Population-Based Surveillance of Clostridium difficile Infection in Manitoba, Canada, by Using Interim Surveillance Definitions

2009 ◽  
Vol 30 (10) ◽  
pp. 945-951 ◽  
Author(s):  
Pascal J. Lambert ◽  
Myrna Dyck ◽  
Laura H. Thompson ◽  
Greg W. Hammond
Keyword(s):  
Nursing Home ◽  
Clostridium Difficile ◽  
Hospital Admission ◽  
Working Group ◽  
Surveillance System ◽  
Ad Hoc ◽  
Healthcare Facility ◽  
Population Based ◽  
Incident Cases ◽  
Community Onset

Objective.TO apply interim surveillance definitions of Clostridium difficile infection (CDI) cases to 1 year of data from the provincewide surveillance system of Manitoba, Canada, to determine the epidemiology of CDI incident cases in a population.Methods.CDI cases were categorized with interim surveillance definitions developed by an ad hoc C. difficile surveillance working group. Incident cases recorded in the provincial CDI database between July 2005 and June 2006 were linked to the provincial hospitalization and nursing home databases and analyzed.Results.One thousand six incident cases were identified over 1 year. Five hundred fifteen (51%) cases were associated with and began in a healthcare facility (HCF), whereas 275 (27%) were associated with and began in the community. An additional 131 (13%) cases were HCF associated but began in the community, while 85 (8%) were of indeterminate origin. Cases of HCF-associated CDI occurred in patients who were older than did cases of community-associated CDI (P < .0001). The provincial rate of community-onset cases was 23.4 per 100,000 person-years, and rates varied among geographic areas. HCF-associated CDI rates among the 10 largest hospitals varied from 0.5 to 8.4 per 10,000 patient-days. The time to CDI onset after hospital admission indicated that 25% of nosocomial cases began by the 8th day, and 50% began by the 17th day.Conclusions.Although the majority of CDI cases were associated with exposure to a HCF, 40% of incident CDI began in the community. Populations with HCF- and community-associated CDI demonstrated significantly different age distributions. The wide variation of rates among HCFs requires explanation. The high percentage of incident cases in the community warrants increased study.

Recommendations for Surveillance of Clostridium difficile–Associated Disease

2007 ◽  
Vol 28 (2) ◽  
pp. 140-145 ◽  
Author(s):  
L. Clifford McDonald ◽  
Bruno Coignard ◽  
Erik Dubberke ◽  
Xiaoyan Song ◽  
Teresa Horan ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Clostridium Difficile ◽  
Pseudomembranous Colitis ◽  
Ad Hoc ◽  
Toxic Megacolon ◽  
Healthcare Facility ◽  
Case Patient ◽  
Healthcare Settings ◽  
Community Onset ◽  
Laboratory Assay

Background.The epidemiology of Clostridium difficile-associated disease (CDAD) is changing, with evidence of increased incidence and severity. However, the understanding of the magnitude of and reasons for this change is currently hampered by the lack of standardized surveillance methods.Objective and Methods.An ad hoc C. difficile surveillance working group was formed to develop interim surveillance definitions and recommendations based on existing literature and expert opinion that can help to improve CDAD surveillance and prevention efforts.Definitions and Recommendations.A CDAD case patient was defined as a patient with symptoms of diarrhea or toxic megacolon combined with a positive result of a laboratory assay and/or endoscopic or histopathologic evidence of pseudomembranous colitis. Recurrent CDAD was defined as repeated episodes within 8 weeks of each other. Severe CDAD was defined by CDAD-associated admission to an intensive care unit, colectomy, or death within 30 days after onset. Case patients were categorized by the setting in which C. difficile was likely acquired, to account for recent evidence that suggests that healthcare facility-associated CDAD may have its onset in the community up to 4 weeks after discharge. Tracking of healthcare facility–onset, healthcare facility–associated CDAD is the minimum surveillance required for healthcare settings; tracking of community–onset, healthcare facility–associated CDAD should be performed only in conjunction with tracking of healthcare facility–onset, healthcare facility–associated CDAD. Community–associated CDAD was defined by symptom onset more than 12 weeks after the last discharge from a healthcare facility. Rates of both healthcare facility–onset, healthcare facility–associated CDAD and community–onset, healthcare facility–associated CDAD should be expressed as case patients per 10,000 patient–days; rates of community-associated CDAD should be expressed as case patients per 100,000 person-years.

scholarly journals An Assessment of 2016 National Healthcare Safety Network (NHSN) and National Electronic Disease Surveillance System (NEDSS) Clostridium difficile Infections (CDI) in Nebraska

2017 ◽  
Vol 4 (suppl_1) ◽  
pp. S399-S399
Author(s):  
Caitlin Pedati ◽  
Madison Sullivan ◽  
Margaret Drake ◽  
Alison Keyser ◽  
Tom Safranek ◽  
...  
Keyword(s):  
Clostridium Difficile ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Healthcare Facility ◽  
Data Sources ◽  
National Healthcare ◽  
Disease Surveillance System ◽  
Department Of Health ◽  
National Healthcare Safety Network ◽  
Community Onset

Abstract Background In 2016 all acute care hospitals, inpatient rehab facilities, and PPS-exempt cancer facilities in Nebraska were required to report laboratory identified (LabID) Clostridium difficile infections (CDIs) to the National Healthcare Safety Network (NHSN). Test results indicating CDIs must be reported to the Nebraska Department of Health and Human Services (NDHHS) via the National Electronic Disease Surveillance System (NEDSS). NHSN and NEDSS represent unique sources of CDI reports in Nebraska. Methods The NHSN Nebraska database was queried for CDIs reported in 2016. All lab tests indicating a CDI in 2016 were extracted from NEDSS. These extracts were analyzed to assess descriptive epidemiologic variables and compared for differences. Results In 2016 there were 1,546 CDI LabID events reported to NHSN Nebraska from 28 facilities. There were 249 outpatient CDIs and 1,297 inpatient CDIs. Infections were further characterized as community-onset (N = 773), community-onset, healthcare facility associated (N = 206), and hospital onset (N = 567). An average of 128 CDIs were reported per month (range: 111–155). In 2016 there were 2,177 lab results indicating a CDI reported to NEDSS among Nebraska residents from 42 facilities. Patient ages ranged from 4 months to 104 years (mean = 58 years). An average of 181 CDIs were reported per month (range: 151–218). Comparison of the two data sources found 781 reports among 591 unique patients at 11 facilities that were made to NHSN and were not in NEDSS. Additionally, there were 1,092 reports from 931 unique patients at 12 facilities that were made to NEDSS and should have been made to NHSN but were not. There were 9 shared facilities that accounted for the majority of these discrepancies. Conclusion NHSN and NEDSS represent two unique data sources that allow for a more comprehensive assessment of CDIs. The number and type of facility that report to each system is slightly different but there is some overlap. Therefore, this comparison allows for detection of a greater number of reports overall and also provides an opportunity for data validation. This assessment identified discrepancies in reporting among 9 facilities that can be targeted for further collaborative efforts to improve CDI reporting and management in Nebraska. Disclosures All authors: No reported disclosures.

scholarly journals Hospital-Associated Clostridium difficile Infection: Is It Necessary to Track Community-Onset Disease?

2009 ◽  
Vol 30 (4) ◽  
pp. 332-337 ◽  
Author(s):  
Erik R. Dubberke ◽  
Kathleen M. McMullen ◽  
Jennie L. Mayfield ◽  
Kimberly A. Reske ◽  
Peter Georgantopoulos ◽  
...  
Keyword(s):  
Clostridium Difficile ◽  
Hospital Admission ◽  
Care Facility ◽  
Healthcare Facility ◽  
Generation Cephalosporin ◽  
Demographic Characteristics ◽  
Fourth Generation ◽  
Patient Demographic ◽  
Traditional Definition ◽  
Community Onset

Objectives.To compare Clostridium difficile infection (CDI) rates determined with use of a traditional definition (ie, with healthcare-onset CDI defined as diagnosis of CDI more than 48 hours after hospital admission) with rates determined with use of expanded definitions, including both healthcare-onset CDI and community-onset CDI, diagnosed within 48 hours after hospital admission in patients who were hospitalized in the previous 30 or 60 days, and to determine whether differences exist between patients with CDI onset in the community and those with CDI onset in a healthcare setting.Design.Prospective cohortSetting.Tertiary acute care facility.Patients.General medicine patients who received a diagnosis of CDI during the period January 1, 2004, through December 31, 2005.Methods.CDI was classified as healthcare-onset CDI, healthcare facility–associated CDI after hospitalization within the previous 30 days, and/or healthcare facility-associated CDI after hospitalization within the previous 60 days. Patient demographic characteristics and medication exposures were obtained. The CDI incidence with use of each definition, CDI rate variability, patient demographic characteristics, and medication exposures were compared.Results.The healthcare-onset CDI rate (1.6 cases per 1,000 patient-days) was significantly lower than the 30-day healthcare facility–associated CDI rate (2.4 cases per 1,000 patient-days; P<.01) and the 60-day healthcare facility–associated CDI rate (2.6 cases per 1,000 patient-days; P<.01). There was good correlation between the healthcare-onset CDI rate and both the 30-day (correlation, 0.69; P<.01) and 60-day (correlation, 0.70; P<.01) healthcare facility–associated CDI rates. There were no months in which the CDI rate was more than 3 standard deviations from the mean. Compared with patients with healthcare-onset CDI, patients with community-onset CDI were less likely to have received a fourth-generation cephalosporin (P = .02) or intravenous vancomycin (P = .01) during hospitalization.Conclusions.Compared with the traditional definition, expanded definitions identify more patients with CDI. There is good correlation between traditional and expanded CDI definitions; therefore, it is unclear whether expanded surveillance is necessary to identify an abnormal change in CDI rates. Cases that met the expanded definitions were less likely to have occurred in patients with fourth-generation cephalosporin and vancomycin exposure.

scholarly journals Multicenter Study of Clostridium difficile Infection Rates from 2000 to 2006

2010 ◽  
Vol 31 (10) ◽  
pp. 1030-1037 ◽  
Author(s):  
Erik R. Dubberke ◽  
Anne M. Butler ◽  
Deborah S. Yokoe ◽  
Jeanmarie Mayer ◽  
Bala Hota ◽  
...  
Keyword(s):  
Clostridium Difficile ◽  
Hospital Admission ◽  
Healthcare Facility ◽  
The United States ◽  
Incidence Rates ◽  
Regional Problem ◽  
Toxin Assay ◽  
Definition Of ◽  
Study Hospital ◽  
Community Onset

Objective.To compare incidence rates of Clostridium difficile infection (CDI) during a 6-year period among 5 geographically diverse academic medical centers across the United States by use of recommended standardized surveillance definitions of CDI that incorporate recent information on healthcare facility (HCF) exposure.Methods.Data on C. difficile toxin assay results and dates of hospital admission and discharge were collected from electronic databases. Chart review was performed for patients with a positive C. difficile toxin assay result who were identified within 48 hours after hospital admission to determine whether they had any HCF exposure during the 90 days prior to their hospital admission. CDI cases, defined as any inpatient with a stool toxin assay positive for C. difficile, were categorized into 5 surveillance definitions based on recent HCF exposure. Annual CDI rates were calculated and evaluated by use of the χ2 test for trend and the χ2 summary test.Results.During the study period, there were significant increases in the overall incidence rates of HCF-onset, HCF-associated CDI (from 7.0 to 8.5 cases per 10,000 patient-days; P < .001); community-onset, HCF-associated CDI attributed to a study hospital (from 1.1 to 1.3 cases per 10,000 patient-days; P = .003); and community-onset, HCF-associated CDI not attributed to a study hospital (from 0.8 to 1.5 cases per 1,000 admissions overall; P < .001). For each surveillance definition of CDI, there were significant differences in the total incidence rate between HCFs.Conclusions.The increasing incidence rates of CDI over time and across healthcare institutions and the correlation of CDI incidence in different surveillance categories suggest that CDI may be a regional problem and not isolated to a single HCF within a community.

Assessment of Clostridium difficile–Associated Disease Surveillance Definitions, North Carolina, 2005

2008 ◽  
Vol 29 (3) ◽  
pp. 197-202 ◽  
Author(s):  
Preeta K. Kutty ◽  
Stephen R. Benoit ◽  
Christopher W. Woods ◽  
Arlene C. Sena ◽  
Susanna Naggie ◽  
...  
Keyword(s):  
North Carolina ◽  
Clostridium Difficile ◽  
Disease Surveillance ◽  
Retrospective Cohort ◽  
Healthcare Facility ◽  
Catchment Areas ◽  
Toxin Assay ◽  
Definition Of ◽  
Community Onset ◽  
Modest Correlation

Objective.To determine the timing of community-onset Clostridium difficile–associated disease (CDAD) relative to the patient's last healthcare facility discharge, the association of postdischarge cases with healthcare facility–onset cases, and the influence of postdischarge cases on overall rates and interhospital comparison of rates of CDAD.Design.Retrospective cohort study for the period January 1, 2005, through December 31, 2005.Setting.Catchment areas of 6 acute care hospitals in North Carolina.Methods.We reviewed medical and laboratory records to determine the date of symptom onset, the dates of hospitalization, and stool C. difficile toxin assay results for patients with CDAD who had diarrhea and positive toxin–assay results. Cases were classified as healthcare facility–onset if they were diagnosed more than 48 hours after admission. Cases were defined as community-onset if they were diagnosed in the community or within 48 hours after admission, and were also classified on the basis of the time since the last discharge: if within 4 weeks, community-onset, healthcare facility–associated (CO-HCFA); if 4-12 weeks, indeterminate exposure; and if more than 12 weeks, community-associated. Pearson's correlation coefficient was used to assess the association between monthly rates of healthcare facility–onset, healthcare facility–associated (HO-HCFA) cases and CO-HCFA cases. We performed interhospital rate comparisons using HO-HCFA cases only and using both HO-HCFA and CO-HCFA cases.Results.Of 1046 CDAD cases, 442 (42%) were HO-HCFA cases and 604 (58%) were community-onset cases. Of the 604 community-onset cases, 94 (15%) were CO-HCFA, 40 (7%) were of indeterminate exposure, and 208 (34%) community-associated. A modest correlation was found between monthly rates of HO-HCFA cases and CO-HCFA cases across the 6 hospitals (r = 0.63, P<.001). Interhospital rankings changed for 6 of 11 months if CO-HCFA cases were included.Conclusions.A substantial proportion of community-onset cases of CDAD occur less than 4 weeks after discharge from a healthcare facility, and inclusion of CO-HCFA cases influences interhospital comparisons. Our findings support the use of a proposed definition of healthcare facility–associated CDAD that includes cases that occur within 4 weeks after discharge.

scholarly journals Determinants of Clostridium difficile Infection Incidence Across Diverse United States Geographic Locations

2014 ◽  
Vol 1 (2) ◽  
Author(s):  
Fernanda C. Lessa ◽  
Yi Mu ◽  
Lisa G. Winston ◽  
Ghinwa K. Dumyati ◽  
Monica M. Farley ◽  
...  
Keyword(s):  
Clostridium Difficile ◽  
Clostridium Difficile Infection ◽  
Regression Models ◽  
Female Gender ◽  
Healthcare Facility ◽  
Geographic Area ◽  
Population Based ◽  
Older Age ◽  
Nucleic Acid Amplification ◽  
Active Population

Abstract Background.  Clostridium difficile infection (CDI) is no longer restricted to hospital settings, and population-based incidence measures are needed. Understanding the determinants of CDI incidence will allow for more meaningful comparisons of rates and accurate national estimates. Methods.  Data from active population- and laboratory-based CDI surveillance in 7 US states were used to identify CDI cases (ie, residents with positive C difficile stool specimen without a positive test in the prior 8 weeks). Cases were classified as community-associated (CA) if stool was collected as outpatients or ≤3 days of admission and no overnight healthcare facility stay in the past 12 weeks; otherwise, cases were classified as healthcare-associated (HA). Two regression models, one for CA-CDI and another for HA-CDI, were built to evaluate predictors of high CDI incidence. Site-specific incidence was adjusted based on the regression models. Results.  Of 10 062 cases identified, 32% were CA. Crude incidence varied by geographic area; CA-CDI ranged from 28.2 to 79.1/100 000 and HA-CDI ranged from 45.7 to 155.9/100 000. Independent predictors of higher CA-CDI incidence were older age, white race, female gender, and nucleic acid amplification test (NAAT) use. For HA-CDI, older age and a greater number of inpatient-days were predictors. After adjusting for relevant predictors, the range of incidence narrowed greatly; CA-CDI rates ranged from 30.7 to 41.3/100 000 and HA-CDI rates ranged from 58.5 to 94.8/100 000. Conclusions.  Differences in CDI incidence across geographic areas can be partially explained by differences in NAAT use, age, race, sex, and inpatient-days. Variation in antimicrobial use may contribute to the remaining differences in incidence.

scholarly journals Comparing the epidemiology of community- and hospital-associated Clostridium difficile infections in Northern Ireland, 2012–2016: a population data linkage and case–case study

2019 ◽  
Vol 147 ◽  
Author(s):  
A. Maisa ◽  
G. Ross ◽  
N.Q. Verlander ◽  
D. Fairley ◽  
D.T. Bradley ◽  
...  
Keyword(s):  
Risk Factors ◽  
Clostridium Difficile ◽  
Gastric Acid ◽  
Care Home ◽  
Multivariable Analysis ◽  
Population Data ◽  
Population Based ◽  
Lower Odds ◽  
Community Onset

AbstractThe burden of community-associated Clostridium difficile infection (CA-CDI) has increased. We aimed to describe the epidemiology of CA-CDI to inform future interventions. We used population-based linked surveillance data from 2012 to 2016 to describe socio-demographic factors, ribotype and mortality for all CA (n = 1303) and hospital-associated (HA, n = 1356) CDI. For 483 community-onset (CO) CA-CDI and 287 COHA-CDI cases, a questionnaire on risk factors was completed and we conducted a case–case study using logistic regression models for univariate and multivariable analysis. CA-CDI cases had lower odds of being male (adjusted odds ratio (AOR) 0.71, 95% confidence interval (CI) 0.58–0.87; P < 0.001), and higher odds of living in rural rather than urban settlement (AOR 1.5, 95% CI 1.1–2.1; P = 0.05) compared with HA-CDI cases. The distribution of ribotypes was similar in both groups with RT078 being most prevalent. CDI-specific death was lower in CA-CDI than HA-CDI (7% vs. 11%, P < 0.001). COCA-CDI had lower odds of having had an outpatient appointment in the previous 4 weeks compared with COHA-CDI (AOR 0.61; 95% CI 0.41–0.9, P = 0.01) and lower odds of being in a care home or hospice when compared with their own home, than COHA-CDI (AOR 0.66; 95% CI 0.45–0.98 and AOR 0.35; 95% CI 0.13–0.92, P = 0.02). Exposure to gastric acid suppressants (50% in COCA-CDI and 55% in COHA-CDI) and antimicrobial therapy (18% in COCA-CDI and 20% in COHA-CDI) prior to CDI was similar. Our analysis of community-onset cases suggests that other risk factors for COHA-CDI may be equally important for COCA-CDI. Opportunities to safely reduce antibiotic and gastric acid suppressants use should be investigated in all healthcare settings.

Automated Surveillance of Clostridium difficile Infections Using BioSense

2011 ◽  
Vol 32 (1) ◽  
pp. 26-33 ◽  
Author(s):  
Stephen R. Benoit ◽  
L. Clifford McDonald ◽  
Roseanne English ◽  
Jerome I. Tokars
Keyword(s):  
Clostridium Difficile ◽  
Surveillance System ◽  
Laboratory Data ◽  
Public Health Importance ◽  
Multicenter Cohort Study ◽  
Administrative Records ◽  
Disease Rates ◽  
Automated Surveillance ◽  
Toxin Assay ◽  
Community Onset

Objective.To determine the feasibility of using electronic laboratory and admission-discharge-transfer data from BioSense, a national automated surveillance system, to apply new modified Clostridium difficile infection (CDI) surveillance definitions and calculate overall and facility-specific rates of disease.Design.Retrospective, multicenter cohort study.Setting.Thirty-four hospitals sending inpatient, emergency department, and /or outpatient data to BioSense.Methods.Laboratory codes and text-parsing methods were used to extract C. difficile-positive toxin assay results from laboratory data sent to BioSense during the period from January 1, 2007, through June 30, 2008; these were merged with administrative records to determine whether cases were community associated or healthcare onset, as well as patient-day data for rate calculations. A patient was classified as having hospital-onset CDI if he or she had a C. difficile toxin-positive result on a stool sample collected 3 or more days after admission and community-onset CDI if the specimen was collected less than 3 days after admission or the patient was not hospitalized.Results.A total of 4,585 patients from 34 hospitals in 12 states had C. difficile-positive assay results. More than half (53.0%) of the cases were community-onset, and 30.8% of these occurred in patients who were recently hospitalized. The overall rate of healthcare-onset CDI was 7.8 cases per 10,000 patient-days, with a range among facilities of 1.5-27.8 cases per 10,000 patient-days.Conclusions.Electronic laboratory data sent to the BioSense surveillance system were successfully used to produce disease rates of CDI comparable to those of other studies, which shows the feasibility of using electronic laboratory data to track a disease of public health importance.

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