title: Searching electronic health records for temporal patterns in patient histories: a case study with microsoft amalga.
abstract: As electronic health records (EHR) become more widespread, they enable clinicians and researchers to pose complex queries that can benefit immediate patient care and deepen understanding of medical treatment and outcomes. However, current query tools make complex temporal queries difficult to pose, and physicians have to rely on computer professionals to specify the queries for them. This paper describes our efforts to develop a novel query tool implemented in a large operational system at the Washington Hospital Center (Microsoft Amalga, formerly known as Azyxxi). We describe our design of the interface to specify temporal patterns and the visual presentation of results, and report on a pilot user study looking for adverse reactions following radiology studies using contrast.
authors.affiliation: Human-Computer Interaction Lab,University of Maryland, MD,USA.
authors.forename: Catherine
authors.initials: C
authors.lastname: Plaisant
authors.forename: Stanley
authors.initials: S
authors.lastname: Lam
authors.forename: Stanley J
authors.initials: SJ
authors.lastname: Lam
authors.forename: Ben
authors.initials: B
authors.lastname: Shneiderman
authors.forename: Mark S
authors.initials: MS
authors.lastname: Smith
authors.forename: David
authors.initials: D
authors.lastname: Roseman
authors.forename: David H
authors.initials: DH
authors.lastname: Roseman
authors.forename: Greg
authors.initials: G
authors.lastname: Marchand
authors.forename: Michael
authors.initials: M
authors.lastname: Gillam
authors.forename: Craig
authors.initials: C
authors.lastname: Feied
authors.forename: Jonathan
authors.initials: J
authors.lastname: Handler
authors.forename: Hank
authors.initials: H
authors.lastname: Rappaport
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D004219:District of Columbia; D016247:Information Storage and Retrieval / Q000379:methods*; D008487:Medical History Taking / Q000379:methods*; D016347:Medical Records Systems, Computerized; D009323:Natural Language Processing; D010363:Pattern Recognition, Automated / Q000379:methods*; D012984:Software; D013358:Subject Headings; D013997:Time Factors; D014481:United States