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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.
Baker, Arthur W; Ilies, Iulian; Benneyan, James C; Lokhnygina, Yuliya; Foy, Katherine R; Lewis, Sarah S; Wood, Brittain; Baker, Esther; Crane, Linda; Crawford, Kathryn L; Cromer, Andrea L; Padgette, Polly; Roach, Linda; Adcock, Linda; Nehls, Nicole; Salem, Joseph; Bratzler, Dale; Dellinger, E Patchen; Greene, Linda R; Huang, Susan S; Mantyh, Christopher R; Anderson, Deverick J.
Afiliação
  • Baker AW; Division of Infectious Diseases, Duke University School of Medicine, Durham, NC, USA.
  • Ilies I; Duke Center for Antimicrobial Stewardship and Infection Prevention, Durham, NC, USA.
  • Benneyan JC; Healthcare Systems Engineering Institute, Northeastern University, Boston, MA, USA.
  • Lokhnygina Y; Healthcare Systems Engineering Institute, Northeastern University, Boston, MA, USA.
  • Foy KR; Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC, USA.
  • Lewis SS; Division of Infectious Diseases, Duke University School of Medicine, Durham, NC, USA.
  • Wood B; Duke Center for Antimicrobial Stewardship and Infection Prevention, Durham, NC, USA.
  • Baker E; Division of Infectious Diseases, Duke University School of Medicine, Durham, NC, USA.
  • Crane L; Duke Center for Antimicrobial Stewardship and Infection Prevention, Durham, NC, USA.
  • Crawford KL; Duke Center for Antimicrobial Stewardship and Infection Prevention, Durham, NC, USA.
  • Cromer AL; Duke Center for Antimicrobial Stewardship and Infection Prevention, Durham, NC, USA.
  • Padgette P; Duke Center for Antimicrobial Stewardship and Infection Prevention, Durham, NC, USA.
  • Roach L; Duke Center for Antimicrobial Stewardship and Infection Prevention, Durham, NC, USA.
  • Adcock L; Duke Center for Antimicrobial Stewardship and Infection Prevention, Durham, NC, USA.
  • Nehls N; Duke Center for Antimicrobial Stewardship and Infection Prevention, Durham, NC, USA.
  • Salem J; Duke Center for Antimicrobial Stewardship and Infection Prevention, Durham, NC, USA.
  • Bratzler D; Duke Center for Antimicrobial Stewardship and Infection Prevention, Durham, NC, USA.
  • Dellinger EP; Healthcare Systems Engineering Institute, Northeastern University, Boston, MA, USA.
  • Greene LR; Healthcare Systems Engineering Institute, Northeastern University, Boston, MA, USA.
  • Huang SS; Department of Health Administration and Policy, College of Public Health, University of Oklahoma, Oklahoma City, OK, USA.
  • Mantyh CR; Department of Surgery, University of Washington School of Medicine, Seattle, WA, USA.
  • Anderson DJ; Highland Hospital, University of Rochester Medical Center Affiliate, Rochester, NY, USA.
EClinicalMedicine ; 54: 101698, 2022 Dec.
Article em En | MEDLINE | ID: mdl-36277312
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, p=0.25). Traditional surveillance generated 24 formal SSI investigations that identified 120 SSIs with deficiencies in two or more perioperative best practices for SSI prevention. In comparison, optimised SPC surveillance generated 74 formal investigations that identified 458 SSIs with multiple best practice deficiencies. 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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Clinical_trials / Guideline / Prognostic_studies / Risk_factors_studies Idioma: En Revista: EClinicalMedicine Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Clinical_trials / Guideline / Prognostic_studies / Risk_factors_studies Idioma: En Revista: EClinicalMedicine Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos