Pivovarov Rimma, Coppleson Yael Judith, Gorman Sharon Lipsky, Vawdrey David K, Elhadad Noémie
Value Institute, NewYork-Presbyterian Hospital, New York, NY.
Department of Biomedical Informatics, Columbia University, New York, NY.
AMIA Annu Symp Proc. 2017 Feb 10;2016:1020-1029. eCollection 2016.
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.
我们开展了一项干预前后的研究，将通用型患者记录汇总工具HARVEST引入了十位数据提取专家。这些专家每月负责审查数百份患者病历，并向各种在线登记处和数据库报告特定疾病的质量指标。我们对HARVEST是否改进了质量指标提取过程进行了定性和定量调查。研究工具包括干预前后的问卷以及对专家在电子健康记录（EHR）中的操作进行日志分析。专家们对HARVEST给出了积极评价，并表示在从住院时间长的患者中提取指标以及从EHR中未以结构化方式一致捕获的指标时，该工具最为有用。在50%的专家中观察到使用HARVEST前后每份病历花费时间有统计学意义的减少，并且90%的专家在研究期后仍继续使用HARVEST。
