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Importance of risk adjusting central line-associated bloodstream infection rates in children

Published online by Cambridge University Press:  07 October 2024

Lakshmi Srinivasan Open the ORCID record for Lakshmi Srinivasan [Opens in a new window] ,
Ashley Oliver ,
Yuan-shung V Huang Open the ORCID record for Yuan-shung V Huang [Opens in a new window] ,
Di Shu ,
Kait M Donnelly ,
Cecelia Harrison Open the ORCID record for Cecelia Harrison [Opens in a new window] ,
Amy L. Roberts  and
Ron Keren
Lakshmi Srinivasan*
Affiliation:
The Children’s Hospital of Philadelphia, Philadelphia, PA, USA Department of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
Ashley Oliver
Affiliation:
The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
Yuan-shung V Huang
Affiliation:
Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
Di Shu
Affiliation:
The Children’s Hospital of Philadelphia, Philadelphia, PA, USA Department of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
Kait M Donnelly
Affiliation:
The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
Cecelia Harrison
Affiliation:
The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
Amy L. Roberts
Affiliation:
Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
Ron Keren
Affiliation:
The Children’s Hospital of Philadelphia, Philadelphia, PA, USA Department of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
*
Corresponding author: Lakshmi Srinivasan; Email: srinivasanl@chop.edu
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Abstract

Objective:

Central line-associated bloodstream infection (CLABSI) is one of the most prevalent pediatric healthcare-associated infections and is used to benchmark hospital performance. Pediatric patients have increased in acuity and complexity over time. Existing approaches to risk adjustment do not control for individual patient characteristics, which are strong predictors of CLABSI risk and vary over time. Our objective was to develop a risk adjustment model for CLABSI in hospitalized children and compare observed to expected rates over time.

Design and Setting:

We conducted a prospective cohort study using electronic health record data at a quaternary Children’s Hospital.

Patients:

We included hospitalized children with central catheters.

Methods:

Risk factors identified from published literature were considered for inclusion in multivariable modeling based on association with CLABSI risk in bivariable analysis and expert input. We calculated observed and expected (risk model-adjusted) annual CLABSI rates.

Results:

Among 16,411 patients with 520,209 line days, 633 patients experienced 796 CLABSIs. The final model included age, behavioral health condition, non-English speaking, oncology service, port catheter type, catheter dwell time, lymphatic condition, total parenteral nutrition, and number of organ systems requiring ICU level care. For every organ system receiving ICU level care the odds ratio for CLABSI was 1.24 (95% CI 1.12–1.37). Although not statistically different, observed rates were lower than expected rates for later years.

Conclusions:

Failure to adjust for patient factors, particularly acuity and complexity of disease, may miss clinically significant differences in CLABSI rates, and may lead to inaccurate interpretation of the impact of quality improvement efforts.

Information

Type
Original Article
Information
Infection Control & Hospital Epidemiology , Volume 45 , Issue 11 , November 2024 , pp. 1280 - 1285
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Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of The Society for Healthcare Epidemiology of America

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Footnotes

Meeting Presentation: This work has been presented at Pediatric Academic Societies, Washington DC in April 2023 and Solutions for Patient Safety, St. Louis, MO in May 2023.

References

Institute of Medicine Committee on Quality of Health Care in A. In: Kohn LT, Corrigan JM, Donaldson MS, eds. To Err is Human: Building a Safer Health System. National Academies Press (US). Copyright 2000 by the National Academy of Sciences.Google Scholar
Lyren, A, Brilli, R, Bird, M, Lashutka, N, Muething, S. Ohio Children’s Hospitals’ solutions for patient safety: a framework for pediatric patient safety improvement. J Healthc Qual 2013. https://doi.org/10.1111/jhq.12058 Google Scholar
Miller, MR, Niedner, MF, Huskins, WC, et al. Reducing PICU central line-associated bloodstream infections: 3-year results. Pediatrics 2011;128:e1077–83. https://doi.org/10.1542/peds.2010-3675 CrossRefGoogle ScholarPubMed
Agency for Healthcare Research and Quality. Eliminating CLABSI, A National Patient Safety Imperative: Final Report. 2013. https://www.ahrq.gov/hai/cusp/clabsi-final/index.html. Accessed March 15, 2023.Google Scholar
Bucholz, EM, Toomey, SL, Schuster, MA. Trends in pediatric hospitalizations and readmissions: 2010–2016. Pediatrics 2019;143:e20181958. https://doi.org/10.1542/peds.2018-1958.CrossRefGoogle ScholarPubMed
Hall, M, Berry, JG, Hall, M, Goodwin, EJ, et al. Changes in hospitalization populations by level of complexity at children’s hospitals. J Hosp Med 2024;19:399–402. https://doi.org/10.1002/jhm.13292. Epub ahead of print. PMID: 38340352.CrossRefGoogle ScholarPubMed
Agency for Healthcare Research and Quality. Pediatric Quality Indicators (PDI) Benchmark Data Tables, v2022. 2022. https://qualityindicators.ahrq.gov/downloads/modules/PDI/V2022/Version_2022_Benchmark_Tables_PDI.pdf. Accessed March 15, 2023.Google Scholar
Goudie, A, Dynan, L, Brady, PW, Rettiganti, M. Attributable cost and length of stay for central line-associated bloodstream infections. Pediatrics 2014;133:e1525–32. https://doi.org/10.1542/peds.2013-3795 CrossRefGoogle ScholarPubMed
The NHSN Standardized Infection Ratio: A guide to the SIR. 2022. https://www.cdc.gov/nhsn/pdfs/ps-analysis-resources/nhsn-sir-guide.pdf. Accessed February 1, 2023.Google Scholar
National Healthcare Safety Network. Bloodstream infection event (central line–associated bloodstream infection and non-central line associated bloodstream infection). Updated January 2023. https://www.cdc.gov/nhsn/pdfs/pscmanual/4psc_clabscurrent.pdf. 2023. Accessed February 6, 2023.Google Scholar
Hord, JD, Lawlor, J, Werner, E, et al. Central line associated blood stream infections in pediatric hematology/oncology patients with different types of central lines. Pediatr Blood Cancer 2016;63:1603–1607.CrossRefGoogle ScholarPubMed
Adler, A, Yaniv, I, Steinberg, R, et al. Infectious complications of implantable ports and Hickman catheters in paediatric haematology-oncology patients. J Hosp Infect 2006;62:358–365.CrossRefGoogle ScholarPubMed
Cui, J. QIC program and model selection in GEE analyses. Stata J 2007;7:209–220.CrossRefGoogle Scholar
Srinivasan, L, Padula, M, on behalf of the Infectious Diseases Focus Group of the Children’s Hospital Neonatal Consortium. Disease-specific Blood Stream Infection and CLABSI Rates among Infants in Level 4 CHNC NICUs. Platform presentation at the Children’s Hospital Neonatal Consortium Annual Conference, Denver, CO. 2022.Google Scholar
Coffey, M, Marino, M, Lyren, A, et al. Association between hospital-acquired harm outcomes and membership in a National Patient Safety Collaborative. JAMA Pediatr 2022;176:924–932. https://doi.org/10.1001/jamapediatrics.2022.2493 CrossRefGoogle Scholar
Armbrister, AJ, Finke, AM, Long, AM, Korvink, M, Gunn, LH. Turning up the volume to address biases in predicted healthcare-associated infections and enhance U.S. hospital rankings: a data-driven approach. Am J Infect Control 2022;50:166–175. https://doi.org/10.1016/j.ajic.2021.08.014 CrossRefGoogle ScholarPubMed
Umscheid, CA, Mitchell, MD, Doshi, JA, Agarwal, R, Williams, K, Brennan, PJ. Estimating the proportion of healthcare-associated infections that are reasonably preventable and the related mortality and costs. Infect Control Hosp Epidemiol 2011;32:101–114. https://doi.org/10.1086/657912 CrossRefGoogle ScholarPubMed
Fuller, RL, Hughes, JS, Atkinson, G, Aubry, BS. Problematic risk adjustment in National Healthcare Safety Network Measures. Am J Med Qual 2020;35:205–212. https://doi.org/10.1177/1062860619859073 CrossRefGoogle ScholarPubMed
Vaughan, AM, Ross, R, Gilman, MM, et al. Mucosal barrier injury central-line-associated bloodstream infections: what is the impact of standard prevention bundles? Infect Control Hosp Epidemiol 2017;38:1385–1387. https://doi.org/10.1017/ice.2017.188 CrossRefGoogle Scholar
Hsu, HE, Mathew, R, Wang, R, et al. Health care-associated infections among critically ill children in the US, 2013–2018. JAMA Pediatr 2020;174:1176–1183. https://doi.org/10.1001/jamapediatrics.2020.3223 CrossRefGoogle ScholarPubMed
Jackson, SS, Leekha, S, Magder, LS, et al. The effect of adding comorbidities to current centers for disease control and prevention central-line-associated bloodstream infection risk-adjustment methodology. Infect Control Hosp Epidemiol 2017;38:1019–1024. https://doi.org/10.1017/ice.2017.129 CrossRefGoogle ScholarPubMed
Wylie, MC, Graham, DA, Potter-Bynoe, G, et al. Risk factors for central line-associated bloodstream infection in pediatric intensive care units. Infect Control Hosp Epidemiol 2010;31:1049–1056. https://doi.org/10.1086/656246 CrossRefGoogle ScholarPubMed
Pepin, CS, Thom, KA, Sorkin, JD, et al. Risk factors for central-line-associated bloodstream infections: a focus on comorbid conditions. Infect Control Hosp Epidemiol 2015;36:479–481. https://doi.org/10.1017/ice.2014.81 CrossRefGoogle ScholarPubMed
Woods-Hill, CZ, Srinivasan, L, Schriver, E, Haj-Hassan, T, Bezpalko, O, Sammons, JS. Novel risk factors for central-line associated bloodstream infections in critically ill children. Infect Control Hosp Epidemiol 2020;41:67–72. https://doi.org/10.1017/ice.2019.302 CrossRefGoogle ScholarPubMed
Figueroa-Phillips, LM, Bonafide, CP, Coffin, SE, Ross, ME, Guevara, JP. Development of a clinical prediction model for central line-associated bloodstream infection in children presenting to the emergency department. Pediatr Emerg Care 2020;36:e600–e605. https://doi.org/10.1097/PEC.0000000000001835 CrossRefGoogle ScholarPubMed
Dube, WC, Jacob, JT, Zheng, Z, et al. Comparison of rates of central line-associated bloodstream infections in patients with 1 vs 2 central venous catheters. JAMA Netw Open 2020;3:e200396. https://doi.org/10.1001/jamanetworkopen.2020.0396 CrossRefGoogle ScholarPubMed
Tomar, S, Lodha, R, Das, B, Sood, S, Kapil, A. Risk factors for central line associated bloodstream infections. Indian Pediatr 2016;53:790–792. https://doi.org/10.1007/s13312-016-0932-y CrossRefGoogle ScholarPubMed
Willer, BL, Tobias, JD, Suttle, ML, Nafiu, OO, Mpody, C. Trends of racial/ethnic disparities in pediatric central line-associated bloodstream infections. Pediatrics 2022;150:e2021054955. https://doi.org/10.1542/peds.2021-054955 CrossRefGoogle ScholarPubMed
Gaur, AH, Bundy, DG, Gao, C, et al. Surveillance of hospital-acquired central line-associated bloodstream infections in pediatric hematology-oncology patients: lessons learned, challenges ahead. Infect Control Hosp Epidemiol 2013;34:316–320. https://doi.org/10.1086/669513 CrossRefGoogle ScholarPubMed
Spaulding, AB, Watson, D, Dreyfus, J, et al. Epidemiology of bloodstream infections in hospitalized children in the United States, 2009–2016. Clin Infect Dis 2019;69:995–1002. https://doi.org/10.1093/cid/ciy1030 CrossRefGoogle ScholarPubMed
Harris, AD, Sbarra, AN, Leekha, S, et al. Electronically available comorbid conditions for risk prediction of healthcare-associated Clostridium difficile infection. Infect Control Hosp Epidemiol 2018;39:297–301. https://doi.org/10.1017/ice.2018.10 CrossRefGoogle ScholarPubMed
Martinez, T, Baugnon, T, Vergnaud, E, et al. Central-line-associated bloodstream infections in a surgical paediatric intensive care unit: risk factors and prevention with chlorhexidine bathing. J Paediatr Child Health 2020;56:936–942. https://doi.org/10.1111/jpc.14780 CrossRefGoogle Scholar
Rabelo, BS, de Alvarenga, KAF, Miranda, J, et al. Risk factors for catheter-related infection in children with cancer: a systematic review and meta-analysis. Am J Infect Control 2023;51:99–106. https://doi.org/10.1016/j.ajic.2022.05.005 CrossRefGoogle Scholar
Maude, SL, Fitzgerald, JC, Fisher, BT, et al. Outcome of pediatric acute myeloid leukemia patients receiving intensive care in the United States. Pediatr Crit Care Med 2014;15:112–120. https://doi.org/10.1097/PCC.0000000000000042 CrossRefGoogle ScholarPubMed
Lyren, A, Children’s hospitals’ solutions for patient safety. Personal Communication, 2023.Google Scholar
Delgado-Rodriguez, M, Llorca, J. Caution should be exercised when using the standardized infection ratio. Infect Control Hosp Epidemiol 2005;26:8–9. https://doi.org/10.1086/503173 CrossRefGoogle ScholarPubMed
Weiner-Lastinger, LM, Dudeck, MA, Allen-Bridson, K, et al. Changes in the number of intensive care unit beds in US hospitals during the early months of the coronavirus disease 2019 (COVID-19) pandemic. Infect Control Hosp Epidemiol 2022;43:1477–1481. https://doi.org/10.1017/ice.2021.266 CrossRefGoogle ScholarPubMed
CMS.gov. Risk Adjustment in Quality Improvement. CMS Measures Management System (MMS) Hub; 2023. https://mmshub.cms.gov/sites/default/files/Risk-Adjustment-in-Quality-Measurement.pdf. Accessed March 15, 2023.Google Scholar
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