title: Can Patient Record Summarization Support Quality Metric Abstraction?
abstract: We present a pre/post intervention study, where HARVEST, a general-purpose patient record summarization tool, was introduced to ten data abstraction specialists. The specialists are responsible for reviewing hundreds of patient charts each month and reporting disease-specific quality metrics to a variety of online registries and databases. We qualitatively and quantitatively investigated whether HARVEST improved the process of quality metric abstraction. Study instruments included pre/post questionnaires and log analyses of the specialists' actions in the electronic health record (EHR). The specialists reported favorable impressions of HARVEST and suggested that it was most useful when abstracting metrics from patients with long hospitalizations and for metrics that were not consistently captured in a structured manner in the EHR. A statistically significant reduction in time spent per chart before and after use of HARVEST was observed for 50% of the specialists and 90% of the specialists continue to use HARVEST after the study period.
authors.affiliation: Value Institute, NewYork-Presbyterian Hospital, New York, NY.
authors.forename: Rimma
authors.initials: R
authors.lastname: Pivovarov
authors.affiliation: Value Institute, NewYork-Presbyterian Hospital, New York, NY.
authors.forename: Yael Judith
authors.initials: YJ
authors.lastname: Coppleson
authors.affiliation: Department of Biomedical Informatics, Columbia University, New York, NY.
authors.forename: Sharon Lipsky
authors.initials: SL
authors.lastname: Gorman
authors.affiliation: Value Institute, NewYork-Presbyterian Hospital, New York, NY; Department of Biomedical Informatics, Columbia University, New York, NY.
authors.forename: David K
authors.initials: DK
authors.lastname: Vawdrey
authors.affiliation: Department of Biomedical Informatics, Columbia University, New York, NY.
authors.forename: Noémie
authors.initials: N
authors.lastname: Elhadad
mesh_terms: D000043:Abstracting and Indexing; D001291:Attitude of Health Personnel; D001292:Attitude to Computers; D057286:Electronic Health Records / Q000458:organization & administration*; D006801:Humans; D016247:Information Storage and Retrieval; D010564:Personnel, Hospital; D011787:Quality of Health Care; D012042:Registries; D011795:Surveys and Questionnaires; D014584:User-Computer Interface