Using artificial intelligence to reduce orthopedic surgical site infection surveillance workload: Algorithm design, validation, and implementation in 4 Spanish hospitals.

Journal: American journal of infection control
PMID: 37100291

Abstract

BACKGROUND: Surgical site infection (SSI) surveillance is a labor-intensive endeavor. We present the design and validation of an algorithm for SSI detection after hip replacement surgery, and a report of its successful implementation in 4 public hospitals in Madrid, Spain.

Authors

  • Álvaro Flores-Balado
    Infection Control Department, Fundación Jiménez Díaz University Hospital, Madrid, Spain.
  • Carlos Castresana Méndez
    Spanish Department of Health, Madrid, Spain.
  • Antonio Herrero González
    QuironSalud, Madrid, Spain. Electronic address: aherrero@quironsalud.es.
  • Raúl Mesón Gutierrez
    Big Data Unit, Fundación Jiménez Díaz University Hospital, Madrid, Spain.
  • Gonzalo de Las Casas Cámara
    Infection Control Department, Rey Juan Carlos University Hospital, Móstoles, Comunidad de Madrid, Spain.
  • Beatriz Vila Cordero
    Infection Control Department, Rey Juan Carlos University Hospital, Móstoles, Comunidad de Madrid, Spain.
  • Javier Arcos
    Fundación Jiménez Díaz University Hospital, Madrid, Spain; UICO (Clinical and Organizational Innovation Unit), Quironsalud 4-H Network, Madrid, Spain.
  • Bernadette Pfang
    UICO (Clinical and Organizational Innovation Unit), Quironsalud 4-H Network, Madrid, Spain.
  • María Dolores Martín-Ríos
    Infection Control Department, Fundación Jiménez Díaz University Hospital, Madrid, Spain. Electronic address: maria.mrios@hospitalreyjuancarlos.es.

Keywords

External Resources

Popular Topics
Recent Journals