Relational Data Model for the American College of Radiology Appropriateness Criteria
Identifieur interne : 000012 ( Pmc/Corpus ); précédent : 000011; suivant : 000013Relational Data Model for the American College of Radiology Appropriateness Criteria
Auteurs : Chris L. Sistrom ; Janice C. HoneymanSource :
- Journal of Digital Imaging [ 0897-1889 ] ; 2002.
Abstract
This article describes a data model for encoding the American College of Radiology Appropriateness Criteria (ACRAC) for selection of diagnostic imaging procedures. These guidelines are recognized widely as an authoritative repository of "best evidence" concerning appropriate radiology tests for a large number of clinical conditions. In its current text document format, the ACRAC is of limited utility for electronic use. The data model the authors propose completely encodes all attributes and domains of the published guidelines and is suitable for translation into any industry standard relational database system. Additionally, the authors have added mappings onto commonly used procedure (CPT) and clinical problem (ICD) coding systems. When populated with the current ACRAC content, such a database could serve as the "master" repository of the guidelines with changes and additions made via an interface built with standard database application development tools. The database also could be made available for incorporation into existing information systems used for order entry, decision support, compliance tracking, and health services research at regional and national levels.
Url:
DOI: 10.1007/s10278-002-0018-3
PubMed: 12415465
PubMed Central: 3611619
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PMC:3611619Le document en format XML
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<author><name sortKey="Sistrom, Chris L" sort="Sistrom, Chris L" uniqKey="Sistrom C" first="Chris L." last="Sistrom">Chris L. Sistrom</name>
<affiliation><nlm:aff id="A">University of Florida School of Medicine, Gainesville, FL, , , , US</nlm:aff>
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<author><name sortKey="Honeyman, Janice C" sort="Honeyman, Janice C" uniqKey="Honeyman J" first="Janice C." last="Honeyman">Janice C. Honeyman</name>
<affiliation><nlm:aff id="A">University of Florida School of Medicine, Gainesville, FL, , , , US</nlm:aff>
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<author><name sortKey="Honeyman, Janice C" sort="Honeyman, Janice C" uniqKey="Honeyman J" first="Janice C." last="Honeyman">Janice C. Honeyman</name>
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<series><title level="j">Journal of Digital Imaging</title>
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<front><div type="abstract" xml:lang="en"><p>This article describes a data model for encoding the American College of Radiology Appropriateness Criteria (ACRAC) for selection of diagnostic imaging procedures. These guidelines are recognized widely as an authoritative repository of "best evidence" concerning appropriate radiology tests for a large number of clinical conditions. In its current text document format, the ACRAC is of limited utility for electronic use. The data model the authors propose completely encodes all attributes and domains of the published guidelines and is suitable for translation into any industry standard relational database system. Additionally, the authors have added mappings onto commonly used procedure (CPT) and clinical problem (ICD) coding systems. When populated with the current ACRAC content, such a database could serve as the "master" repository of the guidelines with changes and additions made via an interface built with standard database application development tools. The database also could be made available for incorporation into existing information systems used for order entry, decision support, compliance tracking, and health services research at regional and national levels.
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<pmc article-type="research-article"><pmc-comment>The publisher of this article does not allow downloading of the full text in XML form.</pmc-comment>
<front><journal-meta><journal-id journal-id-type="nlm-ta">J Digit Imaging</journal-id>
<journal-id journal-id-type="iso-abbrev">J Digit Imaging</journal-id>
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<title-group><article-title>Relational Data Model for the American College of Radiology Appropriateness Criteria
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<contrib-group><contrib contrib-type="author"><name><surname>Sistrom</surname>
<given-names>Chris L.</given-names>
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<contrib contrib-type="author"><name><surname>Honeyman</surname>
<given-names>Janice C.</given-names>
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<aff id="A">University of Florida School of Medicine, Gainesville, FL, , , , US</aff>
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<pub-date pub-type="epub"><day>6</day>
<month>11</month>
<year>2002</year>
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<pub-date pub-type="ppub"><month>12</month>
<year>2002</year>
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<volume>15</volume>
<issue>4</issue>
<fpage>216</fpage>
<lpage>225</lpage>
<permissions><copyright-statement>© 2002 SCAR (Society for Computer Applications in Radiol ogy)</copyright-statement>
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<abstract id="Abs1"><p>This article describes a data model for encoding the American College of Radiology Appropriateness Criteria (ACRAC) for selection of diagnostic imaging procedures. These guidelines are recognized widely as an authoritative repository of "best evidence" concerning appropriate radiology tests for a large number of clinical conditions. In its current text document format, the ACRAC is of limited utility for electronic use. The data model the authors propose completely encodes all attributes and domains of the published guidelines and is suitable for translation into any industry standard relational database system. Additionally, the authors have added mappings onto commonly used procedure (CPT) and clinical problem (ICD) coding systems. When populated with the current ACRAC content, such a database could serve as the "master" repository of the guidelines with changes and additions made via an interface built with standard database application development tools. The database also could be made available for incorporation into existing information systems used for order entry, decision support, compliance tracking, and health services research at regional and national levels.
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