Cited by 4Sepsis Diagnosis and TreatmentElectronic Health Records SystemsHealthcare Technology and Patient Monitoring

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Can an End-to-End Telesepsis Solution Improve the Severe Sepsis and Septic Shock Management Bundle-1 Metrics for Sepsis Patients Admitted From the Emergency Department to the Hospital?

Open access

Abstract

IMPORTANCE: Early detection and treatment for sepsis patients are key components to improving sepsis care delivery and increased The Severe Sepsis and Septic Shock Management Bundle (SEP-1) compliance may correlate with improved outcomes. OBJECTIVES: We assessed the impact of implementing a partially automated end-to-end sepsis solution including electronic medical record-linked automated monitoring, early detection, around-the-clock nurse navigators, and teleconsultation, on SEP-1 compliance in patients with primary sepsis, present at admission, admitted through the emergency department (ER). DESIGN, SETTING AND PARTICIPANTS: After a “surveillance only” training period between September 3, 2020, and October 5, 2020, the automated end-to-end sepsis solution intervention period occurred from October 6, 2020, to January 1, 2021 in five ERs in an academic health system. Patients who screened positive for greater than or equal to 3 sepsis screening criteria (systemic inflammatory response syndrome, quick Sequential Organ Failure Assessment, pulse oximetry), had evidence of infection and acute organ dysfunction, and were receiving treatment consistent with infection or sepsis were included. MAIN OUTCOMES AND MEASURES: SEP-1 compliance during the “surveillance only” period compared to the intervention period. RESULTS: During the intervention period, 56,713 patients presented to the five ERs; 20,213 (35.6%) met electronic screening criteria for potential sepsis; 1,233 patients had a primary diagnosis of sepsis, present at admission, and were captured by the nurse navigators. Median age of the cohort was 68 years (interquartile range, 57–79 yr); 55.3% were male; 63.5% were White/Caucasian, 26.3% Black/African-American; was 16.7%, and 879 patients (71.3%) were presumed bacterial sepsis, nonviral etiology, and SEP-1 bundle eligible. Nurse navigator real-time classification of this group increased from 51.7% during the “surveillance only” period to 71.8% during the intervention period (p = 0.0002). Five hospital SEP-1 compliance for the period leading into the study period (July 1, 2020–August 31, 2020) was 62% (p < 0.0001), during the “surveillance only” period, it was 68.4% and during the intervention period it was 78.3% (p = 0.002). CONCLUSIONS AND RELEVANCE: During an 11-week period of sepsis screening, monitoring, and teleconsultation in 5 EDs, SEP-1 compliance improved significantly compared with institutional SEP-1 reporting metrics and to a “surveillance only” training period.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1097/cce.0000000000000767

Cites

3 of 3 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • AI-enabled early warning systems and EHR-integrated clinical decision support can improve surveillance, risk stratification, and the timeliness of key sepsis processes required by SEP-1.

    “AI-enabled early warning systems and EHR-integrated clinical decision support can improve surveillance, risk stratification, and the timeliness of key sepsis processes required by SEP-1 [45,48,49].”

    From Artificial Intelligence to Facilitate SEP-1 Measure Compliance and Fluid Management in Sepsis (2026) · cites this paper as [49]

    The Methods (Study Population and Design; page not available) describe electronic-record-linked sepsis screening, automated SEP-1 deadline alerts, and nurse-led follow-up. The Discussion reports improved SEP-1 compliance, but the intervention also relied on nurse navigators and teleconsultation; our copy does not establish that the warning system was AI-enabled or that it performed risk stratification. (LLM, conf=0.86)

    Experimental — accuracy not yet measured
  • Gaieski et al. performed a prospective observational study to evaluate the impact of implementing an end-to-end Telesepsis solution in five emergency departments within an academic health system.

    “Gaieski et al. performed a prospective observational study to evaluate the impact of implementing an end-to-end Telesepsis solution—including EMR-linked automated monitoring, nurse navigators, and teleconsultation—in five emergency departments within an academic health system [49].”
  • Among over 56,000 ED encounters (including 1233 confirmed sepsis cases), the Telesepsis intervention significantly improved SEP-1 bundle compliance (from 68.4% to 78.3%, p = 0.002) and enhanced real-time identification and management of sepsis patients compared to the baseline surveillance period.

    “Among over 56,000 ED encounters (including 1233 confirmed sepsis cases), the intervention significantly improved SEP-1 bundle compliance (from 68.4% to 78.3%, p = 0.002) and enhanced real-time identification and management of sepsis patients compared to the baseline surveillance period.”

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 20

  1. Singer, 2016, The third international consensus definitions for sepsis and septic shock (Sepsis-3)., JAMA, 315, 801, 10.1001/jama.2016.0287 · DOI · Paper page
  2. Gaieski, 2013, Benchmarking the incidence and mortality of severe sepsis in the United States., Crit Care Med, 41, 1167, 10.1097/CCM.0b013e31827c09f8 · DOI
  3. Kaukonen, 2014, Mortality related to severe sepsis and septic shock among critically ill patients in Australia and New Zealand, 2000-2012., JAMA, 311, 1308, 10.1001/jama.2014.2637 · DOI · Paper page
  4. Mikkelsen, 2009, Serum lactate is associated with mortality in severe sepsis independent of organ failure and shock., Crit Care Med, 37, 1670, 10.1097/CCM.0b013e31819fcf68 · DOI
  5. Howell, 2007, Performance of severity of illness scoring systems in emergency department patients with infection., Acad Emerg Med, 14, 709, 10.1197/j.aem.2007.02.036 · DOI
  6. Shapiro, 2006, Implementation and outcomes of the Multiple Urgent Sepsis Therapies (MUST) protocol., Crit Care Med, 34, 1025, 10.1097/01.CCM.0000206104.18647.A8 · DOI
  7. Trzeciak, 2007, Serum lactate as a predictor of mortality in patients with infection., Intensive Care Med, 33, 970, 10.1007/s00134-007-0563-9 · DOI
  8. Rivers, 2001, Early goal-directed therapy in the treatment of severe sepsis and septic shock., N Engl J Med, 345, 1368, 10.1056/NEJMoa010307 · DOI · Paper page
  9. Yealy, 2014, A randomized trial of protocol-based care for early septic shock., N Engl J Med, 370, 1683, 10.1056/NEJMoa1401602 · DOI · Paper page
  10. Peake, 2014, Goal-directed resuscitation for patients with early septic shock., N Engl J Med, 371, 1496, 10.1056/NEJMoa1404380 · DOI
  11. Bone, 1992, Definitions for sepsis and organ failure and guidelines for the use of innovative therapies in sepsis. The ACCP/SCCM Consensus Conference Committee. American College of Chest Physicians/Society of Critical Care Medicine., Chest, 101, 1644, 10.1378/chest.101.6.1644 · DOI
  12. Levy, 2003, 2001 SCCM/ESICM/ACCP/ATS/SIS international sepsis definitions conference., Intensive Care Med, 29, 530, 10.1007/s00134-003-1662-x · DOI
  13. Kaukonen, 2015, Systemic inflammatory response syndrome criteria in defining severe sepsis., N Engl J Med, 372, 1629, 10.1056/NEJMoa1415236 · DOI
  14. Baghdadi, 2020, Association of a care bundle for early sepsis management with mortality among patients with hospital-onset or community-onset sepsis., JAMA Intern Med, 180, 707, 10.1001/jamainternmed.2020.0183 · DOI
  15. Rhee, 2018, Compliance with the national SEP-1 quality measure and association with sepsis outcomes: A multicenter retrospective cohort study., Crit Care Med, 46, 1585, 10.1097/CCM.0000000000003261 · DOI
  16. Venkatesh, 2018, Preliminary performance on the new CMS Sepsis-1 National Quality Measure: Early insights from the Emergency Quality Network (E-QUAL)., Ann Emerg Med, 71, 10, 10.1016/j.annemergmed.2017.06.032 · DOI · Paper page
  17. Kumar, 2006, Duration of hypotension before initiation of effective antimicrobial therapy is the critical determinant of survival in human septic shock., Crit Care Med, 34, 1589, 10.1097/01.CCM.0000217961.75225.E9 · DOI · Paper page
  18. Seymour, 2017, Time to treatment and mortality during mandated emergency care for sepsis., N Engl J Med, 376, 2235, 10.1056/NEJMoa1703058 · DOI · Paper page
  19. Mohr, 2021, Provider-to-provider telemedicine improves adherence to sepsis bundle care in community emergency departments., J Telemed Telecare, 27, 518, 10.1177/1357633X19896667 · DOI
  20. Freund, 2018, Effect of systematic physician cross-checking on reducing adverse events in the emergency department: The CHARMED cluster randomized trial., JAMA Intern Med, 178, 812, 10.1001/jamainternmed.2018.0607 · DOI

Cited by

Sorted by citations

Metadata

Authors
Gaieski, D. F., Carr, B., Toolan, M., Ciotti, K., Kidane, A., Flaada, D., Christina, J., & Aggarwal, R.
Affiliations
  • Thomas Jefferson University (US)
  • Mount Sinai Health System (US)
  • Jefferson Strategic Ventures, Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, PA.
  • NutritionQuest (United States) (US)
  • InTouch/TelaDoc Health, Inc, Purchase, NY.
Corresponding author
Gaieski, David F.
Venue
Critical Care Explorations
Published
2022-10
Volume
4
Issue
10
Pages
e0767
ISSN
2639-8028 (ISSN-L)
OpenAlex
W4304141146
Cited by
4
References
3
Citations by year
2024: 2 · 2023: 2
FWCI
0.72
Type
journal article
Language
en
Open access
Locations
  • Critical Care Explorations (publishedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Health Sciences › Medicine › Critical Care and Intensive Care Medicine › Sepsis Diagnosis and Treatment
  • Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
  • Health Sciences › Medicine › Surgery › Healthcare Technology and Patient Monitoring
Keywords
sepsis, septic shock, sepsis treatment, nurse navigators, teleconsultation, emergency department, sepsis screening, bundle compliance, quality improvement, early sepsis detection, hospitalization, SIRS, SOFA score, pulse oximetry

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review