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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
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

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
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.

References

Stone, PW, Pogorzelska, M, Kunches, L, Hirschhorn, LR. Hospital staffing and healthcare-associated infections: a systematic review of the literature. Clin Infect Dis 2008; 47: 937944.CrossRefGoogle ScholarPubMed
Mitchell, BG, Gardner, A, Stone, PW, Hall, L, Pogorzelska-Maziarz, M. Hospital staffing and healthcare-associated infections: a systematic review of the literature. Jt Comm J Qual Patient Saf 2018; 44: 613622.Google ScholarPubMed
Geubbels, ELPE, Wille, JC, Nagelkerke, NJD, Vandenbroucke-Grauls, CM, Grobbee, DE, de Boer, AS. Hospital-related determinants fore surgical-site infections following hip arthroplasty. Infect Control Hosp Epidemiol 2005; 26: 435441.CrossRefGoogle Scholar
Richet, HM, Bengachir, M, Brown, DFJ, et al. Are there regional variations in the diagnosis, surveillance, and control of methicillin-resistant Staphylococcus aureus? Infect Control Hosp Epidemiol 2003; 24: 334341.CrossRefGoogle ScholarPubMed
The UK Neonatal Staffing Study Group. Relationship between probable nosocomial bacteraemia and organizational and structural factors in UK neonatal intensive care units. Qual Saf Health Care 2005; 14: 264269.CrossRefGoogle Scholar
Vassallo, A, Boston, KM. The master of public health graduate as infection preventionist: navigating the changing landscape of infection prevention. Am J Infect Control 2019; 47: 201207.CrossRefGoogle ScholarPubMed
Bartles, R, Dickson, A, Babade, O. A systematic approach to quantifying infection prevention staffing and coverage needs. Am J Infect Control 2018; 46: 487491.CrossRefGoogle ScholarPubMed
Bryant, KA, Harris, AD, Gould, CV, et al. Necessary infrastructure of infection prevention and healthcare epidemiology programs: a review. Infect Control Hosp Epidemiol 2016; 37: 371380.CrossRefGoogle ScholarPubMed
Wright, SB, Ostrowsky, B, Fishman, N, Deloney, VM, Mermel, L, Perl, TM. Expanding roles of healthcare epidemiology and infection control in spite of limited resources and compensation. Infect Control Hosp Epidemiol 2010; 31: 127132.CrossRefGoogle ScholarPubMed
Carosella, L, Leach, R, Ragar, Marshall Gray, M P. The novice roadmap: developing infection preventionists through an internship role. Am J Infect Control 2017;45:S63.CrossRefGoogle Scholar
Sestovic, M, Castellano-Flynn, P. Career advancement for infection preventionists; innovative recruitment and retention tool. Am J Infect Control 2019;47:S32.CrossRefGoogle Scholar
Hessels, AJ, Kelly, AM, Chen, L, Cohen, B, Zachariah, P, Larson, EL. Impact of infectious exposures and outbreaks on nurse and infection preventionist workload. Am J Infect Control 2019; 47: 623627.CrossRefGoogle ScholarPubMed
Landers, T, Davis, J, Crist, K, Malik, C. APIC MegaSurvey: methodology and overview. Am J Infect Control 2017; 45: 584588.Google ScholarPubMed
Bearman, G, Hota, SS, Haessler, SD. Physician burnout and healthcare epidemiology: dual implications worthy of greater scrutiny. Infect Control Hosp Epidemiol 2020; 41: 250251.Google ScholarPubMed
Pogorzelska-Maziarz, M, Gilmartin, H, Reese, S. Infection prevention staffing and resources in US acute-care hospitals: results from the APIC MegaSurvey. Am J Infect Control 2018; 46: 852857.CrossRefGoogle Scholar
National Healthcare Safety Network (NHSN) patient safety component manual. Centers for Disease Control website. https://www.cdc.gov/nhsn/pdfs/pscmanual/pcsmanual_current.pdf. Accessed September 5, 2021.Google Scholar
Koutras, MV, Bersimis, S, Maravelakis, PE. Statistical process control using Shewhart control charts with supplementary runs rules. Methodol Comput Appl Probab 2007; 9: 207224.CrossRefGoogle Scholar
Hugonnet, S, Uçkay, I, Pittet, D. Staffing level: a determinant of late-onset ventilator-associated pneumonia. Crit Care 2007;11:R80.CrossRefGoogle ScholarPubMed
Hugonnet, S, Chevrolet, JC, Pittet, D. The effect of workload on infection risk in critically ill patients. Crit Care Med 2007; 35: 7681.CrossRefGoogle ScholarPubMed
R Core Team ( 2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org. Accessed September 5, 2021.Google Scholar
Haley, RW, Quade, D, Freeman, HE, Bennett, JV. Study on the efficacy of nosocomial infection control (SENIC project). Am J Epidemiol 1980; 11: 472484.CrossRefGoogle Scholar
O’Boyle, C, Jakson, M, Henly, SJ. Staffing requirements for infection control programs in UD health care facilities: Delphi project. Am J Infect Control 2002; 30: 321333.CrossRefGoogle Scholar
Morrison J, Health Canada, Nosocomial and Occupation Infections Section. Development of a resource model for infection control and prevention programs in acute, long term, and home care settings: conference proceedings of the Infection Prevention and Control Alliance. Am J Infect Control 2004; 32: 26.CrossRefGoogle Scholar
van den Broek, PJ, Kluytmans, JAJW, Ummels, LC, Voss, A, Vandenbroucke-Grauls, CM. How many infection control staff do we need in hospitals? J Hosp Infect 2007; 65: 108111.CrossRefGoogle ScholarPubMed
Weiner-Lastinger, LM, Pattabiraman, V, Konnor, RY, et al. The impact of coronavirus disease 2019 (COVID-19) on healthcare-associated infections in 2020: a summary of data reported to the National Healthcare Safety Network. Infect Control Hosp Epidemiol 2021. doi:10.1017/ice.2021.362.CrossRefGoogle Scholar
Magill, SS, Edwards, JR, Bamberg, W, et al. Multistate point-prevalence survey of healthcare-associated infections. N Eng J Med 2014; 370: 11981208.CrossRefGoogle Scholar
Magill, SS, O’Leary, E, Janelle, SJ, et al. Changes in prevalence of healthcare-associated infections in US hospitals. N Eng J Med 2018; 379: 17321744.CrossRefGoogle Scholar
Stone, PW, Mooney-Kane, C, Larson, EL, et al. Nurse working conditions and patient safety outcomes. Med Care 2007; 45: 571578.CrossRefGoogle ScholarPubMed
Tauntoun, RL, Kleinbeck, SV, Stafford, R, Woods, CQ, Bott, MJ. Patient outcomes: are they linked to registered nurse absenteeism, separation, or workload? J Nurs Adm 1994; 24: 4855.Google Scholar
Zingg, W, Mutters, NT, Harbarth, S, Friedrich, AW. Education in infection control: a need for European certification. Clin Microbiol Infect 2015; 21: 10521056.CrossRefGoogle ScholarPubMed
New CAIP ASC infection preventions credential: 7 things to know. Becker’s Clinical Leadership and Infection Control website. https://www.beckersasc.com/asc-quality-infection-control/new-caip-asc-infection-prevention-credential-7-things-to-know.html. Accessed September 5, 2021.Google Scholar
Knighton, SC, Gilmartin, HM, Reese, SM. Factors affecting compensation and professional development support for infection preventionists: implication for recruitment and retention. Am J Infect Control 2018; 46: 865869.CrossRefGoogle Scholar
Supplementary material: File

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