title: Monitoring quality of health care with relational patterns.
abstract: This paper describes the extraction of relational patterns from hospital discharge data for the purpose of monitoring the quality of health care. We discuss what relational patterns are and how they support the extraction of meaningful patterns from data that are expressive, comprehensive, and easy to interpret. We demonstrate how relational patterns can be applied to identify poor practices embedded in hospitalization processes, for instance, help trigger subsequent inquiries and support decision-making processes.
authors.affiliation: Department of Information Systems, Leonard N. Stern School of Business, New York University, New York City, New York, USA.
authors.forename: M
authors.initials: M
authors.lastname: Saar-Tsechansky
authors.forename: N
authors.initials: N
authors.lastname: Pliskin
authors.forename: G
authors.initials: G
authors.lastname: Rabinowitz
authors.forename: M
authors.initials: M
authors.lastname: Tsechansky
authors.forename: A
authors.initials: A
authors.lastname: Porath
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003628:Database Management Systems; D003661:Decision Support Techniques; D006801:Humans; D010351:Patient Discharge; D011785:Quality Assurance, Health Care; D014481:United States