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Cited by 52Sepsis Diagnosis and TreatmentHealthcare Quality and ManagementMedical Coding and Health Information

Variability in determining sepsis time zero and bundle compliance rates for the centers for medicare and medicaid services SEP-1 measure

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Rhee, Chanu, Brown, Sarah R., Jones, Travis M., O’Brien, Cara, Pande, Anupam, Hamad, Yasir, Bulger, Amy L., Tobin, Kathleen A. +5 more·2018·Infection Control & Hospital Epidemiology
DOI 10.1017/ice.2018.134PMC PMC7977505
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Abstract

We compared sepsis “time zero” and Centers for Medicare and Medicaid Services (CMS) SEP-1 pass rates among 3 abstractors in 3 hospitals. Abstractors agreed on time zero in 29 of 80 (36%) cases. Perceived pass rates ranged from 9 of 80 cases (11%) to 19 of 80 cases (23%). Variability in time zero and perceived pass rates limits the utility of SEP-1 for measuring quality.

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  • Strict SEP-1 abstraction may not fully capture clinical judgment in complex cases, particularly when fluid dosing or antibiotic timing decisions need to be individualized.

    “while acknowledging that strict SEP-1 abstraction may not fully capture clinical judgment in complex cases, particularly when fluid dosing or antibiotic timing decisions need to be individualized [8,19].”

    From Artificial Intelligence to Facilitate SEP-1 Measure Compliance and Fluid Management in Sepsis (2026) · cites this paper as [8]

    The Discussion (page unavailable) says SEP-1 abstraction involves subjectivity, substantial judgment, and poor agreement about sepsis time zero and compliance. It does not address whether abstraction captures clinicians’ individualized fluid-dosing or antibiotic-timing decisions; its discussion of judgment concerns the abstractors’ determinations. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

  • SEP-1 failure may reflect clinical complexity rather than poor care.

    “Conversely, other work emphasizes that SEP-1 failure may reflect clinical complexity (e.g., hospital-onset sepsis, atypical presentations) rather than poor care.”

    From Artificial Intelligence to Facilitate SEP-1 Measure Compliance and Fluid Management in Sepsis (2026) · cites this paper as [8]

    The Results and Discussion report that hospital-onset sepsis was associated with greater disagreement about sepsis time zero, and that abstractors also disagreed about whether cases passed SEP-1. This supports the possibility that a recorded failure does not necessarily indicate poor care. The paper does not specifically examine atypical presentations or establish clinical complexity, rather than care quality, as the reason for failures. (LLM, conf=0.82)

    Experimental — accuracy not yet measured

  • National SEP-1 performance remains modest and variably measured.

    “National SEP-1 performance remains modest and variably measured.”

    From Artificial Intelligence to Facilitate SEP-1 Measure Compliance and Fluid Management in Sepsis (2026) · cites this paper as [8]

    The Results report SEP-1 pass rates of 11.3%–23.8%, depending on the abstractor, and poor agreement on compliance. But the Methods describe only 80 cases at three U.S. tertiary hospitals, and the Discussion cautions that the findings may not generalize to community hospitals. The paper supports modest, variably measured performance in its sample, not a national performance estimate. (LLM, conf=0.87)

    Experimental — accuracy not yet measured

  • While some studies associate compliance with improved outcomes, measurement variability and limited evidence for certain mandated elements remain central concerns.

    “While some studies associate compliance with improved outcomes, measurement variability and limited evidence for certain mandated elements remain central concerns [7,8,15,19].”

    From Artificial Intelligence to Facilitate SEP-1 Measure Compliance and Fluid Management in Sepsis (2026) · cites this paper as [8]

    The Discussion (page not provided) reports significant variability between abstractors in determining sepsis time zero and SEP-1 compliance, supporting the measurement-variability concern. Our copy does not address whether compliance improves outcomes or whether evidence is limited for particular mandated elements. (LLM, conf=0.87)

    Experimental — accuracy not yet measured

  • In a study by Rhee et al. across three hospitals, abstractors agreed on time zero in only 36% of cases, and calculated pass rates differed substantially across reviewers.

    “In a study by Rhee et al. across three hospitals, abstractors agreed on “time zero” in only 36% of cases, and calculated pass rates differed substantially across reviewers [8].”

    From Artificial Intelligence to Facilitate SEP-1 Measure Compliance and Fluid Management in Sepsis (2026) · cites this paper as [8]

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Authors
Rhee, C., Brown, S. R., Jones, T. M., O’Brien, C., Pande, A., Hamad, Y., Bulger, A. L., Tobin, K. A., Massaro, A. F., Anderson, D. J., Warren, D. K., Klompas, M., & Program, F. T. C. P. E.
Affiliations
  • Brigham and Women's Hospital (US)
  • Duke University (US)
  • Duke Medical Center (US)
  • Washington University in St. Louis (US)
  • Massachusetts General Hospital (US)
Corresponding author
Rhee, Chanu
ORCID
Venue
Infection Control & Hospital Epidemiology
Publisher
Cambridge University Press (CUP)
Published
2018-06-22
Volume
39
Issue
8
Pages
994-996
ISSN
  • 0899-823X (ISSN-L)
  • 1559-6834
DOI
10.1017/ice.2018.134
PMC
PMC7977505
OpenAlex
W2808958884
Cited by
51
References
8
Citations by year
2026: 6 · 2025: 4 · 2024: 3 · 2023: 4 · 2022: 7 · 2021: 9 · 2020: 10 · 2019: 5 · 2018: 3
FWCI
5.27
Type
journal article
Language
en
Open access
Licence
www.cambridge.org/core/terms (unspecified)
Locations
  • Infection Control and Hospital Epidemiology (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • Digital Commons@Becker (Washington University School of Medicine) (submittedVersion)
Funders
  • Centers for Disease Control and Prevention (U54CK000484)
  • Agency for Healthcare Research and Quality (K08HS025008)
Topics
  • Health Sciences › Medicine › Epidemiology › Sepsis Diagnosis and Treatment
  • Health Sciences › Health Professions › Health Information Management › Healthcare Quality and Management
  • Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
Keywords
sepsis, time zero, Centers for Medicare and Medicaid Services, sepsis bundle compliance, quality of care measurement, hospital quality indicators, sepsis mortality
MeSH terms
Aged, Aged, 80 and over, Cross Infection, Female, Hospitals, Humans, Length of Stay, Male, Medical Audit, Quality Assurance, Health Care, Time Factors, United States, Centers for Medicare and Medicaid Services, U.S., Reproducibility of Results, Multivariate Analysis, Practice Guidelines as Topic, Sepsis, Guideline Adherence, Tertiary Care Centers, Patient Care Bundles

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