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Knowledgebase strategies to aid interpretation of clinical correlation research.
Stead, William W; Lewis, Adam; Giuse, Nunzia B; Koonce, Taneya Y; Bastarache, Lisa.
Afiliación
  • Stead WW; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
  • Lewis A; Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
  • Giuse NB; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
  • Koonce TY; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
  • Bastarache L; Center for Knowledge Management, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
J Am Med Inform Assoc ; 30(7): 1257-1265, 2023 06 20.
Article en En | MEDLINE | ID: mdl-37164621
OBJECTIVE: Knowledgebases are needed to clarify correlations observed in real-world electronic health record (EHR) data. We posit design principles, present a unifying framework, and report a test of concept. MATERIALS AND METHODS: We structured a knowledge framework along 3 axes: condition of interest, knowledge source, and taxonomy. In our test of concept, we used hypertension as our condition of interest, literature and VanderbiltDDx knowledgebase as sources, and phecodes as our taxonomy. In a cohort of 832 566 deidentified EHRs, we modeled blood pressure and heart rate by sex and age, classified individuals by hypertensive status, and ran a Phenome-wide Association Study (PheWAS) for hypertension. We compared the correlations from PheWAS to the associations in our knowledgebase. RESULTS: We produced PhecodeKbHtn: a knowledgebase comprising 167 hypertension-associated diseases, 15 of which were also negatively associated with blood pressure (pos+neg). Our hypertension PheWAS included 1914 phecodes, 129 of which were in the PhecodeKbHtn. Among the PheWAS association results, phecodes that were in PhecodeKbHtn had larger effect sizes compared with those phecodes not in the knowledgebase. DISCUSSION: Each source contributed unique and additive associations. Models of blood pressure and heart rate by age and sex were consistent with prior cohort studies. All but 4 PheWAS positive and negative correlations for phecodes in PhecodeKbHtn may be explained by knowledgebase associations, hypertensive cardiac complications, or causes of hypertension independently associated with hypotension. CONCLUSION: It is feasible to assemble a knowledgebase that is compatible with EHR data to aid interpretation of clinical correlation research.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Estudio de Asociación del Genoma Completo / Hipertensión Tipo de estudio: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Qualitative_research / Risk_factors_studies Límite: Humans Idioma: En Revista: J Am Med Inform Assoc Asunto de la revista: INFORMATICA MEDICA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido
Texto completo
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XML
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Estudio de Asociación del Genoma Completo / Hipertensión Tipo de estudio: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Qualitative_research / Risk_factors_studies Límite: Humans Idioma: En Revista: J Am Med Inform Assoc Asunto de la revista: INFORMATICA MEDICA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido