Howard S Goldberg1, Marilyn D Paterno2, Robert W Grundmeier3, Beatriz H Rocha2, Jeffrey M Hoffman4, Eric Tham5, Marguerite Swietlik6, Molly H Schaeffer7, Deepika Pabbathi7, Sara J Deakyne8, Nathan Kuppermann9, Peter S Dayan10. 1. Division of General Internal Medicine, Brigham and Women's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA. Electronic address: hgoldberg@partners.org. 2. Division of General Internal Medicine, Brigham and Women's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA. 3. Center for Biomedical Informatics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA; Department of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA. 4. Department of Pediatrics, Section of Emergency Medicine, Nationwide Children's Hospital, Columbus, OH, USA; Ohio State University College of Medicine, Columbus, OH, USA. 5. Research Informatics, Seattle Children's Research Institute, Seattle, WA, USA; Department of Pediatrics, Children's Hospital Colorado, Aurora, CO, USA. 6. Department of Pediatrics, Children's Hospital Colorado, Aurora, CO, USA; University of Colorado, Denver, CO, USA. 7. Information Systems, Partners HealthCare System, Boston, MA, USA. 8. Research Informatics, Children's Hospital Colorado, Aurora, CO, USA. 9. Departments of Emergency Medicine and Pediatrics, University of California Davis School of Medicine, Sacramento, CA, USA. 10. Pediatrics, Division of Pediatric Emergency Medicine, Columbia University College of Physicians and Surgeons, New York, NY, USA.
Abstract
OBJECTIVE: To evaluate the architecture, integration requirements, and execution characteristics of a remote clinical decision support (CDS) service used in a multicenter clinical trial. The trial tested the efficacy of implementing brain injury prediction rules for children with minor blunt head trauma. MATERIALS AND METHODS: We integrated the Epic(®) electronic health record (EHR) with the Enterprise Clinical Rules Service (ECRS), a web-based CDS service, at two emergency departments. Patterns of CDS review included either a delayed, near-real-time review, where the physician viewed CDS recommendations generated by the nursing assessment, or a real-time review, where the physician viewed recommendations generated by their own documentation. A backstopping, vendor-based CDS triggered with zero delay when no recommendation was available in the EHR from the web-service. We assessed the execution characteristics of the integrated system and the source of the generated recommendations viewed by physicians. RESULTS: The ECRS mean execution time was 0.74 ±0.72 s. Overall execution time was substantially different at the two sites, with mean total transaction times of 19.67 and 3.99 s. Of 1930 analyzed transactions from the two sites, 60% (310/521) of all physician documentation-initiated recommendations and 99% (1390/1409) of all nurse documentation-initiated recommendations originated from the remote web service. DISCUSSION: The remote CDS system was the source of recommendations in more than half of the real-time cases and virtually all the near-real-time cases. Comparisons are limited by allowable variation in user workflow and resolution of the EHR clock. CONCLUSION: With maturation and adoption of standards for CDS services, remote CDS shows promise to decrease time-to-trial for multicenter evaluations of candidate decision support interventions.
OBJECTIVE: To evaluate the architecture, integration requirements, and execution characteristics of a remote clinical decision support (CDS) service used in a multicenter clinical trial. The trial tested the efficacy of implementing brain injury prediction rules for children with minor blunt head trauma. MATERIALS AND METHODS: We integrated the Epic(®) electronic health record (EHR) with the Enterprise Clinical Rules Service (ECRS), a web-based CDS service, at two emergency departments. Patterns of CDS review included either a delayed, near-real-time review, where the physician viewed CDS recommendations generated by the nursing assessment, or a real-time review, where the physician viewed recommendations generated by their own documentation. A backstopping, vendor-based CDS triggered with zero delay when no recommendation was available in the EHR from the web-service. We assessed the execution characteristics of the integrated system and the source of the generated recommendations viewed by physicians. RESULTS: The ECRS mean execution time was 0.74 ±0.72 s. Overall execution time was substantially different at the two sites, with mean total transaction times of 19.67 and 3.99 s. Of 1930 analyzed transactions from the two sites, 60% (310/521) of all physician documentation-initiated recommendations and 99% (1390/1409) of all nurse documentation-initiated recommendations originated from the remote web service. DISCUSSION: The remote CDS system was the source of recommendations in more than half of the real-time cases and virtually all the near-real-time cases. Comparisons are limited by allowable variation in user workflow and resolution of the EHR clock. CONCLUSION: With maturation and adoption of standards for CDS services, remote CDS shows promise to decrease time-to-trial for multicenter evaluations of candidate decision support interventions.
Authors: Fahd A Ahmad; Philip R O Payne; Ian Lackey; Rachel Komeshak; Kenneth Kenney; Brianna Magnusen; Christopher Metts; Thomas Bailey Journal: J Am Med Inform Assoc Date: 2020-02-01 Impact factor: 4.497
Authors: Edward R Melnick; Wesley C Holland; Osama M Ahmed; Anthony K Ma; Sean S Michael; Howard S Goldberg; Christian Lagier; Gail D'Onofrio; Tomek Stachowiak; Cynthia Brandt; Yauheni Solad Journal: JAMIA Open Date: 2019-10-14
Authors: Eliotte L Hirshberg; Jamin L Alexander; Lisa A Asaro; Kerry Coughlin-Wells; Garry M Steil; Debbie Spear; Cheryl Stone; Vinay M Nadkarni; Michael S D Agus Journal: Chest Date: 2021-04-29 Impact factor: 9.410