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. 2019 Feb 19:8:12-19.
doi: 10.1016/j.eclinm.2019.02.001. eCollection 2019 Feb.

Association of Community Factors with Hospital-onset Clostridioides (Clostridium) difficile Infection: A Population Based U.S.-wide Study

Ioannis M Zacharioudakis  1   2 , Fainareti N Zervou  1   3 , Fadi Shehadeh  1 , Evangelia K Mylona  1 , Eleftherios Mylonakis  1
Affiliations

Association of Community Factors with Hospital-onset Clostridioides (Clostridium) difficile Infection: A Population Based U.S.-wide Study

Ioannis M Zacharioudakis et al. EClinicalMedicine. .

Abstract

Background: Clostridioides (Clostridium) difficile ranks first among the pathogens of hospital-acquired infections with hospital-based preventive strategies being only partially successful in containing its spread.

Methods: We performed a spatial statistical analysis to examine the association between population characteristics and parameters of community healthcare practice and delivery with hospital-onset Clostridioides (Clostridium) difficile infection (HO-CDI), using data from the Medicare Hospital Compare, Medicare Provider Utilization Part D, and other databases. Among the areas with the highest HO-CDI rates ("hot spots"), we conducted a geographically weighted regression (GWR) to quantify the effect of the decrease in the modifiable risk factors on the HO-CDI rate.

Findings: Percentage of population > 85 years old, community claims of antimicrobial agents and acid suppressants, and density of hospitals and nursing homes within the hospital service areas (HSAs) had a statistically significant association with the HO-CDI incidence (p < 0.001). The model including the community claims of antimicrobial agents and number of hospital centers per HSA km2 was associated with 10% (R2 = 0.10, p < 0.001) of the observed variation in HO-CDI rate. The hot spots were organized into 5 Combined Statistical areas that crossed state borders. The association of the antimicrobial claims and HO-CDI rate was as high as 71% in the Boston-Worcester-Providence area (R2 = 0.71, SD 0.19), with a 10% decrease in the rate of antimicrobial claims having the potential to lead to up to 23.1% decrease in the HO-CDI incidence in this area.

Interpretation: These results outline the association of HO-CDI with community practice and characteristics of the healthcare delivery system and support the need to further study the effect of community and nursing home-based antimicrobial and acid suppressant stewardship programs in the rate of HO-CDI in geographic areas that may cross state lines.

Keywords: CA-CDI, Community-acquired Clostridioides difficile infection; CDC, Centers for Disease Control and Prevention; CDI, Clostridioides difficile infection; CSA, Combined Statistical Area; Clostridioides difficile; Clostridium difficile; Geographically weighted regression model; HO-CDI; HO-CDI, Hospital-onset Clostridioides difficile infection; HSA, Hospital Service Area; PPIs, Proton-Pump Inhibitors; Risk factors; Spatial statistical analysis.

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Figures

Fig. 1
Fig. 1
Study flowchart.
Fig. 2
Fig. 2
Map of the statistically significant HO-CDI hot spots.
Fig. 3
Fig. 3
Results of the Geographically Weighted Regression (GWR) model in A. the Boston-Worcester-Providence B. New York-Newark, C. Philadelphia-Reading-Camden, D. Central-South Florida, E. Los Angeles-Long Beach, F. Detroit-Warren-Ann Arbor Combined Statistical Areas (CSAs). The size of the dots represents the regression coefficient for the rate of antimicrobial claims. The color represents the Coefficient of Determination (R [2]).
Fig. 3
Fig. 3
Results of the Geographically Weighted Regression (GWR) model in A. the Boston-Worcester-Providence B. New York-Newark, C. Philadelphia-Reading-Camden, D. Central-South Florida, E. Los Angeles-Long Beach, F. Detroit-Warren-Ann Arbor Combined Statistical Areas (CSAs). The size of the dots represents the regression coefficient for the rate of antimicrobial claims. The color represents the Coefficient of Determination (R [2]).
See this image and copyright information in PMC

References

    1. Magill S.S., Edwards J.R., Bamberg W. Multistate point-prevalence survey of health care-associated infections. N Engl J Med. 2014;370:1198–1208. - PMC - PubMed
    1. Lessa F.C., Mu Y., Bamberg W.M. Burden of Clostridium difficile infection in the United States. N Engl J Med. 2015;372:825–834. - PMC - PubMed
    1. Dubberke E.R., Olsen M.A. Burden of Clostridium difficile on the healthcare system. Clin Infect Dis. 2012;55(Suppl. 2):S88–S92. - PMC - PubMed
    1. Centers for Disease Control and Prevention Antibiotic resistance threats in the United States, 2013. http://www.cdc.gov/drugresistance/threat-report-2013/pdf/ar-threats-2013... [accessed January 5 2018]
    1. McDonald L.C., Gerding D.N., Johnson S. Clinical practice guidelines for Clostridium difficile infection in adults and children: 2017 update by the Infectious Diseases Society of America (IDSA) and Society for Healthcare Epidemiology of America (SHEA) Clin Infect Dis. 2018;66(7):e1–e48. - PMC - PubMed