Evidence map›Paper›PMID 36277312›Full record

ArticleEClinicalMedicine2022

Early recognition and response to increases in surgical site infections using optimised statistical process control charts-The early 2RIS trial: A multicentre stepped wedge cluster randomised controlled trial.

Arthur W Baker, Iulian Ilieş, James C Benneyan, Yuliya Lokhnygina, Katherine R Foy, Sarah S Lewis, Brittain Wood, Esther Baker, Linda Crane, Kathryn L Crawford and 12 more

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in EClinicalMedicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03075813 (Early Recognition and Response to Increases in Surgical Site Infections Using Optimized Statistical Process Control Charts), which is not on this map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.0field-weighted citation impact, top 14% 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.

NCT03075813 nacompletednot on this map

Early Recognition and Response to Increases in Surgical Site Infections Using Optimized Statistical Process Control Charts

TypeinterventionalSponsorDuke UniversityRan2017 to 2020Enrolled29ConditionsInfection Control, Surgical Site InfectionArmsIntervention Cluster
3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Review
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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

22 authors at 6 institutions in 1 country.

Arthur W BakerDivision of Infectious Diseases, Duke University School of Medicine, Durham, NC, USA.
Iulian IlieşHealthcare Systems Engineering Institute, Northeastern University, Boston, MA, USA.
James C BenneyanHealthcare Systems Engineering Institute, Northeastern University, Boston, MA, USA.
Yuliya LokhnyginaDepartment of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC, USA.
Katherine R FoyDivision of Infectious Diseases, Duke University School of Medicine, Durham, NC, USA.
Sarah S LewisDivision of Infectious Diseases, Duke University School of Medicine, Durham, NC, USA.
Brittain WoodDuke Center for Antimicrobial Stewardship and Infection Prevention, Durham, NC, USA.
Esther BakerDuke Center for Antimicrobial Stewardship and Infection Prevention, Durham, NC, USA.
Linda CraneDuke Center for Antimicrobial Stewardship and Infection Prevention, Durham, NC, USA.
Kathryn L CrawfordDuke Center for Antimicrobial Stewardship and Infection Prevention, Durham, NC, USA.
Andrea L CromerDuke Center for Antimicrobial Stewardship and Infection Prevention, Durham, NC, USA.
Polly PadgetteDuke Center for Antimicrobial Stewardship and Infection Prevention, Durham, NC, USA.
Linda RoachDuke Center for Antimicrobial Stewardship and Infection Prevention, Durham, NC, USA.
Linda AdcockDuke Center for Antimicrobial Stewardship and Infection Prevention, Durham, NC, USA.
Nicole NehlsHealthcare Systems Engineering Institute, Northeastern University, Boston, MA, USA.
Joseph SalemHealthcare Systems Engineering Institute, Northeastern University, Boston, MA, USA.
Dale BratzlerDepartment of Health Administration and Policy, College of Public Health, University of Oklahoma, Oklahoma City, OK, USA.
E Patchen DellingerDepartment of Surgery, University of Washington School of Medicine, Seattle, WA, USA.
Linda R GreeneHighland Hospital, University of Rochester Medical Center Affiliate, Rochester, NY, USA.
Susan S HuangDivision of Infectious Diseases, University of California, Irvine School of Medicine, Irvine, CA, USA.
Christopher R MantyhDepartment of Surgery, Duke University School of Medicine, Durham, NC, USA.
Deverick J AndersonDivision of Infectious Diseases, Duke University School of Medicine, Durham, NC, USA.
Duke University · USNortheastern University · USUniversity of California, Irvine · USUniversity of Oklahoma · USUniversity of Rochester Medical Center · USUniversity of Washington · US

Funding

Prevention of Surgical Site Infection using Statistical Process Control ChartsR01HS023821 · AHRQ · DUKE UNIVERSITY · PI ANDERSON, DEVERICK JOHN · 2015 to 2019
$2.5M
Combined Use of Statistical Process Control and Whole Genome Sequencing to Detect and Investigate Nontuberculous Mycobacterial Clusters and OutbreaksK08AI163462 · NIAID · DUKE UNIVERSITY · PI BAKER, ARTHUR W · 2021 to 2025
$942k
AHRQ HHS R01 HS023821NIAID NIH HHS K08 AI163462
6 · The paper itself

Abstract

Background: Traditional approaches for surgical site infection (SSI) surveillance have deficiencies that delay detection of SSI outbreaks and other clinically important increases in SSI rates. We investigated whether use of optimised statistical process control (SPC) methods and feedback for SSI surveillance would decrease rates of SSI in a network of US community hospitals. Methods: We conducted a stepped wedge cluster randomised trial of patients who underwent any of 13 types of common surgical procedures across 29 community hospitals in the Southeastern United States. We divided the 13 procedures into six clusters; a cluster of procedures at a single hospital was the unit of randomisation and analysis. In total, 105 clusters were randomised to 12 groups of 8-10 clusters. All participating clusters began the trial in a 12-month baseline period of control or "traditional" SSI surveillance, including prospective analysis of SSI rates and consultative support for SSI outbreaks and investigations. Thereafter, a group of clusters transitioned from control to intervention surveillance every three months until all clusters received the intervention. Electronic randomisation by the study statistician determined the sequence by which clusters crossed over from control to intervention surveillance. The intervention was the addition of weekly application of optimised SPC methods and feedback to existing traditional SSI surveillance methods. Epidemiologists were blinded to hospital identity and randomisation status while adjudicating SPC signals of increased SSI rates, but blinding was not possible during SSI investigations. The primary outcome was the overall SSI prevalence rate (PR=SSIs/100 procedures), evaluated via generalised estimating equations with a Poisson regression model. Secondary outcomes compared traditional and optimised SPC signals that identified SSI rate increases, including the number of formal SSI investigations generated and deficiencies identified in best practices for SSI prevention. This trial was registered at ClinicalTrials.gov, NCT03075813. Findings: Between Mar 1, 2016, and Feb 29, 2020, 204,233 unique patients underwent 237,704 surgical procedures. 148,365 procedures received traditional SSI surveillance and feedback alone, and 89,339 procedures additionally received the intervention of optimised SPC surveillance. The primary outcome of SSI was assessed for all procedures performed within participating clusters. SSIs occurred after 1171 procedures assigned control surveillance (prevalence rate [PR] 0.79 per 100 procedures), compared to 781 procedures that received the intervention (PR 0·87 per 100 procedures; model-based PR ratio 1.10, 95% CI 0.94-1.30, Interpretation: The addition of optimised SPC methods and feedback to traditional methods for SSI surveillance led to greater detection of important SSI rate increases and best practice deficiencies but did not decrease SSI rates. Additional research is needed to determine how to best utilise SPC methods and feedback to improve adherence to SSI quality measures and prevent SSIs. Funding: Agency for Healthcare Research and Quality.

Indexed as

Healthcare-associated infection surveillanceRandomised controlled trialStatistical process controlSurgical site infection

Identifiers

PMID36277312
PMCPMC9583445
OpenAlexW4306654693

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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.