1
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      Neurological Dashboards and Consultation Turnaround Time at an Academic Medical Center

      research-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background  Neurologists perform a significant amount of consultative work. Aggregative electronic health record (EHR) dashboards may help to reduce consultation turnaround time (TAT) which may reflect time spent interfacing with the EHR.

          Objectives  This study was aimed to measure the difference in TAT before and after the implementation of a neurological dashboard.

          Methods  We retrospectively studied a neurological dashboard in a read-only, web-based, clinical data review platform at an academic medical center that was separate from our institutional EHR. Using our EHR, we identified all distinct initial neurological consultations at our institution that were completed in the 5 months before, 5 months after, and 12 months after the dashboard go-live in December 2017. Using log data, we determined total dashboard users, unique page hits, patient-chart accesses, and user departments at 5 months after go-live. We calculated TAT as the difference in time between the placement of the consultation order and completion of the consultation note in the EHR.

          Results  By April 30th in 2018, we identified 269 unique users, 684 dashboard page hits (median hits/user 1.0, interquartile range [IQR] = 1.0), and 510 unique patient-chart accesses. In 5 months before the go-live, 1,434 neurology consultations were completed with a median TAT of 2.0 hours (IQR = 2.5) which was significantly longer than during 5 months after the go-live, with 1,672 neurology consultations completed with a median TAT of 1.8 hours (IQR = 2.2; p  = 0.001). Over the following 7 months, 2,160 consultations were completed and median TAT remained unchanged at 1.8 hours (IQR = 2.5).

          Conclusion  At a large academic institution, we found a significant decrease in inpatient consult TAT 5 and 12 months after the implementation of a neurological dashboard. Further study is necessary to investigate the cognitive and operational effects of aggregative dashboards in neurology and to optimize their use.

          Related collections

          Author and article information

          Journal
          Appl Clin Inform
          Appl Clin Inform
          10.1055/s-00035026
          Applied Clinical Informatics
          Georg Thieme Verlag KG (Stuttgart · New York )
          1869-0327
          October 2019
          06 November 2019
          : 10
          : 5
          : 849-858
          Affiliations
          [1 ] Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, United States
          [2 ] Department of Neurology, Columbia University, New York, New York, United States
          [3 ] Department of Analytics, New York Presbyterian Hospital, New York, New York, United States
          [4 ] Department of Biomedical Informatics, Columbia University, New York, New York, United States
          [5 ] Department of Epidemiology, Columbia University Mailman School of Public Health, New York, New York, United States
          Author notes
          Address for correspondence Benjamin R. Kummer, MD Department of Neurology, Icahn School of Medicine at Mount Sinai 1 Gustave L Levy Place Annenberg Building, Suite Box 1137, New York, NY 10029 United States benjamin.kummer@ 123456mountsinai.org
          Article
          PMC6834453 PMC6834453 6834453 190116ra
          10.1055/s-0039-1698465
          6834453
          31694054
          ae8af25a-93c1-4990-bc65-e3d90c43b500
          © Thieme Medical Publishers
          History
          : 19 May 2019
          : 28 August 2019
          Categories
          Research Article

          clinical decision support systems,organizational efficiency,inpatients,data aggregation,neurology,referral and consultation

          Comments

          Comment on this article