, so the issue of their quality demands greater attention. In order to meet the resulting stringent criteria for completeness and correctness, a quality assurance system comprising a database of more than 500 rules is being developed and applied to the Read Thesaurus. The authors discuss the requirement to apply quality assurance processes to their dynamic editing database in order to ensure the quality of exported products. Sources of errors include human, hardware, and software factors as well as new rules and transactions. The overall quality strategy includes prevention, detection, and correction of errors. The quality assurance process encompasses simple data specification, internal consistency, inspection procedures and, eventually, field testing. The quality assurance system is driven by a small number of tables and UNIX scripts, with “business rules” declared explicitly as Structured Query Language (SQL) statements. Concurrent authorship, client-server technology, and an initial failure to implement robust transaction control have all provided valuable lessons. The feedback loop for error management needs to be short. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of the American Medical Informatics Association Oxford University Press

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Publisher
Oxford University Press
Copyright
American Medical Informatics Association
ISSN
1067-5027
eISSN
1527-974X
DOI
10.1136/jamia.1998.0050337
Publisher site
See Article on Publisher Site

Abstract

AbstractAs controlled clinical vocabularies assume an increasing role in modern clinical information systems, so the issue of their quality demands greater attention. In order to meet the resulting stringent criteria for completeness and correctness, a quality assurance system comprising a database of more than 500 rules is being developed and applied to the Read Thesaurus. The authors discuss the requirement to apply quality assurance processes to their dynamic editing database in order to ensure the quality of exported products. Sources of errors include human, hardware, and software factors as well as new rules and transactions. The overall quality strategy includes prevention, detection, and correction of errors. The quality assurance process encompasses simple data specification, internal consistency, inspection procedures and, eventually, field testing. The quality assurance system is driven by a small number of tables and UNIX scripts, with “business rules” declared explicitly as Structured Query Language (SQL) statements. Concurrent authorship, client-server technology, and an initial failure to implement robust transaction control have all provided valuable lessons. The feedback loop for error management needs to be short.

Journal

Journal of the American Medical Informatics AssociationOxford University Press

Published: Jul 1, 1998

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