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Infection preventionist staffing levels and rates of 10 types of healthcare-associated infections: A 9-year ambidirectional observation

Published online by Cambridge University Press:  17 January 2022

Robert J. Clifford Open the ORCID record for Robert J. Clifford [Opens in a new window] ,
Donna Newhart ,
Maryrose R. Laguio-Vila Open the ORCID record for Maryrose R. Laguio-Vila [Opens in a new window] ,
Jennifer L. Gutowski ,
Melissa Z. Bronstein  and
Emil P. Lesho
Robert J. Clifford
Affiliation:
Bioinformatics, Cavia Partners, Silver Spring, Maryland
Donna Newhart
Affiliation:
Quality and Safety Institute, Rochester Regional Health, Rochester, New York
Maryrose R. Laguio-Vila
Affiliation:
Infectious Diseases Unit, Rochester Regional Health, Rochester, New York
Jennifer L. Gutowski
Affiliation:
Infection Prevention, Rochester Regional Health, Rochester, New York
Melissa Z. Bronstein
Affiliation:
Quality and Safety Institute, Rochester Regional Health, Rochester, New York
Emil P. Lesho*
Affiliation:
Infectious Diseases Unit, Rochester Regional Health, Rochester, New York
*
Author for correspondence: Emil Lesho, E-mail: carolinelesho@yahoo.com
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Abstract

Objective:

To quantitatively evaluate relationships between infection preventionists (IPs) staffing levels, nursing hours, and rates of 10 types of healthcare-associated infections (HAIs).

Design and setting:

An ambidirectional observation in a 528-bed teaching hospital.

Patients:

All inpatients from July 1, 2012, to February 1, 2021.

Methods:

Standardized US National Health Safety Network (NHSN) definitions were used for HAIs. Staffing levels were measured in full-time equivalents (FTE) for IPs and total monthly hours worked for nurses. A time-trend analysis using control charts, t tests, Poisson tests, and regression analysis was performed using Minitab and R computing programs on rates and standardized infection ratios (SIRs) of 10 types of HAIs. An additional analysis was performed on 3 stratifications: critically low (2–3 FTE), below recommended IP levels (4–6 FTE), and at recommended IP levels (7–8 FTE).

Results:

The observation covered 1.6 million patient days of surveillance. IP staffing levels fluctuated from ≤2 IP FTE (critically low) to 7–8 IP FTE (recommended levels). Periods of highest catheter-associated urinary tract infection SIRs, hospital-onset Clostridioides difficile and carbapenem-resistant Enterobacteriaceae infection rates, along with 4 of 5 types of surgical site SIRs coincided with the periods of lowest IP staffing levels and the absence of certified IPs and a healthcare epidemiologist. Central-line–associated bloodstream infections increased amid lower nursing levels despite the increased presence of an IP and a hospital epidemiologist.

Conclusions:

Of 10 HAIs, 8 had highest incidences during periods of lowest IP staffing and experience. Some HAI rates varied inversely with levels of IP staffing and experience and others appeared to be more influenced by nursing levels or other confounders.

Type
Original Article
Information
Infection Control & Hospital Epidemiology , Volume 43 , Issue 11 , November 2022 , pp. 1641 - 1646
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Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of The Society for Healthcare Epidemiology of America

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Footnotes

PREVIOUS PRESENTATION: These data were presented in an oral presentation at the Infectious Diseases Society of America IDWeek 2019 on February 3, 2019, in Washington, DC: “During A Million Patient Days of Surveillance, Low Levels of Infection Preventionists Correlated with Higher Rates of Some Healthcare-associated Infections” by E. Lesho, R. Clifford, C. Sosa, K. Vore, J. Fede, M. Laguio-Vila, and M. Bronstein.

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