title: Using Natural Language Processing and Network Analysis to Develop a Conceptual Framework for Medication Therapy Management Research.
abstract: This paper describes a theory derivation process used to develop a conceptual framework for medication therapy management (MTM) research. The MTM service model and chronic care model were selected as parent theories. Review article abstracts targeting medication therapy management in chronic disease care were retrieved from Ovid Medline (2000-2016). Unique concepts in each abstract were extracted using MetaMap and their pairwise cooccurrence determined. The information was used to construct a network graph of concept co-occurrence that was analyzed to identify content for the new conceptual model. 142 abstracts were analyzed. Medication adherence is the most studied drug therapy problem and co-occurred with concepts related to patient-centered interventions targeting self-management. The enhanced model consists of 65 concepts clustered into 14 constructs. The framework requires additional refinement and evaluation to determine its relevance and applicability across a broad audience including underserved settings.
authors.affiliation: department of Biomedical Informatics, Columbia University, New York.
authors.forename: William
authors.initials: W
authors.lastname: Ogallo
authors.affiliation: department of Biomedical Informatics, Columbia University, New York.
authors.forename: Andrew S
authors.initials: AS
authors.lastname: Kanter
mesh_terms: D035843:Biomedical Research; D002908:Chronic Disease / Q000188:drug therapy*; D006801:Humans; D055118:Medication Adherence; D054539:Medication Therapy Management; D009323:Natural Language Processing; D012648:Self Care