Use of statistical process control charts in the epidemiological surveillance of nosocomial infections

• Autor(a) principal: Arantes, Aglai
• Data de Publicação: 2003
• Outros Autores: Carvalho, Eduardo da Silva, Medeiros, Eduardo Alexandrino Servolo, Farhat, Calil Kairalla, Mantese, Orlando César
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Revista de Saúde Pública
• Texto Completo: https://www.revistas.usp.br/rsp/article/view/31660
• topic: Epidemiological surveillance; Cross infection; Infection control; Endemic diseases; Statistical graphs; Incidence; Inpatients; Intensive care units; pediatric; Hospitals; university; Vigilância epidemiológica; Infecção hospitalar; Controle de infecções; Doenças endêmicas; Gráficos estatísticos; Incidência; Pacientes internados; Unidades de terapia intensiva pediátrica; Hospitais universitários

OBJECTIVE: To monitor occurrence trends and identify clusters of nosocomial infection (NI) using statistical process control (SPC) charts. METHODS: Between January 1998 and December 2000 nosocomial infection occurrence was evaluated in a cohort of 460 patients admitted to the Pediatric Intensive Care Unit of a university hospital, according to the concepts and criteria proposed by the National Nosocomial Infection Surveillance System of the Centers for Disease Control, in the United States. Graphs were plotted using Poisson statistical distribution, including four horizontal lines: center line (CL), upper warning limit (UWL) and upper control limit (UCL). The CL was the arithmetic mean NI rate calculated for the studied period; UWL and UCL were drawn at 2 and 3 standard deviations above average NI rates, respectively. Clusters were identified when NI rates remained above UCL. RESULTS: Mean NI incidence was 20 per 1,000 patient days. One urinary tract infection cluster was identified in July 2000, with an infection rate of 63 per 1,000 patient days, exceeding UCL and characterizing a period of epidemic. CONCLUSIONS: The use of SPC charts for controlling endemic levels of NI, through both global and site-specific evaluation, allowed for the identification of uncommon variations in NI rates, such as outbreaks and epidemics, and for their distinction from the natural variations observed in NI occurrence rates, without the need for calculations and hypothesis testing.