Hostname: page-component-586b7cd67f-g8jcs Total loading time: 0 Render date: 2024-11-25T08:49:18.008Z Has data issue: false hasContentIssue false

The economic burden of Clostridioides difficile infection in patients with hematological malignancies in the United States: A case-control study

Published online by Cambridge University Press:  15 May 2020

Lola Duhalde
Affiliation:
Da Volterra, Paris, France Ecole Polytechnique, Palaiseau, France
Lise Lurienne
Affiliation:
Da Volterra, Paris, France
Sebastian M. Wingen-Heimann
Affiliation:
Department of Internal Medicine, University Hospital of Cologne, Cologne, Germany FOM University of Applied Sciences, Cologne, Germany
Lucien Guillou
Affiliation:
Da Volterra, Paris, France Faculty of Pharmacy, University Paris-Sud, Châtenay-Malabry, France
Renaud Buffet
Affiliation:
Da Volterra, Paris, France
Pierre-Alain Bandinelli*
Affiliation:
Da Volterra, Paris, France
*
Author for correspondence: Pierre-Alain Bandinelli, E-mail: [email protected]

Abstract

Objective:

The primary study aim was to describe all direct healthcare costs associated with Clostridioides difficile infection (CDI), both in and out of the hospital, in patients with hematologic malignancies in the United States.

Design:

A retrospective analysis was conducted utilizing data from US databases of Truven Health Analytics.

Patients:

We analyzed health insurance claims between January 2014 and December 2017 of patients diagnosed with hematological cancer: acute myeloid leukemia (AML), acute lymphoblastic leukemia, Hodgkin’s lymphoma, and non-Hodgkin’s lymphoma (NHL).

Methods:

Patients with CDI after cancer diagnosis (CDI+, cases) were matched with patients without CDI reported (CDI−, controls). Matched cases and controls were compared to identify the CDI-associated costs in the 90 days following the onset of CDI.

Results:

We matched 622 CDI+ patients with 11,111 CDI− patients. NHL (41.7%) and AML (30.9%) were the predominant underlying diseases in the CDI+ groups. During study period, the average time in-hospital of CDI+ patients was 23.1 days longer than for CDI− patients (P < 2×10−16). Overall, CDI onset increased costs of care by an average of US$57,159 per patient (P = 6×10−12), mainly driven by hospital costs.

Conclusions:

This study confirms the significant economic burden associated with CDI in the United States, especially in patients with hematological malignancies. These findings highlight the need for prevention of CDI in this specific patient population.

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

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Bartlett, JG, Gerding, DN. Clinical recognition and diagnosis of Clostridium difficile infection. Clin Infect Dis 2008;46 suppl 1:S12S18.CrossRefGoogle ScholarPubMed
What is C. diff? Centers for Disease Control and Prevention website. https://www.cdc.gov/cdiff/what-is.html. Accessed August 2019.Google Scholar
Bruminhent, J, Wang, Z-X, Hu, C, et al. Clostridium difficile colonization and disease in patients undergoing hematopoietic stem cell transplantation. Biol Blood Marrow Transpl 2014;20:13291334.CrossRefGoogle ScholarPubMed
Cannon, CM, Musuuza, JS, Barker, AK, et al. Risk of Clostridium difficile infection in hematology-oncology patients colonized with toxigenic C. difficile . Infect Control Hosp Epidemiol 2017;38:718720.CrossRefGoogle ScholarPubMed
Selvey, LA, Slimings, C, Joske, DJL, Riley, TV. Clostridium difficile infections amongst patients with haematological malignancies: a data linkage study. PLoS One 2016;11(6):e0157839.CrossRefGoogle ScholarPubMed
Zhang, D, Prabhu, VS, Marcella, SW. Attributable healthcare resource utilization and costs for patients with primary and recurrent Clostridium difficile infection in the United States. Clin Infect Dis 2018;66:13261332.CrossRefGoogle ScholarPubMed
Quimbo, RA, Palli, SR, Singer, J, Strauss, M. PIN13 The incremental economic burden of Clostridium difficile–associated diarrhea among hospitalized patients at high risk of recurrent infection. Value Health 2012;15(4):A239.CrossRefGoogle Scholar
Desai, K, Gupta, SB, Dubberke, ER, Prabhu, VS, Browne, C, Mast, TC. Epidemiological and economic burden of Clostridium difficile in the United States: estimates from a modeling approach. BMC Infect Dis 2016;16:303.CrossRefGoogle ScholarPubMed
Mollard, S, Lurienne, L, Heimann, SM, Bandinelli, P-A. Burden of Clostridium (Clostridioides) difficile infection during inpatient stays in the USA between 2012 and 2016. J Hosp Infect 2019;102:135140.Google Scholar
Leblanc, S, Blein, C, Andremont, A, Bandinelli, P-A, Galvain, T. Burden of Clostridium difficile infections in French hospitals in 2014 from the national health insurance perspective. Infect Control Hosp Epidemiol 2017;38:906911.CrossRefGoogle ScholarPubMed
Grube, R, Heinlein, W, Scheffer, H, et al. Ökonomische Auswirkungen einer Clostridium-difficile-Enterokolitis in deutschen Krankenhäusern auf der Basis von DRG-Kostendaten [in German]. Z Für Gastroenterol. 2015;53:391397.Google Scholar
Heimann, SM, Cruz Aguilar, MR, Mellinghof, S, Vehreschild, MJGT. Economic burden and cost-effective management of Clostridium difficile infections. Médecine Mal Infect 2018;48:2329.CrossRefGoogle ScholarPubMed
Luo, R, Greenberg, A, Stone, CD. Outcomes of Clostridium difficile infection in hospitalized leukemia patients: a nationwide analysis. Infect Control Hosp Epidemiol 2015;36:794801.CrossRefGoogle ScholarPubMed
Ran-Castillo, D, Oluwole, A, Abuaisha, M, et al. Risk, outcomes, and trends of Clostridium difficile infection in multiple myeloma patients from a nationwide analysis. Cureus 2019;11(4):e4391.Google ScholarPubMed
Revolinski, SL, Munoz-Price, LS. Clostridium difficile in immunocompromised hosts: a review of epidemiology, risk factors, treatment, and prevention. Clin Infect Dis 2019;68:21442153.CrossRefGoogle ScholarPubMed
MarketScan Research website. https://marketscan.truvenhealth.com/marketscanportal/. Accessed December 30, 2019.Google Scholar
IBM MarketScan Research Databases. https://www.ibm.com/us-en/marketplace/marketscan-research-databases. Accessed December 30, 2019.Google Scholar
Garrison, LP, Pauly, MV, Willke, RJ, Neumann, PJ. An overview of value, perspective, and decision context—a health economics approach: an ISPOR special task force report. Value Health 2018;21:124130.CrossRefGoogle ScholarPubMed
Schalk, E, Bohr, URM, König, B, Scheinpflug, K, Mohren, M. Clostridium difficile–associated diarrhoea, a frequent complication in patients with acute myeloid leukaemia. Ann Hematol 2010;89:914.CrossRefGoogle ScholarPubMed
Quan, H, Sundararajan, V, Halfon, P, et al. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care 2005;43:11301139.CrossRefGoogle ScholarPubMed
Gasparini, A. Comorbidity: an R package for computing comorbidity scores. J Open Source Softw 2018;3:648.CrossRefGoogle Scholar
US Bureau of Labor Statistics. Consumer Price Index for All Urban Consumers: Medical Care Services. CUSR0000SAM2. St Louis, MO: Federal Reserve Bank; 2018.Google Scholar
R Core Team. R: a language and environment for statisticalcomputing. R Foundation for Statistical Computing website. https://www.R-project.org/. Published 2018. Accessed December 30, 2019.Google Scholar
R-data table. Github website. https://github.com/Rdatatable/data.table/wiki. Accessed August 9, 2019.Google Scholar
Ho, DE, Imai, K, King, G, Stuart, EA. MATCHIT: nonparametric preprocessing for parametric causal inference. Harvard website. https://r.iq.harvard.edu/docs/matchit/2.4-20/. Published October 24, 2011. Accessed August 9, 2019.Google Scholar
Ford, CD, Lopansri, BK, Webb, BJ, et al. Clostridioides difficile colonization and infection in patients with newly diagnosed acute leukemia: incidence, risk factors, and patient outcomes. Am J Infect Control 2019;47:394399.CrossRefGoogle ScholarPubMed
Duhalde, L, Lurienne, L, Wingen-Heimann, SM, Guillou, L, Buffet, R, Bandinelli, P-A. Excess burden associated with Clostridioides difficile infection in haematological patients occurring during hospitalization with induction chemotherapy in the United States. J Hosp Infect 2019;S0195670119305389.Google Scholar
Healthcare-associated infections—community interface (HAIC). Centers for Disease Control and Prevention website. https://www.cdc.gov/hai/eip/cdiff-tracking.html. Published December 2013. Accessed December 30, 2019.Google Scholar
Heimann, SM, Vehreschild, JJ, Cornely, OA, et al. Economic burden of Clostridium difficile associated diarrhoea: a cost-of-illness study from a German tertiary care hospital. Infection 2015;43:707714.CrossRefGoogle ScholarPubMed
Scheurer, DB, Hicks, LS, Cook, EF, Schnipper, JL. Accuracy of ICD-9 coding for Clostridium difficile infections: a retrospective cohort. Epidemiol Infect 2007;135:10101013.CrossRefGoogle ScholarPubMed
Supplementary material: File

Duhalde et al. Supplementary Materials

Duhalde et al. Supplementary Materials

Download Duhalde et al. Supplementary Materials(File)
File 100.9 KB