Applications of network analysis to routinely collected health care data: a systematic review. (13th September 2017)

• Record Type: Journal Article
• Authors: Brunson, Jason Cory; Laubenbacher, Reinhard C
• Is Part Of: Journal of the American Medical Informatics Association. Volume 25:Number 2(2018)
• Page Start: 210
• Page End: 221
• Publication Date: 2017-09-13
• Subjects: network analysis -- graph theory -- secondary use -- administrative data -- EHR; Medical informatics -- Periodicals; Information Services -- Periodicals; Medical Informatics -- Periodicals; Médecine -- Informatique -- Périodiques; Informatica; Geneeskunde; Informatique médicale; Computer network resources; Electronic journals; 610.285
• DOI: 10.1093/jamia/ocx052
• Languages: English
• ISSNs: 1067-5027

Abstract

Abstract: Objective: To survey network analyses of datasets collected in the course of routine operations in health care settings and identify driving questions, methods, needs, and potential for future research. Materials and Methods: A search strategy was designed to find studies that applied network analysis to routinely collected health care datasets and was adapted to 3 bibliographic databases. The results were grouped according to a thematic analysis of their settings, objectives, data, and methods. Each group received a methodological synthesis. Results: The search found 189 distinct studies reported before August 2016. We manually partitioned the sample into 4 groups, which investigated institutional exchange, physician collaboration, clinical co-occurrence, and workplace interaction networks. Several robust and ongoing research programs were discerned within (and sometimes across) the groups. Little interaction was observed between these programs, despite conceptual and methodological similarities. Discussion: We use the literature sample to inform a discussion of good practice at this methodological interface, including the concordance of motivations, study design, data, and tools and the validation and standardization of techniques. We then highlight instances of positive feedback between methodological development and knowledge domains and assess the overall cohesion of the sample.