title: Relational data model for the American College of Radiology Appropriateness Criteria.
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.
authors.affiliation: Department of Radiology, University of Florida School of Medicine, PO Box 100374, Gainesville, FL 32610, USA. sistromc@xray.ufl.edu
authors.forename: Chris L
authors.initials: CL
authors.lastname: Sistrom
authors.forename: Janice C
authors.initials: JC
authors.lastname: Honeyman
mesh_terms: D016208:Databases, Factual; D003658:Decision Making, Computer-Assisted; D003952:Diagnostic Imaging / Q000706:statistics & numerical data*; D006801:Humans; D017410:Practice Guidelines as Topic; D012955:Societies, Medical; D014481:United States