title: Using a Clinical Knowledge Base to Assess Comorbidity Interrelatedness Among Patients with Multiple Chronic Conditions.
abstract: Decision support tools increasingly integrate clinical knowledge such as medication indications and contraindications with electronic health record (EHR) data to support clinical care and patient safety. The availability of this encoded information and patient data provides an opportunity to develop measures of clinical decision complexity that may be of value for quality improvement and research efforts. We investigated the feasibility of using encoded clinical knowledge and EHR data to develop a measure of comorbidity interrelatedness (the degree to which patients' co-occurring conditions interact to generate clinical complexity). Using a common clinical scenario-decisions about blood pressure medications in patients with hypertension-we quantified comorbidity interrelatedness by calculating the number of indications and contraindications to blood pressure medications that are generated by patients' comorbidities (e.g., diabetes, gout, depression). We examined properties of comorbidity interrelatedness using data from a decision support system for hypertension in the Veterans Affairs Health Care System.
authors.affiliation: Center for Innovation to Implementation, VA Palo Alto Health Care System, Menlo Park, CA; Division of General Medical Disciplines, Stanford University, Stanford, CA.
authors.forename: Donna M
authors.initials: DM
authors.lastname: Zulman
authors.affiliation: Geriatrics Research Education and Clinical Center (GRECC), VA Palo Alto Health Care System, Palo Alto, CA.
authors.forename: Susana B
authors.initials: SB
authors.lastname: Martins
authors.affiliation: Department of Biomedical, Industrial, and Human Factors Engineering, Wright State University, Dayton, OH.
authors.forename: Yan
authors.initials: Y
authors.lastname: Liu
authors.affiliation: Biomedical Informatics Research (BMIR), Stanford University School of Medicine, Stanford, CA.
authors.forename: Samson W
authors.initials: SW
authors.lastname: Tu
authors.affiliation: VA Boston Health Care System, West Roxbury Division, Boston, MA; Harvard Medical School, Boston, MA.
authors.forename: Brian B
authors.initials: BB
authors.lastname: Hoffman
authors.affiliation: Center for Innovation to Implementation, VA Palo Alto Health Care System, Menlo Park, CA; Division of General Medical Disciplines, Stanford University, Stanford, CA.
authors.forename: Steven M
authors.initials: SM
authors.lastname: Asch
authors.affiliation: Geriatrics Research Education and Clinical Center (GRECC), VA Palo Alto Health Care System, Palo Alto, CA; Center for Primary Care and Outcomes Research (PCOR), Stanford University School of Medicine, Stanford, CA.
authors.forename: Mary K
authors.initials: MK
authors.lastname: Goldstein
mesh_terms: D015897:Comorbidity; D003661:Decision Support Techniques; D003920:Diabetes Mellitus; D057286:Electronic Health Records; D006801:Humans; D051188:Knowledge Bases; D000071069:Multiple Chronic Conditions