A randomized controlled trial of the accuracy of clinical record retrieval using SNOMED-RT as compared with ICD9-CM.

BACKGROUND: Concept-based Indexing is purported to provide more granular data representation for clinical records.1,2 This implies that a detailed clinical terminology should be able to provide improved access to clinical records. To date there is no data to show that a clinical reference terminology is superior to a precoordinated terminology in its ability to provide access to the clinical record. Today, ICD9-CM is the most commonly used method of retrieving clinical records. OBJECTIVE: In this study, we compare the sensitivity, specificity, positive likelihood ratio, positive predictive value and accuracy of SNOMED-RT vs. ICD9-CM in retrieving ten diagnoses from a random sample of 2,022 episodes of care. METHOD: We randomly selected 1,014 episodes of care from the inpatient setting and 1,008 episodes of care from the outpatient setting. Each record had associated with it, the free text final diagnoses from the Master Sheet Index at the Mayo Clinic and the ICD9-CM codes used to bill for the encounters within the episode of care. The free text diagnoses were coded by two expert indexers (disagreements were addressed by a Staff Clinician) as to whether queries regarding one of 5 common or 5 uncommon diagnoses should return this encounter. The free text entries were automatically coded using the Mayo Vocabulary Processor. Each of the ten diagnoses was exploded in both SNOMED-RT and ICD9-CM and using these entry points, a retrieval set was generated from the underlying corpus of records. Each retrieval set was compared with the Gold Standard created by the expert indexers. RESULTS: SNOMED-RT produced significantly greater specificity in its retrieval sets (99.8% vs. 98.3%, p<0.001 McNemar Test). The positive likelihood ratios were significantly better for SNOMED-RT retrieval sets (264.9 vs. 33.8, p<0.001 McNemar Test). The positive predictive value of a SNOMED-RT retrieval was also significantly better than ICD9-CM (92.9% vs. 62.4%, p<0.001 McNemar Test). The accuracy defined as 1 (the total error rate (FP+FN) / Total # episodes queried (20,220)) was significantly greater for SNOMED-RT (98.2% vs. 96.8%, p=0.002 McNemar Test). Interestingly, the sensitivity of the SNOMED-RT generated retrieval set was not significantly different from ICD9-CM, but there was a trend toward significance (60.4% vs. 57.6%, p=0.067 McNemar Test). However, if we examine only the outpatient practice SNOMED-RT produced a more sensitive retrieval set than ICD9-CM (54.8% vs. 46.4%, p=0.002 McNemar Test). CONCLUSIONS: Our data clearly shows that information regarding both common and rare disorders is more accurately identified with automated SNOMED-RT indexing using the Mayo Vocabulary Processor than it is with traditional hand picked constellations of codes using ICD9-CM. SNOMED-RT provided more sensitive retrievals of outpatient episodes of care than ICD9-CM.

Expression of a domain ontology model in unified modeling language for the World Health Organization International classification of impairment, disability, and handicap, version 2.

The International Classification of Impairment, Disability, and Handicap Version 2(ICIDH-2), an anticipated addition to the World Health Organization suite of terminologies, has been put forth as a means for standardized representation of generic health and/or functional status data. In an attempt to make explicit the ontology upon which ICIDH-2 is based the authors derived a concept model expressed as a Unified Modeling Language static class diagram through abstraction of concept-terms in the documentation provided with the Full Version Pre-Final Draft of ICIDH-2 (December 2000). ICIDH-2's semantic structure is analyzed and evaluated for its semantic consistency. Discussion is presented on the utility of domain ontology models in terminology development and potential roles ICIDH-2 might play, as it undergoes refinement towards a representational standard. It is intended that the proposed UML rendering will stimulate domain discourse and consensus that will lead to enhancement of conceptual clarity in the ICIDH-2 ontological hierarchy and further enable its study and development as a healthcare classification.

Representation by standard terminologies of health status concepts contained in two health status assessment instruments used in rheumatic disease management.

Health and functional status data have been shown to have clinical utility in predicting outcome. Various metadata registries in the form of patient self-administered health assessment questionnaires have been incorporated into routine clinical care and clinical research of patients with rheumatic disease. Examples of such health assessment instruments are the Clinical Health Assessment Questionnaire (CLINHAQ) and the Modified Health Assessment Questionnaire (MHAQ). These instruments contain concepts that are an integral part of the health and functional status domain. Using an automated indexing tool we examined the clinical content coverage by SNOMED RT and the Unified Medical Language System (UMLS) Metathesaurus for health and functional status concepts identified in the MHAQ and CLINHAQ. Significant differences existed between the overall representational ability of SNOMED and UMLS for concepts identified in the MHAQ (49%, vs. 77% respectively, p < .005) and for concepts identified in the CLINHAQ (30% vs. 64% respectively p < .005). Representational capability by SNOMED-RT and UMLS for concepts in a given health assessment instrument was carried across four semantic classes of "attitudes", "symptoms", "activities", and "social attributes". The conceptual content coverage of health status assessment concepts contained in the MHAQ and CLINHAQ by SNOMED-RT and UMLS was incomplete but better for UMLS with its panoply of vocabulary sources. This observed overall improved representation by UMLS appeared to be due to better representation of concepts in "activities" and "social attributes" semantic classes. Representation of health or functional status concepts in a computerized medical record should be founded on a universally agreed concept model of that domain. Established functional and health status metadata registries can serve as important sources for concepts and candidate classes within that domain.

Common variable immune deficiency syndrome associated with lupus anticoagulant.

A patient with an acquired immune deficiency syndrome developed a lupus anticoagulant in which the inhibitory activity was manifested only as a prolongation of the partial thromboplastin time. Contrary to previous reports, the substitution of platelets or platelet sonicates for phospholipid in this coagulant assay failed to correct the abnormality and the inhibitor did not exhibit immunoreactivity against phospholipids. The possible mechanisms of action of these inhibitors are discussed.