End-to-End Sepsis Solution Incorporating Expert Telemedicine Consultation

David F. Gaieski, Brendan Carr, Melanie Toolan, Kim Ciotti, Amy Kidane, Joseph Christina, Rajesh Aggarwal

Research output: Contribution to journalArticlepeer-review

Abstract

Introduction: Early detection and optimal resuscitation of critically ill sepsis patients may improve sepsis care delivery. The objective was to assess the feasibility of developing and implementing an end-to-end sepsis solution including early detection, monitoring, and teleconsultation. Methods: Prospective implementation of an end-to-end sepsis solution for potential sepsis patients presenting to a community hospital emergency department (ED) between 11 AM and 5 PM, Monday to Friday, during a 40-day period in 2019. Qualifying patients were compared with patients presenting at other times during the pilot screening period and to historic controls. Results: During the initial period, 203 patients met the screening criteria for potential sepsis; 77 patients (37.9%) had a primary diagnosis of sepsis, present on admission. Mean age was 60 – 20 years; 50.7% were female; and 24 patients (11.8%) were primary sepsis, SEP-1 bundle eligible. Eighty of 203 (39.4%) had an initial lactate performed, mean, 2.7 – 1.7 mmol/L. For the 24 primary sepsis, SEP-1 bundle eligible patients, 100% received antibiotics and intravenous fluid. Thirteen consults were performed on 12 patients; mean time from consult decision to beam in to the telemedicine robot was 7.3 – 5.5 min; mean time from beam in to robot connection with the expert was 23.6 – 13.2 s; mean consultation call time was 6.3 – 4.3 min. Conclusions: In a convenience sample of patients with potential sepsis presenting to a community hospital ED, an end-to-end sepsis solution using early detection, tracking, and consultation was feasible and has the potential to improve sepsis detection and treatment.

Original languageEnglish
Pages (from-to)1679-1687
Number of pages9
JournalTelemedicine Journal and e-Health
Volume29
Issue number11
DOIs
StatePublished - 1 Nov 2023
Externally publishedYes

Keywords

  • identification
  • resuscitation
  • sepsis
  • telemedicine
  • time-sensitive illness

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