BACKGROUND: Establishing a relationship between medications and diagnoses within a functioning electronic medical record system (EMR) has many valuable applications,such as improving the quality and utility of the problem list to support better decisions. METHODS: We evaluated over 1.6 million de-identified patient records from the Regenstrief Medical Record System (RMRS) with over 90 million diagnoses and 20 million medications. Using RxNorm, the VA National Drug File Reference Terminology, and SNOMED-CT (SCT)standard terminologies and mappings we evaluated the linkage for local concept terms for medications and problems (diagnoses & complaints). RESULTS: We were able to map 24,398 candidates as medication and indication pairs. The overall sensitivity and specificity for term pairs was 67.5% and 86% respectively and 39.5% and 97.4 when adjusted for term pair occurrence within single patient records. CONCLUSIONS: Medications can be mapped by machine to a disease/ disorder using established terminology standards.This mapping may inform many knowledge management and decision support features in an EMR.
BACKGROUND: Establishing a relationship between medications and diagnoses within a functioning electronic medical record system (EMR) has many valuable applications,such as improving the quality and utility of the problem list to support better decisions. METHODS: We evaluated over 1.6 million de-identified patient records from the Regenstrief Medical Record System (RMRS) with over 90 million diagnoses and 20 million medications. Using RxNorm, the VA National Drug File Reference Terminology, and SNOMED-CT (SCT)standard terminologies and mappings we evaluated the linkage for local concept terms for medications and problems (diagnoses & complaints). RESULTS: We were able to map 24,398 candidates as medication and indication pairs. The overall sensitivity and specificity for term pairs was 67.5% and 86% respectively and 39.5% and 97.4 when adjusted for term pair occurrence within single patient records. CONCLUSIONS: Medications can be mapped by machine to a disease/ disorder using established terminology standards.This mapping may inform many knowledge management and decision support features in an EMR.
Authors: C J McDonald; J M Overhage; W M Tierney; P R Dexter; D K Martin; J G Suico; A Zafar; G Schadow; L Blevins; T Glazener; J Meeks-Johnson; L Lemmon; J Warvel; B Porterfield; J Warvel; P Cassidy; D Lindbergh; A Belsito; M Tucker; B Williams; C Wodniak Journal: Int J Med Inform Date: 1999-06 Impact factor: 4.046
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Authors: Adam Wright; Justine Pang; Joshua C Feblowitz; Francine L Maloney; Allison R Wilcox; Harley Z Ramelson; Louise I Schneider; David W Bates Journal: J Am Med Inform Assoc Date: 2011-05-25 Impact factor: 4.497