{
  "abstract": "Background While run charts and statistical process control (SPC) charts are powerful tools for visualizing data over time and detecting non-random variation, they have methodological limitations when used to infer causality in quality improvement (QI) initiatives. In complex, real-world settings where randomization is often not feasible, Quasi-Experimental Designs (QEDs) offer a practical approach to establishing causal pathways for evaluating intervention effectiveness. The 2nd Mexico in Alliance with St. Jude Golden Hour Quality Improvement Collaborative was implemented across 85 Latin American hospitals with the aim of reducing the time between triage and antibiotic administration (TTA) for febrile pediatric hematology-oncology patients (fPHOP) who present to the Emergency Department to <= 60 minutes (Golden Hour).Objectives Establish the causal pathway and evaluate the impact of Golden Hour on reducing infection-related complications using QEDs.Methods Segmented regression was applied to ITS data collected between November 2021 and July 2024. Between-group comparisons were performed using chi-square and Mann-Whitney U tests. Effect sizes were reported as absolute risk reduction (ARR) and number needed to treat (NNT).Results For 10,442 fPHO reported events, the median TTA showed a significant monthly reduction (–8.5; p<0.001) from 70 (IQR: 40–150) to 41 minutes (IQR: 30–71) following the implementation of the Golden Hour. The intervention led to an immediate 5.8 percentage point reduction in sepsis incidence (95% CI: –9.9 to –1.6; p<0.05) ( figure 1), which further decreased from 7.7% during the implementation phase to 4.3% in the sustainability phase (p<0.001). The ARR was 0.5%, 7.8%, and 0.7%, and the NNT was 189, 13, and 142 for mortality, sepsis, and ICU transfers, respectively (p<0.05)Conclusion QEDs offer a rigorous complement to run and SPC charts for establishing the causal pathway evidence of QI initiatives. Using QEDs, we demonstrated the Golden Hour effectiveness in improving and sustaining clinical outcomes at scale in real-world settings.Abstract 48 Figure 1Segmented regression on the impact of the golden hour on sepsis incidence",
  "authors": [
    {
      "affiliations": [
        "Patient Safety Research Unit, Clinical Research Institute, School of Medicine, Universidad Nacional de Colombia. Bogotá, Colombia",
        "Clinical Research Institute, School of Medicine, Fundación Universitaria Sanitas. Bogotá, Colombia. C",
        "Adverse Events Analysis Unit, Instituto de Evaluación Tecnológica en Salud (IETS). Bogotá, Colombia",
        "Institute for Healthcare Improvement, Boston, MA"
      ],
      "name": "Kelly Estrada-Orozco"
    },
    {
      "affiliations": [
        "Institute for Healthcare Improvement, Boston, MA",
        "National Institute of Public Health, Cuernavaca, MOR, Mexico"
      ],
      "name": "Klaudia A Arizmendi-Barrera"
    },
    {
      "affiliations": [
        "Institute for Healthcare Improvement, Boston, MA",
        "Instituto de Efectividad Clínica y Sanitaria, Buenos Aires, Argentina",
        "PICU, Hospital General de Niños Pedro de Elizalde, Buenos Aires, Argentina"
      ],
      "name": "Facundo Jorro-Baron"
    },
    {
      "affiliations": [
        "Department of Global Pediatric Medicine, St. Jude Children’s Research Hospital, Memphis, TN, USA"
      ],
      "name": "Naomi Echendía-Abud"
    },
    {
      "affiliations": [
        "Department of Global Pediatric Medicine, St. Jude Children’s Research Hospital, Memphis, TN, USA"
      ],
      "name": "Miriam Gonzalez-Guzman"
    },
    {
      "affiliations": [
        "Institute for Healthcare Improvement, Boston, MA"
      ],
      "name": "Sonya Panjwani"
    },
    {
      "affiliations": [
        "Department of Global Pediatric Medicine, St. Jude Children’s Research Hospital, Memphis, TN, USA"
      ],
      "name": "Paola Friedrich"
    },
    {
      "affiliations": [
        "Institute for Healthcare Improvement, Boston, MA",
        "Department of Global Health and Social Medicine, Harvard Medical School, Boston, MA, USA",
        "Harvard TH Chan School of Public Health, Boston, MA, USA"
      ],
      "name": "Jafet Arrieta"
    }
  ],
  "title": "48 Moving beyond run and control charts to establish a causal pathway and evaluate impact: a case study",
  "uid": "ee6a9563-2c53-5aad-9f86-0385a6d43e7f"
}