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Background: Inappropriate Clostridioides difficile testing has adverse consequences for patients, hospitals, and public health. Computerized clinical decision support (CCDS) systems in the electronic health record (EHR) may reduce C. difficile test ordering; however, effectiveness of different approaches, ease of use, and best fit into healthcare providers' (HCP) workflow are not well understood., Methods: Nine academic and 6 community hospitals in the United States participated in this 2-year cohort study. CCDS (hard stop or soft stop) triggered when a duplicate C. difficile test order was attempted or if laxatives were recently received. The primary outcome was the difference in testing rates pre- and post-CCDS interventions, using incidence rate ratios (IRRs) and mixed-effect Poisson regression models. We performed qualitative evaluation (contextual inquiry, interviews, focus groups) based on a human factors model. We identified themes using a codebook with primary nodes and subnodes., Results: In 9 hospitals implementing hard-stop CCDS and 4 hospitals implementing soft-stop CCDS, C. difficile testing incidence rate (IR) reduction was 33% (95% confidence interval [CI]: 30%-36%) and 23% (95% CI: 21%-25%), respectively. Two hospitals implemented a non-EHR-based human intervention with IR reduction of 21% (95% CI: 15%-28%). HCPs reported generally favorable experiences and highlighted time efficiencies such as inclusion of the patient's most recent laxative administration on the CCDS. Organizational factors, including hierarchical cultures and communication between HCPs caring for the same patient, impact CCDS acceptance and integration., Conclusions: CCDS systems reduced unnecessary C. difficile testing and were perceived positively by HCPs when integrated into their workflow and when displaying relevant patient-specific information needed for decision making., Competing Interests: Potential conflicts of interest. D. J. D. reports a grant to his institution for a clinical trial of new susceptibility test systems from bioMérieux, outside of the conduct of the study; payment for consulting on novel diagnostics from OpGen; and payment for consulting on antimicrobial resistance surveillance studies from JMI Laboratories. A. P. G. reports grants or contracts from the Agency for Healthcare Research and Quality (AHRQ), the CDC, and the National Institutes of Health (NIH), outside of the conduct of the study; payment for lecture from the North Carolina Health Association; and Human Factors and Ergonomics Society Executive Council. J. J. reports royalties from UpToDate. D. J. M. reports grant funding to support infection prevention and medical decision making research from the CDC, NIH, AHRQ, and the Veterans Affairs Health Services Research and Development Service, and reimbursement for travel related to meeting planning on speaking at meetings from the Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America. All other authors report no potential conflicts of interest. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed., (© The Author(s) 2022. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)

Background: Although clinical factors affecting a person's susceptibility to Clostridium difficile infection are well-understood, little is known about what drives differences in incidence across long-term care settings., Objective: To obtain a comprehensive picture of individual and regional factors that affect C difficile incidence., Design: Multilevel longitudinal nested case-control study., Setting: Veterans Health Administration health care regions, from 2006 through 2012., Participants: Long-term care residents., Measurements: Individual-level risk factors included age, number of comorbid conditions, and antibiotic exposure. Regional risk factors included importation of cases of acute care C difficile infection per 10 000 resident-days and antibiotic use per 1000 resident-days. The outcome was defined as a positive result on a long-term care C difficile test without a positive result in the prior 8 weeks., Results: 6012 cases (incidence, 3.7 cases per 10 000 resident-days) were identified in 86 regions. Long-term care C difficile incidence (minimum, 0.6 case per 10 000 resident-days; maximum, 31.0 cases per 10 000 resident-days), antibiotic use (minimum, 61.0 days with therapy per 1000 resident-days; maximum, 370.2 days with therapy per 1000 resident-days), and importation (minimum, 2.9 cases per 10 000 resident-days; maximum, 341.3 cases per 10 000 resident-days) varied substantially across regions. Together, antibiotic use and importation accounted for 75% of the regional variation in C difficile incidence (R2 = 0.75). Multilevel analyses showed that regional factors affected risk together with individual-level exposures (relative risk of regional antibiotic use, 1.36 per doubling [95% CI, 1.15 to 1.60]; relative risk of importation, 1.23 per doubling [CI, 1.14 to 1.33])., Limitations: Case identification was based on laboratory criteria. Admission of residents with recent C difficile infection from non-Veterans Health Administration acute care sources was not considered., Conclusion: Only 25% of the variation in regional C difficile incidence in long-term care remained unexplained after importation from acute care facilities and antibiotic use were accounted for, which suggests that improved infection control and antimicrobial stewardship may help reduce the incidence of C difficile in long-term care settings., Primary Funding Source: U.S. Department of Veterans Affairs and Centers for Disease Control and Prevention.

A commercial PCR assay of perirectal swab specimens detected 17 (68%) of 25 asymptomatic carriers of toxigenic Clostridium difficile, including 93% with skin and/or environmental contamination. A clinical prediction rule, followed by PCR screening, could be used to identify carriers at high risk of C. difficile shedding.

Objective: To assess Clostridium difficile infection (CDI)-related colectomy rates by CDI surveillance definitions and over time at multiple healthcare facilities., Setting: Five university-affiliated acute care hospitals in the United States., Design and Methods: Cases of CDI and patients who underwent colectomy from July 2000 through June 2006 were identified from 5 US tertiary care centers. Monthly CDI-related colectomy rates were calculated as the number of CDI-related colectomies per 1,000 CDI cases, and cases were categorized according to recommended surveillance definitions. Logistic regression was performed to evaluate risk factors for CDI-related colectomy., Results: In total, 8,569 cases of CDI were identified, and 75 patients underwent CDI-related colectomy. The overall colectomy rate was 8.7 per 1,000 CDI cases. The CDI-related colectomy rate ranged from 0 to 23 per 1,000 CDI episodes across hospitals. The colectomy rate for healthcare-facility-onset CDI was 4.3 per 1,000 CDI cases, and that for community-onset CDI was 16.5 per 1,000 CDI cases (P < .05). There were significantly more CDI-related colectomies at hospitals B and C (P < .05)., Conclusions: The overall CDI-related colectomy rate was low, and there was no significant change in the CDI-related colectomy rate over time. Onset of disease outside the study hospital was an independent risk factor for colectomy.

Background: US estimates of the Clostridium difficile infection (CDI) burden have utilized International Classification of Disease, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis codes. Whether ICD-9-CM code rank order affects CDI prevalence estimates is important because the National Hospital Discharge Survey (NHDS) and the Nationwide Inpatient Sample (NIS) have varying limits on the number of ICD-9-CM codes collected., Methods: ICD-9-CM codes for CDI (008.45), C. difficile toxin assay results, and dates of admission and discharge were collected from electronic hospital databases for adult patients admitted to 4 hospitals in the United States from July 2000 through June 2006. CDI prevalence per 1000 discharges was calculated and compared for NHDS and NIS limits and toxin assay results from the same hospitals. CDI prevalence estimates were compared using the χ(2) test, and the test of equality was used to compare slopes., Results: CDI prevalence measured by NIS criteria was significantly higher than that measured using NHDS criteria (10.7 cases per 1000 discharges versus 9.4 cases per 1000 discharges; P<.001) in the 4 hospitals. CDI prevalence measured by toxin assay results was 9.4 cases per 1000 discharges (P=.57 versus NHDS). However, the CDI prevalence increased more rapidly over time when measured according to the NHDS criteria than when measured according to toxin assay results (β=1.09 versus 0.84; P=.008)., Conclusions: Compared with the NHDS definition, the NIS definition captured 12% more CDI cases and reported significantly higher CDI rates. Rates calculated using toxin assay results were not different from rates calculated using NHDS criteria, but CDI prevalence appeared to increase more rapidly when measured by NHDS criteria than when measured by toxin assay results., (© The Author 2011. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved.)

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 chi(2) test for trend and the chi(2) 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.

Objective: To compare incidence of hospital-onset Clostridium difficile infection (CDI) measured by the use of International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) discharge diagnosis codes with rates measured by the use of electronically available C. difficile toxin assay results., Methods: Cases of hospital-onset CDI were identified at 5 US hospitals during the period from July 2000 through June 2006 with the use of 2 surveillance definitions: positive toxin assay results (gold standard) and secondary ICD-9-CM discharge diagnosis codes for CDI. The chi(2) test was used to compare incidence, linear regression models were used to analyze trends, and the test of equality was used to compare slopes., Results: Of 8,670 cases of hospital-onset CDI, 38% were identified by the use of both toxin assay results and the ICD-9-CM code, 16% by the use of toxin assay results alone, and 45% by the use of the ICD-9-CM code alone. Nearly half (47%) of cases of CDI identified by the use of a secondary diagnosis code alone were community-onset CDI according to the results of the toxin assay. The rate of hospital-onset CDI found by use of ICD-9-CM codes was significantly higher than the rate found by use of toxin assay results overall (P < .001), as well as individually at 3 of the 5 hospitals (P < .001 for all). The agreement between toxin assay results and the presence of a secondary ICD-9-CM diagnosis code for CDI was moderate, with an overall kappa value of 0.509 and hospital-specific kappa values of 0.489-0.570. Overall, the annual increase in CDI incidence was significantly greater for rates determined by the use of ICD-9-CM codes than for rates determined by the use of toxin assay results (P = .006)., Conclusions: Although the ICD-9-CM code for CDI seems to be adequate for measuring the overall CDI burden, use of the ICD-9-CM discharge diagnosis code for CDI, without present-on-admission code assignment, is not an acceptable surrogate for surveillance for hospital-onset CDI.

Objective: To evaluate the impact of cases of community-onset, healthcare facility (HCF)-associated Clostridium difficile infection (CDI) on the incidence and outbreak detection of CDI., Design: A retrospective multicenter cohort study., Setting: Five university-affiliated, acute care HCFs in the United States., Methods: We collected data (including results of C. difficile toxin assays of stool samples) on all of the adult patients admitted to the 5 hospitals during the period from July 1, 2000, through June 30, 2006. CDI cases were classified as HCF-onset if they were diagnosed more than 48 hours after admission or as community-onset, HCF-associated if they were diagnosed within 48 hours after admission and if the patient had recently been discharged from the HCF. Four surveillance definitions were compared: cases of HCF-onset CDI only (hereafter referred to as HCF-onset CDI) and cases of HCF-onset and community-onset, HCF-associated CDI diagnosed within 30, 60, and 90 days after the last discharge from the study hospital (hereafter referred to as 30-day, 60-day, and 90-day CDI, respectively). Monthly CDI rates were compared. Control charts were used to identify potential CDI outbreaks., Results: The rate of 30-day CDI was significantly higher than the rate of HCF-onset CDI at 2 HCFs (P < .01). The rates of 30-day CDI were not statistically significantly different from the rates of 60-day or 90-day CDI at any HCF. The correlations between each HCF's monthly rates of HCF-onset CDI and 30-day CDI were almost perfect (rho range, 0.94-0.99; P < .001). Overall, 12 time points had a CDI rate that was more than 3 standard deviations above the mean, including 11 time points identified using the definition for HCF-onset CDI and 9 time points identified using the definition for 30-day CDI, with discordant results at 4 time points ((kappa = 0.794; P < .001)., Conclusions: Tracking cases of both community-onset and HCF-onset, HCF-associated CDI captures significantly more CDI cases, but surveillance of HCF-onset, HCF-associated CDI alone is sufficient to detect an outbreak.

BackgroundDrivers of differences in Clostridium difficile incidence across acute and long-term care facilities are poorly understood. We sought to obtain a comprehensive picture of C. difficile incidence and risk factors in acute and long-term care.MethodsWe conducted a case-cohort study of persons spending at least 3 days in one of 131 acute care or 120 long-term care facilities managed by the United States Veterans Health Administration between 2006 and 2012. Patient (n = 8) and facility factors (n = 5) were included in analyses. The outcome was the incidence of facility-onset laboratory-identified C. difficile infection (CDI), defined as a person with a positive C. difficile test without a positive test in the prior 8 weeks.ResultsCDI incidence in acute care was 5 times that observed in long-term care (median, 15.6 vs 3.2 per 10000 person-days). History of antibiotic use was greater in acute care compared to long-term care (median, 739 vs 513 per 1000 person-days) and explained 72% of the variation in C. difficile rates. Importation of C. difficile cases (acute care: patients with recent long-term care attributable infection; long-term care: residents with recent acute care attributable infection) was 3 times higher in long-term care as compared to acute care (median, 52.3 vs 16.2 per 10000 person-days).ConclusionsFacility-level antibiotic use was the main factor driving differences in CDI incidence between acute and long-term care. Importation of acute care C. difficile cases was a greater concern for long-term care as compared to importation of long-term care cases for acute care.

Background Environmental contamination is an important source of hospital multidrug-resistant organism (MDRO) transmission. Factors such as patient MDRO contact precautions (CP) status, patient proximity to surfaces, and unit type likely influence MDRO contamination and bacterial bioburden levels on patient room surfaces. Identifying factors associated with environmental contamination in patient rooms and on shared unit surfaces could help identify important environmental MDRO transmission routes. Methods Surfaces were sampled from MDRO CP and non-CP rooms, nursing stations, and mobile equipment in acute care, intensive care, and transplant units within 6 acute care hospitals using a convenience sampling approach blinded to cleaning events. Precaution rooms had patients with clinical or surveillance tests positive for methicillin-resistant Staphylococcus aureus , vancomycin-resistant enterococci, carbapenem-resistant Enterobacteriaceae or Acinetobacter within the previous 6 months, or Clostridioides difficile toxin within the past 30 days. Rooms not meeting this definition were considered non-CP rooms. Samples were cultured for the above MDROs and total bioburden. Results Overall, an estimated 13% of rooms were contaminated with at least 1 MDRO. MDROs were detected more frequently in CP rooms (32% of 209 room-sample events) than non-CP rooms (12% of 234 room-sample events). Surface bioburden did not differ significantly between CP and non-CP rooms or MDRO-positive and MDRO-negative rooms. Conclusions CP room surfaces are contaminated more frequently than non-CP room surfaces; however, contamination of non-CP room surfaces is not uncommon and may be an important reservoir for ongoing MDRO transmission. MDRO contamination of non-CP rooms may indicate asymptomatic patient MDRO carriage, inadequate terminal cleaning, or cross-contamination of room surfaces via healthcare personnel hands. [ABSTRACT FROM AUTHOR]