Use of a remote clinical decision support service for a multicenter trial to implement prediction rules for children with minor blunt head trauma

Howard S Goldberg; Marilyn D Paterno; Robert W Grundmeier; Beatriz H Rocha; Jeffrey M Hoffman; Eric Tham; Marguerite Swietlik; Molly H Schaeffer; Deepika Pabbathi; Sara J Deakyne; Nathan Kuppermann; Peter S Dayan

doi:10.1016/j.ijmedinf.2015.12.002

Use of a remote clinical decision support service for a multicenter trial to implement prediction rules for children with minor blunt head trauma

Int J Med Inform. 2016 Mar:87:101-10. doi: 10.1016/j.ijmedinf.2015.12.002. Epub 2015 Dec 4.

Authors

Affiliations

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.

PMID: 26806717
DOI: 10.1016/j.ijmedinf.2015.12.002

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.

Keywords: Clinical decision support; Clinical trial; Interoperability; Service-oriented architecture; Standards; Traumatic brain injury.

Publication types

Research Support, American Recovery and Reinvestment Act
Research Support, N.I.H., Extramural
Research Support, U.S. Gov't, P.H.S.

MeSH terms

Adolescent
Brain Injuries / diagnosis*
Case Management*
Child
Child, Preschool
Decision Support Systems, Clinical / statistics & numerical data*
Electronic Health Records / statistics & numerical data*
Emergency Service, Hospital / standards*
Female
Humans
Infant
Infant, Newborn
Male
Remote Consultation / statistics & numerical data*

Abstract

Publication types

MeSH terms

Grants and funding