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Prevalence and Epidemiology of Healthcare-Associated Infections (HAI) in US Nursing Homes (NH), 2017

Published online by Cambridge University Press:  02 November 2020

Nicola Thompson
Affiliation:
Centers for Disease Control and Prevention
Nimalie Stone
Affiliation:
Centers for Disease Control and Prevention
Cedric Brown
Affiliation:
Centers for Disease Control and Prevention
Taniece Eure
Affiliation:
Centers for Disease Control and Prevention
Austin Penna
Affiliation:
Centers for Disease Control and Prevention
Grant Barney
Affiliation:
New York Emerging Infections Program, Rochester, NY
Devra Barter
Affiliation:
Colorado Department of Public Health and Environment, Denver, CO
Paula Clogher
Affiliation:
Connecticut Emerging Infections Program and the Yale School of Public Health, New Haven, CT
Ghinwa Dumyati
Affiliation:
University of Rochester
Erin Epson
Affiliation:
California Department of Public Health, Healthcare-Associated Infections Program
Christina B. Felsen
Affiliation:
University of Rochester Medical Center
Linda Frank
Affiliation:
California Emerging Infections Program
Deborah Godine
Affiliation:
California Emerging Infections Program
Lourdes Irizarry
Affiliation:
New Mexico Department of Health, Santa Fe, NM
Helen Johnston
Affiliation:
Colorado Department of Public Health and Environment
Marion Kainer
Affiliation:
MPH, Tennessee Department of Health, Nashville, TN
Linda Li
Affiliation:
Maryland Department of Health, Baltimore, MD
Ruth Lynfield
Affiliation:
Minnesota Department of Health, St. Paul, MN
J.P. Mahoehney
Affiliation:
MPH, Minnesota Department of Health, St. Paul, MN
Joelle Nadle
Affiliation:
California Emerging Infections Program
Valerie Ocampo
Affiliation:
Oregon Health Authority
Susan Ray
Affiliation:
Emory Univ Sch of Med and Grady Health System
Monika Samper
Affiliation:
Oregon Health Authority
Sarah Shrum
Affiliation:
New Mexico Department of Health
Marla Sievers
Affiliation:
New Mexico Department of Health
Srinivasan Krithika
Affiliation:
Yale University
Lucy E. Wilson
Affiliation:
Maryland Department of Health, Baltimore, MD
Alexia Zhang
Affiliation:
Oregon Health Authority
Shelley Magill
Affiliation:
Centers for Disease Control and Prevention
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Abstract

Background: With an aging population, increasingly complex care, and frequent re-admissions, prevention of healthcare-associated infections (HAIs) in nursing homes (NHs) is a federal priority. However, few contemporary sources of HAI data exist to inform surveillance, prevention, and policy. Prevalence surveys (PSs) are an efficient approach to generating data to measure the burden and describe the types of HAI. In 2017, the Centers for Disease Control and Prevention (CDC) performed its first large-scale HAI PS through the Emerging Infections Program (EIP) to measure the prevalence and describe the epidemiology of HAI in NH residents. Methods: NHs from several states (CA, CO, CT, GA, MD, MN, NM, NY, OR, & TN) were randomly selected and asked to participate in a 1-day HAI PS between April and October 2017; participation was voluntary. EIP staff reviewed available medical records for NH residents present on the survey date to collect demographic and basic clinical information and infection signs and symptoms. HAIs with onset on or after NH day 3 were identified using revised McGeer infection definitions applied to data collected by EIP staff and were reported to the CDC through a web-based system. Data were reviewed by CDC staff for potential errors and to validate HAI classifications prior to analysis. HAI prevalence, number of residents with >1 HAI per number of surveyed residents ×100, and 95% CIs were calculated overall (pooled mean) and for selected resident characteristics. Data were analyzed using SAS v9.4 software. Results: Among 15,296 residents in 161 NHs, 358 residents with 375 HAIs were identified. The most common HAI sites were skin (32%), respiratory tract (29%), and urinary tract (20%). Cellulitis, soft-tissue or wound infection, symptomatic UTI, and cold or pharyngitis were the most common individual HAIs (Fig. 1). Overall HAI prevalence was 2.3 per 100 residents (95% CI, 2.1–2.6); at the NH level, the median HAI prevalence was 1.8 and ranged from 0 to 14.3 (interquartile range, 0–3.1). At the resident level (Fig. 2), HAI prevalence was significantly higher in persons admitted for postacute care with diabetes, with a pressure ulcer, receiving wound care, or with a device. Conclusions: In this large-scale survey, 1 in 43 NH residents had an HAI on a given day. Three HAI types comprised >80% of infections. In addition to identifying characteristics that place residents at higher risk for HAIs, these findings provide important data on HAI epidemiology in NHs that can be used to expand HAI surveillance and inform prevention policies and practices.

Funding: None

Disclosures: None

Type
Oral Presentations
Copyright
© 2020 by The Society for Healthcare Epidemiology of America. All rights reserved.
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