Evidence map›Paper›PMID 35907839›Full record

ArticleBMC health services research2022

Mitigating structural racism to reduce inequities in sepsis outcomes: a mixed methods, longitudinal intervention study.

Erika L Linnander, Adeola Ayedun, Dowin Boatright, Kupiri Ackerman-Barger, Timothy I Morgenthaler, Natasha Ray, Brita Roy, Steven Simpson, Leslie A Curry

Open access · goldAbstract read
In one paragraph

Article in BMC health services research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
4.0field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Observational
  5. Be-SNAP: the Belgian Sepsis National Action Plan.Frontiers in public health · 2025
    Article
  6. Article
  7. Article
  8. Article
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  10. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 6 institutions in 1 country.

Erika L LinnanderDepartment of Health Policy and Management, Yale School of Public Health, New Haven, USA. erika.linnander@yale.edu.ORCID http://orcid.org/0000-0002-3417-1049
Adeola AyedunYale Global Health Leadership Initiative, Yale School of Public Health, New Haven, USA.
Dowin BoatrightDepartment of Emergency Medicine, Yale School of Medicine, New Haven, USA.
Kupiri Ackerman-BargerBetty Irene Moore School of Nursing, University of California Davis Health, Sacramento, USA.
Timothy I MorgenthalerDivision of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, USA.
Natasha RayNew Haven Healthy Start, New Haven, USA.
Brita RoyDepartment of Medicine, Yale School of Medicine, New Haven, USA.
Steven SimpsonDivision of Pulmonary, Critical Care and Sleep Medicine, School of Medicine, University of Kansas, Kansas City, USA.
Leslie A CurryDepartment of Health Policy and Management, Yale School of Public Health, New Haven, USA.
Yale New Haven Health System · USYale University · USHealthy Start · USMayo Clinic in Florida · USUC Davis Health · USUniversity of Kansas · US

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Reducing Variation in Sepsis OutcomesR01GM146463 · NIGMS · YALE UNIVERSITY · PI Dowin Boatright, LESLIE CURRY · 2022 to 2026
$2.9M
NCATS NIH HHS UL1 TR001863NIGMS NIH HHS 1R01GM146463-01NIGMS NIH HHS R01 GM146463
6 · The paper itself

Abstract

backgroundSepsis affects 1.7 million patients in the US annually, is one of the leading causes of mortality, and is a major driver of US healthcare costs. African American/Black and LatinX populations experience higher rates of sepsis complications, deviations from standard care, and readmissions compared with Non-Hispanic White populations. Despite clear evidence of structural racism in sepsis care and outcomes, there are no prospective interventions to mitigate structural racism in sepsis care, nor are we aware of studies that report reductions in racial inequities in sepsis care as an outcome. Therefore, we will deliver and evaluate a coalition-based intervention to equip health systems and their surrounding communities to mitigate structural racism, driving measurable reductions in inequities in sepsis outcomes. This paper presents the theoretical foundation for the study, summarizes key elements of the intervention, and describes the methodology to evaluate the intervention.

methodsOur aims are to: (1) deliver a coalition-based leadership intervention in eight U.S. health systems and their surrounding communities; (2) evaluate the impact of the intervention on organizational culture using a longitudinal, convergent mixed methods approach, and (3) evaluate the impact of the intervention on reduction of racial inequities in three clinical outcomes: a) early identification (time to antibiotic), b) clinical management (in-hospital sepsis mortality) and c) standards-based follow up (same-hospital, all-cause sepsis readmissions) using interrupted time series analysis. DISCUSSION: This study is aligned with calls to action by the NIH and the Sepsis Alliance to address inequities in sepsis care and outcomes. It is the first to intervene to mitigate effects of structural racism by developing the domains of organizational culture that are required for anti-racist action, with implications for inequities in complex health outcomes beyond sepsis.

Indexed as

Black or African AmericanHealth Care CostsHispanic or LatinoHumansLongitudinal StudiesRacismSepsisSystemic RacismUnited StatesHealth SystemsIntervention StudiesLeadershipOrganizational CultureRacial DisparitiesSepsisStructural Racism

Identifiers

PMID35907839
PMCPMC9338573
OpenAlexW4288748931

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.