RESUMEN
Extended-spectrum-ß-lactamase (ESBL)-producing organisms are increasingly prevalent. We determined the characteristics of 66 consecutive ESBL-producing isolates from six community hospitals in North Carolina and Virginia from 2010 to 2012. Fifty-three (80%) ESBL-producing isolates contained CTX-M enzymes; CTX-M-15 was found in 68% of Escherichia coli and 73% of Klebsiella isolates. Sequence type 131 (ST131) was the commonest type of E. coli, accounting for 48% of CTX-M-15-producing and 66% of CTX-M-14-producing isolates. In conclusion, the CTX-M genotype and ST131 E. coli were common among ESBL isolates from U.S. community hospitals.
Asunto(s)
Infecciones por Enterobacteriaceae/microbiología , Escherichia coli/genética , Klebsiella/genética , beta-Lactamasas/genética , Anciano , Anciano de 80 o más Años , Infecciones por Enterobacteriaceae/epidemiología , Escherichia coli/clasificación , Escherichia coli/aislamiento & purificación , Expresión Génica , Hospitales Comunitarios , Humanos , Klebsiella/clasificación , Klebsiella/aislamiento & purificación , Persona de Mediana Edad , Tipificación de Secuencias Multilocus , North Carolina/epidemiología , Virginia/epidemiologíaRESUMEN
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.
RESUMEN
We performed a cross-sectional survey of infection preventionists in 60 US community hospitals between April 22 and May 8, 2020. Several differences in hospital preparedness for SARS-CoV-2 emerged with respect to personal protective equipment conservation strategies, protocols related to testing, universal masking, and restarting elective procedures.
Asunto(s)
COVID-19/prevención & control , Recursos en Salud/provisión & distribución , Hospitales Comunitarios/estadística & datos numéricos , Control de Infecciones/estadística & datos numéricos , Estudios Transversales , Encuestas de Atención de la Salud , Humanos , Control de Infecciones/instrumentación , Control de Infecciones/métodos , Equipo de Protección Personal/provisión & distribución , SARS-CoV-2Asunto(s)
Infección Hospitalaria/epidemiología , Laminectomía/efectos adversos , Complicaciones Posoperatorias/epidemiología , Recto/cirugía , Infección de la Herida Quirúrgica/epidemiología , Centers for Disease Control and Prevention, U.S. , Humanos , Mejoramiento de la Calidad/organización & administración , Estudios Retrospectivos , Sociedades Médicas , Estados Unidos/epidemiologíaRESUMEN
OBJECTIVE: To describe the rates of several key outcomes and healthcare-associated infections (HAIs) among hospitals that participated in the Duke Infection Control Outreach Network (DICON). DESIGN AND SETTING: Prospective, observational cohort study of patients admitted to 24 community hospitals from 2003 through 2009. METHODS: The following data were collected and analyzed: incidence of central line-associated bloodstream infections (CLABSIs), ventilator-associated pneumonia (VAP), catheter-associated urinary tract infections (CAUTIs), and HAIs caused by methicillin-resistant Staphylococcus aureus (MRSA); employee exposures to bloodborne pathogens (EBBPs); physician EBBPs; patient-days; central line-days; ventilator-days; and urinary catheter-days. Poisson regression was used to determine whether incidence rates of these HAIs and exposures changed during the first 5 and 7 years of participation in DICON; nonrandom clustering of each outcome was controlled for. Cost saved and lives saved were calculated on the basis of published estimates. RESULTS: In total, we analyzed 6.5 million patient-days, 4,783 EBPPs, 2,948 HAIs due to MRSA, and 2,076 device-related infections. Rates of employee EBBPs, HAIs due to MRSA, and device-related infections decreased significantly during the first 5 years of participation in DICON (P< .05 for all models; average decrease was approximately 50%); in contrast, physician EBBPs remained unchanged. In aggregate, 210 CLABSIs, 312 cases of VAP, 332 CAUTIs, 1,042 HAIs due to MRSA, and 1,016 employee EBBPs were prevented. Each hospital saved approximately $100,000 per year of participation, and collectively the hospitals may have prevented 52-105 deaths from CLABSI or VAP. The 7-year analysis demonstrated that these trends continued with further participation. CONCLUSIONS: Hospitals with long-term participation in an infection control network decreased rates of significant HAIs by approximately 50%, decreased costs, and saved lives.