Rebekah W. Moehring

Enhanced terminal room disinfection and acquisition and infection caused by multidrug-resistant organisms and Clostridium difficile (the Benefits of Enhanced Terminal Room Disinfection study): a cluster-randomised, multicentre, crossover study

BACKGROUND Patients admitted to hospital can acquire multidrug-resistant organisms and Clostridium difficile from inadequately disinfected environmental surfaces. We determined the effect of three enhanced strategies for terminal room disinfection (disinfection of a room between occupying patients) on acquisition and infection due to meticillin-resistant Staphylococcus aureus, vancomycin-resistant enterococci, C difficile, and multidrug-resistant Acinetobacter. METHODS We did a pragmatic, cluster-randomised, crossover trial at nine hospitals in the southeastern USA. Rooms from which a patient with infection or colonisation with a target organism was discharged were terminally disinfected with one of four strategies: reference (quaternary ammonium disinfectant except for C difficile, for which bleach was used); UV (quaternary ammonium disinfectant and disinfecting ultraviolet [UV-C] light except for C difficile, for which bleach and UV-C were used); bleach; and bleach and UV-C. The next patient admitted to the targeted room was considered exposed. Every strategy was used at each hospital in four consecutive 7-month periods. We randomly assigned the sequence of strategies for each hospital (1:1:1:1). The primary outcomes were the incidence of infection or colonisation with all target organisms among exposed patients and the incidence of C difficile infection among exposed patients in the intention-to-treat population. This trial is registered with ClinicalTrials.gov, NCT01579370. FINDINGS 31 226 patients were exposed; 21 395 (69%) met all inclusion criteria, including 4916 in the reference group, 5178 in the UV group, 5438 in the bleach group, and 5863 in the bleach and UV group. 115 patients had the primary outcome during 22 426 exposure days in the reference group (51·3 per 10 000 exposure days). The incidence of target organisms among exposed patients was significantly lower after adding UV to standard cleaning strategies (n=76; 33·9 cases per 10 000 exposure days; relative risk [RR] 0·70, 95% CI 0·50-0·98; p=0·036). The primary outcome was not statistically lower with bleach (n=101; 41·6 cases per 10 000 exposure days; RR 0·85, 95% CI 0·69-1·04; p=0·116), or bleach and UV (n=131; 45·6 cases per 10 000 exposure days; RR 0·91, 95% CI 0·76-1·09; p=0·303) among exposed patients. Similarly, the incidence of C difficile infection among exposed patients was not changed after adding UV to cleaning with bleach (n=38 vs 36; 30·4 cases vs 31·6 cases per 10 000 exposure days; RR 1·0, 95% CI 0·57-1·75; p=0·997). INTERPRETATION A contaminated health-care environment is an important source for acquisition of pathogens; enhanced terminal room disinfection decreases this risk. FUNDING US Centers for Disease Control and Prevention.

Rising Rates of Carbapenem-Resistant Enterobacteriaceae in Community Hospitals: A Mixed-Methods Review of Epidemiology and Microbiology Practices in a Network of Community Hospitals in the Southeastern United States

OBJECTIVE Describe the epidemiology of carbapenem-resistant Enterobacteriaceae (CRE) and examine the effect of lower carbapenem breakpoints on CRE detection. DESIGN Retrospective cohort. SETTING Inpatient care at community hospitals. PATIENTS All patients with CRE-positive cultures were included. METHODS CRE isolated from 25 community hospitals were prospectively entered into a centralized database from January 2008 through December 2012. Microbiology laboratory practices were assessed using questionnaires. RESULTS A total of 305 CRE isolates were detected at 16 hospitals (64%). Patients with CRE had symptomatic infection in 180 cases (59%) and asymptomatic colonization in the remainder (125 cases; 41%). Klebsiella pneumoniae (277 isolates; 91%) was the most prevalent species. The majority of cases were healthcare associated (288 cases; 94%). The rate of CRE detection increased more than fivefold from 2008 (0.26 cases per 100,000 patient-days) to 2012 (1.4 cases per 100,000 patient-days; incidence rate ratio (IRR), 5.3 [95% confidence interval (CI), 1.22-22.7]; P = .01). Only 5 hospitals (20%) had adopted the 2010 Clinical and Laboratory Standards Institute (CLSI) carbapenem breakpoints. The 5 hospitals that adopted the lower carbapenem breakpoints were more likely to detect CRE after implementation of breakpoints than before (4.1 vs 0.5 cases per 100,000 patient-days; P < .001; IRR, 8.1 [95% CI, 2.7-24.6]). Hospitals that implemented the lower carbapenem breakpoints were more likely to detect CRE than were hospitals that did not (3.3 vs 1.1 cases per 100,000 patient-days; P = .01). CONCLUSIONS The rate of CRE detection increased fivefold in community hospitals in the southeastern United States from 2008 to 2012. Despite this, our estimates are likely underestimates of the true rate of CRE detection, given the low adoption of the carbapenem breakpoints recommended in the 2010 CLSI guidelines.

Assessing the relative burden of hospital-acquired infections in a network of community hospitals.

Hospital-acquired infections (HAIs) occur commonly, cause significant harm to patients, and result in excess healthcare expenditures.1 The urinary tract is frequently cited as the most common site of HAI, but these estimates were extrapolated from National Nosocomial Infection Surveillance (NNIS) data from the 1990s.1 Updated information regarding the relative burden of specific types of HAIs would help governmental agencies and other stakeholders within the field of infection prevention to prioritize areas for research and innovation. The objective of our study was to assess the relative proportion of HAIs attributed to each of the following 5 types of infection in a network of community hospitals: catheter-associated urinary tract infection (CAUTI), surgical site infection (SSI), ventilator-associated pneumonia (VAP), central line–associated bloodstream infection (CLABSI), and Clostridium difficile infection (CDI). We performed a retrospective cohort study using prospectively collected HAI surveillance data from hospitals participating in the Duke Infection Control Outreach Network (DICON). DICON hospital epidemiologists and liaison infection preventionists work directly with local hospital infection preventionists to provide surveillance data validation, benchmarking, and infection prevention consultation services to participating hospitals.2 Fifteen DICON-affiliated community hospitals (median size, 186 beds; range, 50–457 beds) that had continuously collected hospital-wide and surgical surveillance data from January 1, 2010, through June 30, 2012, were included in the study. Infection preventionists at each hospital prospectively identified all HAIs occurring in intensive care unit (ICU) and non-ICU locations using standardized National Healthcare Safety Network (NHSN) surveillance definitions.3,4 All adult and pediatric cases of CLABSI, CAUTI, VAP, and hospital-onset healthcare facility–associated (HO-HCFA) CDI identified during the study period were included in the analysis. SSIs identified after 37 procedure types performed during the study period were included in this analysis if they met the following criteria: (1) surgery did not involve implanted material, and SSI occurred within 30 days; or (2) surgery involved implanted material, and SSI occurred within 90 days. The 30-month healthcare exposure period included 100,449 surgical procedures, 135,716 ICU inpatient-days, 1,596,277 non-ICU inpatient-days, 244,105 central line-days, 393,948 urinary catheter–days, and 53,352 ventilator-days. A total of 2,345 HAIs were identified. SSIs were the most common HAI (n = 882; 38%). The second most common HAI was CAUTI (n = 611; 26%), followed by HO-HCFA CDI (n = 514; 22%), CLABSI (n = 280; 12%), and VAP (n = 58; 2%). The median percentage of HAIs due to SSIs at each hospital was 43% (range, 16%–63%). SSIs were the most frequent HAI for 12 hospitals (80%). The proportion of HAIs due to SSIs was not related to surgical volume or the ratio between surgical and inpatient volume at individual hospitals (data not shown). The overall prevalence rate of SSI in our cohort was 0.82 infections per 100 operations. The most common surgical procedures to result in infections are shown in Table 1 and include colon surgery (90 SSIs; 2.6 SSIs per 100 operations), open herniorrhaphy (69 SSIs; 0.7 SSIs per 100 operations), knee replacement surgery (63 SSIs; 0.8 SSIs per 100 operations), and Cesarean delivery (63 SSIs; 0.9 SSIs per 100 operations). One-third of all identified SSIs (n = 316) were superficial-incisional. A total of 600 SSIs (68%) were identified at the time of hospital readmission. Only 169 SSIs (19%) were identified in the outpatient setting. The incidence rates of other HAIs were comparable to or lower than rates published by the NHSN5 and included 1.6 CAUTIs per 1,000 urinary catheter-days, 1.1 CLABSIs per 1,000 central line-days, 1.1 VAPs per 1,000 ventilator-days, and 3.0 cases of HO-HCFA per 10,000 inpatient-days. TABLE 1 Prevalence Rates of Surgical Site Infection (SSI) for Select Surgical Procedures, Duke Infection Control Outreach Network, January 1, 2010–June 30, 2012 SSIs were the most frequently observed HAI in this large cohort of community hospitals in the southeastern United States. This finding is remarkable, because the overall rate of SSI in this cohort was low. However, because the surgical volume in these hospitals was relatively high, the total burden of HAIs due to SSI exceeded that of other HAIs. Our large, multicenter study validates the results of other recent investigations. For example, SSIs were the most common HAI and accounted for 39% of all HAIs reported to the NHSN at a single academic medical center.6 In another study, SSIs accounted for 31% of the 58 HAIs identified during a point prevalence survey of 9 acute care hospitals in a single city.7 Our study has important limitations. First, our cohort included only community hospitals in one region of the United States. Thus, even though the majority of hospitals in the United States are similar in size to the hospitals in our cohort, our results may not be generalizable to all settings. Second, we suspect that our data underestimate the true frequency with which SSIs actually occur. SSIs occurring in outpatients are underrecognized by current SSI surveillance mechanisms. This is particularly important because more than 50% of all SSIs occur after hospital discharge.8 Additionally, because non-ventilator-associated pneumonias, non-catheter-associated UTIs, and SSIs after procedure types not reported to the NHSN were not included in this data analysis, we may have undercounted the actual burden of SSIs and other types of HAIs in this cohort of hospitals.6 We believe, however, that it is unlikely that any one specific HAI not included in our analysis occurs frequently enough to supplant SSIs as the most common HAI. SSIs are now the most common HAI in our community hospital network. We believe that our findings highlight the need for improved and expanded evidence-based interventions to effectively reduce the rate of SSIs in real-world settings. Collectively, the infection prevention community has already made substantial and important progress in reducing HAIs due to CLABSI and CAUTI in the past decade. It is time to shift our focus to finding better and new ways to prevent SSI.

Bloodstream infections in community hospitals in the 21st century: a multicenter cohort study.

Background While the majority of healthcare in the US is provided in community hospitals, the epidemiology and treatment of bloodstream infections in this setting is unknown. Methods and Findings We undertook this multicenter, retrospective cohort study to 1) describe the epidemiology of bloodstream infections (BSI) in a network of community hospitals and 2) determine risk factors for inappropriate therapy for bloodstream infections in community hospitals. 1,470 patients were identified as having a BSI in 9 community hospitals in the southeastern US from 2003 through 2006. The majority of BSIs were community-onset, healthcare associated (n = 823, 56%); 432 (29%) patients had community-acquired BSI, and 215 (15%) had hospital-onset, healthcare-associated BSI. BSIs due to multidrug-resistant pathogens occurred in 340 patients (23%). Overall, the three most common pathogens were S. aureus (n = 428, 28%), E. coli (n = 359, 24%), coagulase-negative Staphylococci (n = 148, 10%), though type of infecting organism varied by location of acquisition (e.g., community-acquired). Inappropriate empiric antimicrobial therapy was given to 542 (38%) patients. Proportions of inappropriate therapy varied by hospital (median = 33%, range 21–71%). Multivariate logistic regression identified the following factors independently associated with failure to receive appropriate empiric antimicrobial therapy: hospital where the patient received care (p<0.001), assistance with ≥3 ADLs (p = 0.005), Charlson score (p = 0.05), community-onset, healthcare-associated infection (p = 0.01), and hospital-onset, healthcare-associated infection (p = 0.02). Important interaction was observed between Charlson score and location of acquisition. Conclusions Our large, multicenter study provides the most complete picture of BSIs in community hospitals in the US to date. The epidemiology of BSIs in community hospitals has changed: community-onset, healthcare-associated BSI is most common, S. aureus is the most common cause, and 1 of 3 patients with a BSI receives inappropriate empiric antimicrobial therapy. Our data suggest that appropriateness of empiric antimicrobial therapy is an important and needed performance metric for physicians and hospital stewardship programs in community hospitals.

Observing and Improving Hand Hygiene Compliance: Implementation and Refinement of an Electronic-Assisted Direct-Observer Hand Hygiene Audit Program

We implemented a direct-observer hand hygiene audit program that used trained observers, wireless data entry devices, and an intranet portal. We improved the reliability and utility of the data by standardizing audit processes, regularly retraining auditors, developing an audit guidance tool, and reporting weighted composite hand hygiene compliance scores.

Impact of Change to Molecular Testing for Clostridium difficile Infection on Healthcare Facility–Associated Incidence Rates

BACKGROUND Change from nonmolecular to molecular testing techniques is thought to contribute to the increasing trend in incidence of Clostridium difficile infection (CDI); however the degree of effect attributed to this versus other time-related epidemiologic factors is unclear. METHODS We compared the relative change in incidence rate (IRR) of healthcare facility-associated (HCFA) CDI among hospitals in the Duke Infection Control Outreach Network before and after the date of switch from nonmolecular tests to polymerase chain reaction (PCR) using prospectively collected surveillance data from July 2009 to December 2011. Data from 10 hospitals that switched and 22 control hospitals were included. Individual hospital estimates were determined using Poisson regression. We used an interrupted time series approach to develop a Poisson mixed-effects model. Additional regression adjustments were made for clustering and proportion of intensive care unit patient-days. The variable for PCR was treated as a fixed effect; other modeled variables were random effects. RESULTS For those hospitals that switched to PCR, mean incidence rate of HCFA CDI before the switch was 6.0 CDIs per 10,000 patient-days compared with 9.6 CDIs per 10,000 patient-days after the switch. Estimates of hospital-specific IRR that compared after the switch with before the switch ranged from 0.89 (95% confidence interval [CI], 0.32-2.44) to 6.91 (95% CI, 1.12-42.54). After adjustment in the mixed-effects model, the overall IRR comparing CDI incidence after the switch to before the switch was 1.56 (95% CI, 1.28-1.90). Time-trend variables did not reach statistical significance. CONCLUSION Hospitals that switched from nonmolecular to molecular tests experienced an approximate 56% increase in the rate of HCFA CDI after testing change.

Hospital-acquired Clostridium difficile infections: estimating all-cause mortality and length of stay.

Background: Clostridium difficile is a health care–associated infection of increasing importance. The purpose of this study was to estimate the time until death from any cause and time until release among patients with C. difficile, comparing the burden of those in the intensive care unit (ICU) with those in the general hospital population. Methods: A parametric mixture model was used to estimate event times, as well as the case-fatality ratio in ICU and non-ICU patients within a cohort of 609 adult incident cases of C. difficile in the Southeastern United States between 1 July 2009 and 31 December 2010. Results: ICU patients had twice the median time to death (relative time = 1.97 [95% confidence interval (CI) = 0.96–4.01]) and nearly twice the median time to release (1.88 [1.40–2.51]) compared with non-ICU patients. ICU patients also experienced 3.4 times the odds of mortality (95% CI = 1.8–6.2). Cause-specific competing risks analysis underestimated the relative survival time until death (0.65 [0.36–1.17]) compared with the mixture model. Conclusions: Patients with C. difficile in the ICU experienced higher mortality and longer lengths of stay within the hospital. ICU patients with C. difficile infection represent a population in need of particular attention, both to prevent adverse patient outcomes and to minimize transmission of C. difficile to other hospitalized patients.

Epidemiology of methicillin-resistant Staphylococcus aureus pneumonia in community hospitals.

OBJECTIVE Describe the epidemiology of healthcare-related (ie, healthcare-associated and hospital-acquired) pneumonia due to methicillin-resistant Staphylococcus aureus (MRSA) among hospitalized patients in community hospitals. DESIGN Retrospective cohort study. SETTING Twenty-four community hospitals in the southeastern United States affiliated with the Duke Infection Control Outreach Network (median size, 211 beds; range, 103-658 beds). METHODS Adult patients with healthcare-related MRSA pneumonia admitted to study hospitals from January 1, 2008, to December 31, 2012, were identified using surveillance data. Seasonal and annual incidence rates (cases per 100,000 patient-days) were estimated using generalized estimating equation models. Characteristics of community-onset and hospital-onset cases were compared. RESULTS A total of 1,048 cases of healthcare-related pneumonia due to MRSA were observed during 5,863,941 patient-days. The annual incidence rate of healthcare-related MRSA pneumonia increased from 11.3 cases per 100,000 patient-days (95% confidence interval [CI], 6.8-18.7) in 2008 to 15.5 cases per 100,000 patient-days (95% CI, 8.4-28.5) in 2012 (P = .055). The incidence rate was highest in winter months and lowest in summer months (15.4 vs 11.1 cases per 100,000 patient-days; incidence rate ratio, 1.39 [95% CI, 1.06-1.82]; P = .016). A total of 814 cases (77.7%) were community-onset healthcare-associated pneumonia cases; only 49 cases (4.7%) were ventilator-associated cases. Of 811 patients whose disposition was known, 240 (29.6%) died during hospitalization or were discharged to hospice. CONCLUSIONS From 2008 through 2012, the incidence of healthcare-related MRSA pneumonia among patients who were admitted to a large network of community hospitals increased, despite the decreasing incidence of invasive MRSA infections nationwide. Additional study is warranted to evaluate trends in this important and potentially modifiable public health problem.

Seasonal Variation of Common Surgical Site Infections: Does Season Matter?

OBJECTIVE To evaluate seasonal variation in the rate of surgical site infections (SSI) following commonly performed surgical procedures. DESIGN Retrospective cohort study. METHODS We analyzed 6 years (January 1, 2007, through December 31, 2012) of data from the 15 most commonly performed procedures in 20 hospitals in the Duke Infection Control Outreach Network. We defined summer as July through September. First, we performed 3 separate Poisson regression analyses (unadjusted, multivariable, and polynomial) to estimate prevalence rates and prevalence rate ratios of SSI following procedures performed in summer versus nonsummer months. Then, we stratified our results to obtain estimates based on procedure type and organism type. Finally, we performed a sensitivity analysis to test the robustness of our findings. RESULTS We identified 4,543 SSI following 441,428 surgical procedures (overall prevalence rate, 1.03/100 procedures). The rate of SSI was significantly higher during the summer compared with the remainder of the year (1.11/100 procedures vs 1.00/100 procedures; prevalence rate ratio, 1.11 [95% CI, 1.04-1.19]; P=.002). Stratum-specific SSI calculations revealed higher SSI rates during the summer for both spinal (P=.03) and nonspinal (P=.004) procedures and revealed higher rates during the summer for SSI due to either gram-positive cocci (P=.006) or gram-negative bacilli (P=.004). Multivariable regression analysis and sensitivity analyses confirmed our findings. CONCLUSIONS The rate of SSI following commonly performed surgical procedures was higher during the summer compared with the remainder of the year. Summer SSI rates remained elevated after stratification by organism and spinal versus nonspinal surgery, and rates did not change after controlling for other known SSI risk factors.

A Mathematical Model to Evaluate the Routine Use of Fecal Microbiota Transplantation to Prevent Incident and Recurrent Clostridium difficile Infection

OBJECTIVE Fecal microbiota transplantation (FMT) has been suggested as a new treatment to manage Clostridium difficile infection (CDI). With use of a mathematical model of C. difficile within an intensive care unit (ICU), we examined the potential impact of routine FMT. DESIGN, SETTING, AND PATIENTS A mathematical model of C. difficile transmission, supplemented with prospective cohort, surveillance, and billing data from hospitals in the southeastern United States. METHODS Cohort, surveillance, and billing data as well as data from the literature were used to construct a compartmental model of CDI within an ICU. Patients were defined as being in 1 of 6 potential health states: uncolonized and at low risk; uncolonized and at high risk; colonized and at low risk; colonized and at high risk; having CDI; or treated with FMT. RESULTS The use of FMT to treat patients after CDI was associated with a statistically significant reduction in recurrence but not with a reduction in incident cases. Treatment after administration of high-risk medications, such as antibiotics, did not result in a decrease in recurrence but did result in a statistically significant difference in incident cases across treatment groups, although whether this difference was clinically relevant was questionable. CONCLUSIONS Our study is a novel mathematical model that examines the effect of FMT on the prevention of recurrent and incident CDI. The routine use of FMT represents a promising approach to reduce complex recurrent cases, but a reduction in CDI incidence will require the use of other methods to prevent transmission.