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ImportanceUrinary tract infection (UTI) is the second most common infection leading to hospitalization and is often associated with gram-negative multidrug-resistant organisms (MDROs). Clinicians overuse extended-spectrum antibiotics although most patients are at low risk for MDRO infection. Safe strategies to limit overuse of empiric antibiotics are needed.ObjectiveTo evaluate whether computerized provider order entry (CPOE) prompts providing patient- and pathogen-specific MDRO risk estimates could reduce use of empiric extended-spectrum antibiotics for treatment of UTI.Design, setting, and participantsCluster-randomized trial in 59 US community hospitals comparing the effect of a CPOE stewardship bundle (education, feedback, and real-time and risk-based CPOE prompts; 29 hospitals) vs routine stewardship (n = 30 hospitals) on antibiotic selection during the first 3 hospital days (empiric period) in noncritically ill adults (≥18 years) hospitalized with UTI with an 18-month baseline (April 1, 2017-September 30, 2018) and 15-month intervention period (April 1, 2019-June 30, 2020).InterventionsCPOE prompts recommending empiric standard-spectrum antibiotics in patients ordered to receive extended-spectrum antibiotics who have low estimated absolute risk (

ImportancePneumonia is the most common infection requiring hospitalization and is a major reason for overuse of extended-spectrum antibiotics. Despite low risk of multidrug-resistant organism (MDRO) infection, clinical uncertainty often drives initial antibiotic selection. Strategies to limit empiric antibiotic overuse for patients with pneumonia are needed.ObjectiveTo evaluate whether computerized provider order entry (CPOE) prompts providing patient- and pathogen-specific MDRO infection risk estimates could reduce empiric extended-spectrum antibiotics for non-critically ill patients admitted with pneumonia.Design, setting, and participantsCluster-randomized trial in 59 US community hospitals comparing the effect of a CPOE stewardship bundle (education, feedback, and real-time MDRO risk-based CPOE prompts; n = 29 hospitals) vs routine stewardship (n = 30 hospitals) on antibiotic selection during the first 3 hospital days (empiric period) in non-critically ill adults (≥18 years) hospitalized with pneumonia. There was an 18-month baseline period from April 1, 2017, to September 30, 2018, and a 15-month intervention period from April 1, 2019, to June 30, 2020.InterventionCPOE prompts recommending standard-spectrum antibiotics in patients ordered to receive extended-spectrum antibiotics during the empiric period who have low estimated absolute risk (

BackgroundDetection and containment of hospital outbreaks currently depend on variable and personnel-intensive surveillance methods. Whether automated statistical surveillance for outbreaks of health care-associated pathogens allows earlier containment efforts that would reduce the size of outbreaks is unknown.MethodsWe conducted a cluster-randomized trial in 82 community hospitals within a larger health care system. All hospitals followed an outbreak response protocol when outbreaks were detected by their infection prevention programs. Half of the hospitals additionally used statistical surveillance of microbiology data, which alerted infection prevention programs to outbreaks. Statistical surveillance was also applied to microbiology data from control hospitals without alerting their infection prevention programs. The primary outcome was the number of additional cases occurring after outbreak detection. Analyses assessed differences between the intervention period (July 2019 to January 2022) versus baseline period (February 2017 to January 2019) between randomized groups. A post hoc analysis separately assessed pre-coronavirus disease 2019 (Covid-19) and Covid-19 pandemic intervention periods.ResultsReal-time alerts did not significantly reduce the number of additional outbreak cases (intervention period versus baseline: statistical surveillance relative rate [RR]=1.41, control RR=1.81; difference-in-differences, 0.78; 95% confidence interval [CI], 0.40 to 1.52; P=0.46). Comparing only the prepandemic intervention with baseline periods, the statistical outbreak surveillance group was associated with a 64.1% reduction in additional cases (statistical surveillance RR=0.78, control RR=2.19; difference-in-differences, 0.36; 95% CI, 0.13 to 0.99). There was no similarly observed association between the pandemic versus baseline periods (statistical surveillance RR=1.56, control RR=1.66; difference-in-differences, 0.94; 95% CI, 0.46 to 1.92).ConclusionsAutomated detection of hospital outbreaks using statistical surveillance did not reduce overall outbreak size in the context of an ongoing pandemic. (Funded by the Centers for Disease Control and Prevention; ClinicalTrials.gov number, NCT04053075. Support for HCA Healthcare's participation in the study was provided in kind by HCA.).

ImportanceUniversal nasal mupirocin plus chlorhexidine gluconate (CHG) bathing in intensive care units (ICUs) prevents methicillin-resistant Staphylococcus aureus (MRSA) infections and all-cause bloodstream infections. Antibiotic resistance to mupirocin has raised questions about whether an antiseptic could be advantageous for ICU decolonization.ObjectiveTo compare the effectiveness of iodophor vs mupirocin for universal ICU nasal decolonization in combination with CHG bathing.Design, setting, and participantsTwo-group noninferiority, pragmatic, cluster-randomized trial conducted in US community hospitals, all of which used mupirocin-CHG for universal decolonization in ICUs at baseline. Adult ICU patients in 137 randomized hospitals during baseline (May 1, 2015-April 30, 2017) and intervention (November 1, 2017-April 30, 2019) were included.InterventionUniversal decolonization involving switching to iodophor-CHG (intervention) or continuing mupirocin-CHG (baseline).Main outcomes and measuresICU-attributable S aureus clinical cultures (primary outcome), MRSA clinical cultures, and all-cause bloodstream infections were evaluated using proportional hazard models to assess differences from baseline to intervention periods between the strategies. Results were also compared with a 2009-2011 trial of mupirocin-CHG vs no decolonization in the same hospital network. The prespecified noninferiority margin for the primary outcome was 10%.ResultsAmong the 801 668 admissions in 233 ICUs, the participants' mean (SD) age was 63.4 (17.2) years, 46.3% were female, and the mean (SD) ICU length of stay was 4.8 (4.7) days. Hazard ratios (HRs) for S aureus clinical isolates in the intervention vs baseline periods were 1.17 for iodophor-CHG (raw rate: 5.0 vs 4.3/1000 ICU-attributable days) and 0.99 for mupirocin-CHG (raw rate: 4.1 vs 4.0/1000 ICU-attributable days) (HR difference in differences significantly lower by 18.4% [95% CI, 10.7%-26.6%] for mupirocin-CHG, P

BackgroundNursing home residents are at high risk for infection, hospitalization, and colonization with multidrug-resistant organisms.MethodsWe performed a cluster-randomized trial of universal decolonization as compared with routine-care bathing in nursing homes. The trial included an 18-month baseline period and an 18-month intervention period. Decolonization entailed the use of chlorhexidine for all routine bathing and showering and administration of nasal povidone-iodine twice daily for the first 5 days after admission and then twice daily for 5 days every other week. The primary outcome was transfer to a hospital due to infection. The secondary outcome was transfer to a hospital for any reason. An intention-to-treat (as-assigned) difference-in-differences analysis was performed for each outcome with the use of generalized linear mixed models to compare the intervention period with the baseline period across trial groups.ResultsData were obtained from 28 nursing homes with a total of 28,956 residents. Among the transfers to a hospital in the routine-care group, 62.2% (the mean across facilities) were due to infection during the baseline period and 62.6% were due to infection during the intervention period (risk ratio, 1.00; 95% confidence interval [CI], 0.96 to 1.04). The corresponding values in the decolonization group were 62.9% and 52.2% (risk ratio, 0.83; 95% CI, 0.79 to 0.88), for a difference in risk ratio, as compared with routine care, of 16.6% (95% CI, 11.0 to 21.8; P

ObjectiveNational validation of claims-based surveillance for surgical-site infections (SSIs) following colon surgery and abdominal hysterectomy.DesignRetrospective cohort study.SettingUS hospitals selected for data validation by Centers for Medicare & Medicaid Services (CMS).ParticipantsThe study included 550 hospitals performing colon surgery and 458 hospitals performing abdominal hysterectomy in federal fiscal year 2013.MethodsWe requested 1,200 medical records from hospitals selected for validation as part of the CMS Hospital Inpatient Quality Reporting program. For colon surgery, we sampled 60% with a billing code suggestive of SSI during their index admission and/or readmission within 30 days and 40% who were readmitted without one of these codes. For abdominal hysterectomy, we included all patients with an SSI code during their index admission, all patients readmitted within 30 days, and a sample of those with a prolonged surgical admission (length of stay > 7 days). We calculated sensitivity and positive predictive value for the different groups.ResultsWe identified 142 colon-surgery SSIs (46 superficial SSIs and 96 deep and organ-space SSIs) and 127 abdominal-hysterectomy SSIs (58 superficial SSIs and 69 deep and organ-space SSIs). Extrapolating to the full CMS data validation cohort, we estimated an SSI rate of 8.3% for colon surgery and 3.0% for abdominal hysterectomy. Our colon-surgery surveillance codes identified 93% of SSIs, with 1 SSI identified for every 2.6 patients reviewed. Our abdominal-hysterectomy surveillance codes identified 73% of SSIs, with 1 SSI identified for every 1.6 patients reviewed.ConclusionsUsing claims to target record review for SSI validation performed well in a national sample.

ObjectiveTo compare strategies for hospital ranking based on colon surgical-site infection (SSI) rate by combining all colon procedures versus stratifying by surgical approach (ie, laparoscopic vs open).DesignRetrospective cohort study.MethodsWe identified SSIs among Medicare beneficiaries undergoing colon surgery from 2009 through 2013 using previously validated methods. We created a risk prediction model for SSI using age, sex, race, comorbidities, surgical approach (laparoscopy vs open), and concomitant colon and noncolon procedures. Adjusted SSI rates were used to rank hospitals. Subanalyses were performed for common colon procedures and procedure types for which there were both open and laparoscopic procedures. We generated ranks using only open and only laparoscopic procedures, overall and for each subanalysis. Rankings were compared using a Spearman correlation coefficient.ResultsIn total, 694,813 colon procedures were identified among 508,135 Medicare beneficiaries. The overall SSI rate was 7.6%. The laparoscopic approach was associated with lower SSI risk (OR, 0.5; 95% CI, 0.4-0.5), and higher SSI risk was associated with concomitant abdominal surgeries (OR, 1.4; 95% CI, 1.4-1.5) and higher Elixhauser score (OR, 1.1; 95% CI, 1.0-1.1). Hospital rankings for laparascopic procedures were poorly correlated with rankings for open procedures (r = 0.23).ConclusionsHospital rankings based on total colon procedures fail to account for differences in SSI risk from laparoscopic vs open procedures. Stratifying rankings by surgical approach yields a more equitable comparison of surgical performance.

BackgroundThe profound changes wrought by coronavirus disease 2019 (COVID-19) on routine hospital operations may have influenced performance on hospital measures, including healthcare-associated infections (HAIs). We aimed to evaluate the association between COVID-19 surges and HAI and cluster rates.MethodsIn 148 HCA Healthcare-affiliated hospitals, from 1 March 2020 to 30 September 2020, and a subset of hospitals with microbiology and cluster data through 31 December 2020, we evaluated the association between COVID-19 surges and HAIs, hospital-onset pathogens, and cluster rates using negative binomial mixed models. To account for local variation in COVID-19 pandemic surge timing, we included the number of discharges with a laboratory-confirmed COVID-19 diagnosis per staffed bed per month.ResultsCentral line-associated blood stream infections (CLABSI), catheter-associated urinary tract infections (CAUTI), and methicillin-resistant Staphylococcus aureus (MRSA) bacteremia increased as COVID-19 burden increased. There were 60% (95% confidence interval [CI]: 23-108%) more CLABSI, 43% (95% CI: 8-90%) more CAUTI, and 44% (95% CI: 10-88%) more cases of MRSA bacteremia than expected over 7 months based on predicted HAIs had there not been COVID-19 cases. Clostridioides difficile infection was not significantly associated with COVID-19 burden. Microbiology data from 81 of the hospitals corroborated the findings. Notably, rates of hospital-onset bloodstream infections and multidrug resistant organisms, including MRSA, vancomycin-resistant enterococcus, and Gram-negative organisms, were each significantly associated with COVID-19 surges. Finally, clusters of hospital-onset pathogens increased as the COVID-19 burden increased.ConclusionsCOVID-19 surges adversely impact HAI rates and clusters of infections within hospitals, emphasizing the need for balancing COVID-related demands with routine hospital infection prevention.

[This corrects the article DOI: 10.1371/journal.pone.0245064.].

Abstract Background The profound changes wrought by COVID-19 on routine hospital operations may have influenced performance on hospital measures, including healthcare-associated infections (HAIs). Objective Evaluate the association between COVID-19 surges and HAI or cluster rates Methods Design: Prospective cohort study Setting 148 HCA Healthcare-affiliated hospitals, 3/1/2020-9/30/2020, and a subset of hospitals with microbiology and cluster data through 12/31/2020 Patients All inpatients Measurements We evaluated the association between COVID-19 surges and HAIs, hospital-onset pathogens, and cluster rates using negative binomial mixed models. To account for local variation in COVID-19 pandemic surge timing, we included the number of discharges with a laboratory-confirmed COVID-19 diagnosis per staffed bed per month at each hospital. Results Central line-associated blood stream infections (CLABSI), catheter-associated urinary tract infections (CAUTI), and methicillin-resistant Staphylococcus aureus (MRSA) bacteremia increased as COVID-19 burden increased (P ≤ 0.001 for all), with 60% (95% CI, 23 to 108%) more CLABSI, 43% (95% CI, 8 to 90%) more CAUTI, and 44% (95% CI, 10 to 88%) more cases of MRSA bacteremia than expected over 7 months based on predicted HAIs had there not been COVID-19 cases. Clostridioides difficile infection (CDI) was not significantly associated with COVID-19 burden. Microbiology data from 81 of the hospitals corroborated the findings. Notably, rates of hospital-onset bloodstream infections and multidrug resistant organisms, including MRSA, vancomycin-resistant enterococcus and Gram-negative organisms were each significantly associated with COVID-19 surges (P < 0.05 for all). Finally, clusters of hospital-onset pathogens increased as the COVID-19 burden increased (P = 0.02). Limitations Variations in surveillance and reporting may affect HAI data. Table 1. Effect of an increase in number of COVID-19 discharges on HAIs and hospital-onset pathogens Figure 1. Predicted mean HAI rates as COVID-19 discharges increase Predicted mean HAI rate by increasing monthly COVID-19 discharges. Panel a. CLABSI, Panel b, CAUTI Panel c. MRSA Bacteremia, Panel d. CDI. Data are stratified by small, medium and large hospitals. Figure 2. Monthly comparison of COVID discharges to clusters COVID-19 discharges and the number of clusters of hospital-onset pathogens are correlated throughout the pandemic. Conclusion COVID-19 surges adversely impact HAI rates and clusters of infections within hospitals, emphasizing the need for balancing COVID-related demands with routine hospital infection prevention. Disclosures Kenneth Sands, MD, MPH, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Susan S. Huang, MD, MPH, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Stryker (Sage) (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Xttrium (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products) Ken Kleinman, PhD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products) Edward Septimus, MD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products) Eunice J. Blanchard, MSN RN, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Russell Poland, PhD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Micaela H. Coady, MS, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Deborah S. Yokoe, MD, MPH, Nothing to disclose Julia Moody, MS, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Richard Platt, MD, MSc, Medline (Research Grant or Support, Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Jonathan B. Perlin, MD, PhD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product)

Abstract Background Nursing home (NH) residents are at high infection and hospital readmission risk. Colonization with multidrug-resistant organisms (MDROs) is common. In ICU and post-hospital discharge settings, decolonization has reduced infection rates. However, the effectiveness of this strategy in NHs is unclear. Methods We performed a cluster randomized trial of 1:1 universal decolonization (decol) vs standard of care bathing (control) in 28 California NHs. After an 18 month baseline evaluation of hospitalization rates due to infection and MDRO prevalence, NHs were randomized to decol or control. Decol consisted of 1) chlorhexidine bathing; 2) nasal povidone iodine bid on admission x 5d and then M-F biweekly x 18 mo. Primary outcome was the probability that a transfer to a hospital was due to infection. Secondary outcome was the probability that a NH discharge was to a hospital. Results Four of 28 NHs dropped from the trial (3 decol, 1 control). Mean facility baseline of hospital transfers due to infection was 58% and 57% in the control and decol groups. In the intervention period, proportions were 57% and 48% in the control and decol groups. When accounting for clustering within NHs, hospital transfers due to infection had an OR of 0.91 (95% CI: 0.82-1.02) in the control group and an OR of 0.73 (95% CI: 0.56-0.95) in the decol group when comparing intervention to baseline period. For the primary outcome, decol had a 18% greater impact v. control (P=0.005, Fig. A). Baseline proportion of NH discharges due to hospitalization was 37% and 39% in the control and decol groups. In the intervention period, proportions were 36% and 33%. When accounting for clustering within NHs, the proportion of discharges due to hospitalization had an OR of 1.14 (95% CI: 1.06-1.22) in the control group and 0.91 (CI: 0.77-1.07) in the decol group when comparing the intervention period to the baseline period. For the secondary outcome, decol had a 23% greater impact v. control (P< 0.0001, Fig. B). In this figure, each nursing home is represented by a circle. The size of the circle represents the amount of contributed patient days to the trial. The groups represent “as randomized” categories. Panel A) compares the probability that a transfer to a hospital was due to infection; panel B) compares the probability that a nursing home discharge was to a hospital. The y-axis represents the odds ratio of these probabilities comparing the baseline to the intervention period. The p values represent the significance of the difference between groups (the trial effect). Conclusion Universal NH decolonization with chlorhexidine and nasal iodophor significantly reduced the proportion of transfers to hospitals due to infection and discharges due to hospitalization. Our findings suggest that NH decolonization reduces serious infections and can decrease morbidity in this vulnerable population. Disclosures Loren G. Miller, MD, MPH, Medline (Grant/Research Support, Other Financial or Material Support, Contributed product) Stryker (Other Financial or Material Support, Contributed product) Xttrium (Other Financial or Material Support, Contributed product) James A. McKinnell, MD, Medline (Grant/Research Support) Raveena Singh, MA, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products) Stryker (Sage) (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic products) Xttrium (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic products) Gabrielle Gussin, MS, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products) Stryker (Sage) (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic products) Xttrium (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic products) Ken Kleinman, PhD, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products) Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic products) Raheeb Saavedra, AS, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products) Stryker (Sage) (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic products) Xttrium (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic products) Lauren Heim, MPH, Medline (Other Financial or Material Support, Conducted clinical trials and studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products) Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals received contributed antiseptic product) Stryker (Sage) (Other Financial or Material Support, Conducted clinical trials and studies in which participating hospitals and nursing homes received contributed antiseptic product) Xttrium (Other Financial or Material Support, Conducted clinical trials and studies in which participating hospitals and nursing homes received contributed antiseptic product) Shruti K. Gohil, MD, MPH, Medline (Other Financial or Material Support, Co-Investigator in studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products) Molnycke (Other Financial or Material Support, Co-Investigator in studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products) Stryker (Sage) (Other Financial or Material Support, Co-Investigator in studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products) Susan S. Huang, MD, MPH, Medline (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products) Molnlycke (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products) Stryker (Sage) (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)Xttrium (Other Financial or Material Support, Conducted studies in which participating hospitals and nursing homes received contributed antiseptic and cleaning products)

BackgroundThe profound changes wrought by COVID-19 on routine hospital operations may have influenced performance on hospital measures, including healthcare-associated infections (HAIs). We aimed to evaluate the association between COVID-19 surges and HAI and cluster rates.MethodsIn 148 HCA Healthcare-affiliated hospitals, 3/1/2020-9/30/2020, and a subset of hospitals with microbiology and cluster data through 12/31/2020, we evaluated the association between COVID-19 surges and HAIs, hospital-onset pathogens, and cluster rates using negative binomial mixed models. To account for local variation in COVID-19 pandemic surge timing, we included the number of discharges with a laboratory-confirmed COVID-19 diagnosis per staffed bed per month.ResultsCentral line-associated blood stream infections (CLABSI), catheter-associated urinary tract infections (CAUTI), and methicillin-resistant Staphylococcus aureus (MRSA) bacteremia increased as COVID-19 burden increased. There were 60% (95% CI, 23-108%) more CLABSI, 43% (95% CI, 8-90%) more CAUTI, and 44% (95% CI, 10-88%) more cases of MRSA bacteremia than expected over 7 months based on predicted HAIs had there not been COVID-19 cases. Clostridioides difficile infection was not significantly associated with COVID-19 burden. Microbiology data from 81 of the hospitals corroborated the findings. Notably, rates of hospital-onset bloodstream infections and multidrug resistant organisms, including MRSA, vancomycin-resistant enterococcus and Gram-negative organisms were each significantly associated with COVID-19 surges. Finally, clusters of hospital-onset pathogens increased as the COVID-19 burden increased.ConclusionCOVID-19 surges adversely impact HAI rates and clusters of infections within hospitals, emphasizing the need for balancing COVID-related demands with routine hospital infection prevention.

In group or cluster-randomized trials (GRTs), matching is a technique that can be used to improve covariate balance. When baseline data are available, we suggest a strategy that can be used to achieve the desired balance between treatment and control groups across numerous potential confounding variables. This strategy minimizes the overall within-pair Mahalanobis distance; and involves iteratively: 1) making pairs that minimize the distance between pairs of clusters with respect to potentially confounding variables; 2) visually assessing the potential effects of these pairs and resulting possible randomizations; and 3) reweighting variables of selecting weights to make pairs of clusters. In step 2, we plot the between-arm differences with a parallel-coordinates plot. Investigators can compare plots of different weighting schemes to determine the one that best suits their needs prior to the actual, final, randomization. We demonstrate application of the approach with the Mupirocin-Iodophor Swap Out trial. A webapp is provided.

BackgroundPer- and polyfluoroalkyl substances (PFAS) are endocrine disrupting chemicals that have been associated with cardiovascular risk factors including elevated body weight and hypercholesterolemia. Therefore, PFAS may contribute to the development of atherosclerosis and cardiovascular disease (CVD). However, no previous study has evaluated associations between PFAS exposure and arterial calcification.Methods and resultsThis study used data from 666 prediabetic adults enrolled in the Diabetes Prevention Program trial who had six PFAS quantified in plasma at baseline and two years after randomization, as well as measurements of coronary artery calcium (CAC) and ascending (AsAC) and descending (DAC) thoracic aortic calcification 13-14 years after baseline. We performed multinomial regression to test associations between PFAS and CAC categorized according to Agatston score [low (400)]. We used logistic regression to assess associations between PFAS and presence of AsAC and DAC. We adjusted models for baseline sex, age, BMI, race/ethnicity, cigarette smoking, education, treatment assignment (placebo or lifestyle intervention), and statin use. PFAS concentrations were similar to national means; 53.9% of participants had CAC > 11, 7.7% had AsAC, and 42.6% had DAC. Each doubling of the mean sum of plasma concentrations of linear and branched isomers of perfluorooctane sulfonic acid (PFOS) was associated with 1.49-fold greater odds (95% CI: 1.01, 2.21) of severe versus low CAC. This association was driven mainly by the linear (n-PFOS) isomer [1.54 (95% CI: 1.05, 2.25) greater odds of severe versus low CAC]. Each doubling of mean plasma N-ethyl-perfluorooctane sulfonamido acetic acid concentration was associated with greater odds of CAC in a dose-dependent manner [OR = 1.26 (95% CI:1.08, 1.47) for moderate CAC and OR = 1.37 (95% CI:1.07, 1.74) for severe CAC, compared to low CAC)]. Mean plasma PFOS and n-PFOS were also associated with greater odds of AsAC [OR = 1.67 (95% CI:1.10, 2.54) and OR = 1.70 (95% CI:1.13, 2.56), respectively], but not DAC. Other PFAS were not associated with outcomes.ConclusionsPrediabetic adults with higher plasma concentrations of select PFAS had higher risk of coronary and thoracic aorta calcification. PFAS exposure may be a risk factor for adverse cardiovascular health among high-risk populations.

Preterm birth occurs at excessively high and disparate rates in the United States. In 2016, the National Institutes of Health (NIH) launched the Environmental influences on Child Health Outcomes (ECHO) program to investigate the influence of early life exposures on child health. Extant data from the ECHO cohorts provides the opportunity to examine racial and geographic variation in effects of individual- and neighborhood-level markers of socioeconomic status (SES) on gestational age at birth. The objective of this study was to examine the association between individual-level (maternal education) and neighborhood-level markers of SES and gestational age at birth, stratifying by maternal race/ethnicity, and whether any such associations are modified by US geographic region. Twenty-six ECHO cohorts representing 25,526 mother-infant pairs contributed to this disseminated meta-analysis that investigated the effect of maternal prenatal level of education (high school diploma, GED, or less; some college, associate's degree, vocational or technical training [reference category]; bachelor's degree, graduate school, or professional degree) and neighborhood-level markers of SES (census tract [CT] urbanicity, percentage of black population in CT, percentage of population below the federal poverty level in CT) on gestational age at birth (categorized as preterm, early term, full term [the reference category], late, and post term) according to maternal race/ethnicity and US region. Multinomial logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CIs). Cohort-specific results were meta-analyzed using a random effects model. For women overall, a bachelor's degree or above, compared with some college, was associated with a significantly decreased odds of preterm birth (aOR 0.72; 95% CI: 0.61-0.86), whereas a high school education or less was associated with an increased odds of early term birth (aOR 1.10, 95% CI: 1.00-1.21). When stratifying by maternal race/ethnicity, there were no significant associations between maternal education and gestational age at birth among women of racial/ethnic groups other than non-Hispanic white. Among non-Hispanic white women, a bachelor's degree or above was likewise associated with a significantly decreased odds of preterm birth (aOR 0.74 (95% CI: 0.58, 0.94) as well as a decreased odds of early term birth (aOR 0.84 (95% CI: 0.74, 0.95). The association between maternal education and gestational age at birth varied according to US region, with higher levels of maternal education associated with a significantly decreased odds of preterm birth in the Midwest and South but not in the Northeast and West. Non-Hispanic white women residing in rural compared to urban CTs had an increased odds of preterm birth; the ability to detect associations between neighborhood-level measures of SES and gestational age for other race/ethnic groups was limited due to small sample sizes within select strata. Interventions that promote higher educational attainment among women of reproductive age could contribute to a reduction in preterm birth, particularly in the US South and Midwest. Further individual-level analyses engaging a diverse set of cohorts are needed to disentangle the complex interrelationships among maternal education, neighborhood-level factors, exposures across the life course, and gestational age at birth outcomes by maternal race/ethnicity and US geography.

ObjectiveDetermine the prevalence of methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant Enterococcus spp. (VRE), extended-spectrum beta-lactamase producing organisms (ESBLs), and carbapenem-resistant Enterobacteriaceae (CRE) among residents and in the environment of nursing homes (NHs).DesignPoint prevalence sampling of residents and environmental sampling of high-touch objects in resident rooms and common areas.SettingTwenty-eight NHs in Southern California from 2016 to 2017.ParticipantsNH participants in Project PROTECT, a cluster-randomized trial of enhanced bathing and decolonization vs routine care.MethodsFifty residents were randomly sampled per NH. Twenty objects were sampled, including 5 common room objects plus 5 objects in each of 3 rooms (ambulatory, total care, and dementia care residents).ResultsA total of 2797 swabs were obtained from 1400 residents in 28 NHs. Median prevalence of multidrug-resistant organism (MDRO) carriage per NH was 50% (range: 24%-70%). Median prevalence of specific MDROs were as follows: MRSA, 36% (range: 20%-54%); ESBL, 16% (range: 2%-34%); VRE, 5% (range: 0%-30%); and CRE, 0% (range: 0%-8%). A median of 45% of residents (range: 24%-67%) harbored an MDRO without a known MDRO history. Environmental MDRO contamination was found in 74% of resident rooms and 93% of common areas.Conclusions and implicationsIn more than half of the NHs, more than 50% of residents were colonized with MDROs of clinical and public health significance, most commonly MRSA and ESBL. Additionally, the vast majority of resident rooms and common areas were MDRO contaminated. The unknown submerged portion of the iceberg of MDRO carriers in NHs may warrant changes to infection prevention and control practices, particularly high-fidelity adoption of universal strategies such as hand hygiene, environmental cleaning, and decolonization.

Background: Addressing the high burden of multidrug-resistant organisms (MDROs) in nursing homes is a public health priority. High interfacility transmission may be attributed to inadequate infection prevention practices, shared living spaces, and frequent care needs. We assessed the contribution of roommates to the likelihood of MDRO carriage in nursing homes. Methods: We performed a secondary analysis of the SHIELD OC (Shared Healthcare Intervention to Eliminate Life-threatening Dissemination of MDROs in Orange County, CA) Project, a CDC-funded regional decolonization intervention to reduce MDROs among 38 regional facilities (18 nursing homes, 3 long-term acute-care hospitals, and 17 hospitals). Decolonization in participating nursing homes involved routine chlorhexidine bathing plus nasal iodophor (Monday through Friday, twice daily every other week) from April 2017 through July 2019. MDRO point-prevalence assessments involving all residents at 16 nursing homes conducted at the end of the intervention period were used to determine whether having a roommate was associated with MDRO carriage. Nares, bilateral axilla/groin, and perirectal swabs were processed for methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant enterococcus (VRE), extended-spectrum β-lactamase (ESBL)–producing Enterobacteriaceae, and carbapenem-resistant Enterobacteriaceae (CRE). Generalized linear mixed models assessed the impact of maximum room occupancy on MDRO prevalence when clustering by room and hallway, and adjusting for the following factors: nursing home facility, age, gender, length-of-stay at time of swabbing, bedbound status, known MDRO history, and presence of urinary or gastrointestinal devices. CRE models were not run due to low counts. Results: During the intervention phase, 1,451 residents were sampled across 16 nursing homes. Overall MDRO prevalence was 49%. In multivariable models, we detected a significant increasing association of maximum room occupants and MDRO carriage for MRSA but not other MDROs. For MRSA, the adjusted odds ratios for quadruple-, triple-, and double-occupancy rooms were 3.5, 3.6, and 2.8, respectively, compared to residents in single rooms (P = .013). For VRE, these adjusted odds ratios were 0.3, 0.3, and 0.4, respectively, compared to residents in single rooms (P = NS). For ESBL, the adjusted odds ratios were 0.9, 1.1, and 1.5, respectively, compared to residents in single rooms (P = nonsignificant). Conclusions: Nursing home residents in shared rooms were more likely to harbor MRSA, suggesting MRSA transmission between roommates. Although decolonization was previously shown to reduce MDRO prevalence by 22% in SHIELD nursing homes, this strategy did not appear to prevent all MRSA transmission between roommates. Additional efforts involving high adherence hand hygiene, environmental cleaning, and judicious use of contact precautions are likely needed to reduce transmission between roommates in nursing homes. Funding: None Disclosures: Gabrielle M. Gussin, Stryker (Sage Products): Conducting studies in which contributed antiseptic product is provided to participating hospitals and nursing homes. Clorox: Conducting studies in which contributed antiseptic product is provided to participating hospitals and nursing homes. Medline: Conducting studies in which contributed antiseptic product is provided to participating hospitals and nursing homes. Xttrium: Conducting studies in which contributed antiseptic product is provided to participating hospitals and nursing homes.

Distinguished Oral Background: Shared Healthcare Intervention to Eliminate Life-threatening Dissemination of MDROs in Orange County, California (SHIELD OC) was a CDC-funded regional decolonization intervention from April 2017 through July 2019 involving 38 hospitals, nursing homes (NHs), and long-term acute-care hospitals (LTACHs) to reduce MDROs. Decolonization in NH and LTACHs consisted of universal antiseptic bathing with chlorhexidine (CHG) for routine bathing and showering plus nasal iodophor decolonization (Monday through Friday, twice daily every other week). Hospitals used universal CHG in ICUs and provided daily CHG and nasal iodophor to patients in contact precautions. We sought to evaluate whether decolonization reduced hospitalization and associated healthcare costs due to infections among residents of NHs participating in SHIELD compared to nonparticipating NHs. Methods: Medicaid insurer data covering NH residents in Orange County were used to calculate hospitalization rates due to a primary diagnosis of infection (counts per member quarter), hospital bed days/member-quarter, and expenditures/member quarter from the fourth quarter of 2015 to the second quarter of 2019. We used a time-series design and a segmented regression analysis to evaluate changes attributable to the SHIELD OC intervention among participating and nonparticipating NHs. Results: Across the SHIELD OC intervention period, intervention NHs experienced a 44% decrease in hospitalization rates, a 43% decrease in hospital bed days, and a 53% decrease in Medicaid expenditures when comparing the last quarter of the intervention to the baseline period (Fig. 1). These data translated to a significant downward slope, with a reduction of 4% per quarter in hospital admissions due to infection (P < .001), a reduction of 7% per quarter in hospitalization days due to infection (P < .001), and a reduction of 9% per quarter in Medicaid expenditures (P = .019) per NH resident. Conclusions: The universal CHG bathing and nasal decolonization intervention adopted by NHs in the SHIELD OC collaborative resulted in large, meaningful reductions in hospitalization events, hospitalization days, and healthcare expenditures among Medicaid-insured NH residents. The findings led CalOptima, the Medicaid provider in Orange County, California, to launch an NH incentive program that provides dedicated training and covers the cost of CHG and nasal iodophor for OC NHs that enroll. Funding: None Disclosures: Gabrielle M. Gussin, University of California, Irvine, Stryker (Sage Products): Conducting studies in which contributed antiseptic product is provided to participating hospitals and nursing homes. Clorox: Conducting studies in which contributed antiseptic product is provided to participating hospitals and nursing homes. Medline: Conducting studies in which contributed antiseptic product is provided to participating hospitals and nursing homes. Xttrium: Conducting studies in which contributed antiseptic product is provided to participating hospitals and nursing homes.

OBJECTIVE: To assess the utility of an automated, statistically-based outbreak detection system to identify clusters of hospital-acquired microorganisms. DESIGN: Multicenter retrospective cohort study. SETTING: The study included 43 hospitals using a common infection prevention surveillance system. METHODS: A space-time permutation scan statistic was applied to hospital microbiology, admission, discharge, and transfer data to identify clustering of microorganisms within hospital locations and services. Infection preventionists were asked to rate the importance of each cluster. A convenience sample of 10 hospitals also provided information about clusters previously identified through their usual surveillance methods. RESULTS: We identified 230 clusters in 43 hospitals involving Gram-positive and -negative bacteria and fungi. Half of the clusters progressed after initial detection, suggesting that early detection could trigger interventions to curtail further spread. Infection preventionists reported that they would have wanted to be alerted about 81% of these clusters. Factors associated with clusters judged to be moderately or highly concerning included high statistical significance, large size, and clusters involving Clostridioides difficile or multidrug-resistant organisms. Based on comparison data provided by the convenience sample of hospitals, only 9 (18%) of 51 clusters detected by usual surveillance met statistical significance, and of the 70 clusters not previously detected, 58 (83%) involved organisms not routinely targeted by the hospitals surveillance programs. All infection prevention programs felt that an automated outbreak detection tool would improve their ability to detect outbreaks and streamline their work. CONCLUSIONS: Automated, statistically-based outbreak detection can increase the consistency, scope, and comprehensiveness of detecting hospital-associated transmission.

Importance:Colon surgery is associated with a high rate of surgical site infection (SSI), and there is an urgent need for strategies to reduce infection rates. Objective:To assess whether laparoscopic colon surgery is associated with a lower surgical site infection rate than open-approach laparoscopy, especially in patients with medically complex conditions. Design, Setting, and Participants:This cohort study used previously validated diagnosis and procedure codes from Medicare beneficiaries who underwent colon surgery from January 1, 2009, to November 30, 2013. Analyses were performed from August 1 to December 31, 2018. Main Outcomes and Measures:Outcome measures were SSI events, medical comorbidities, and laparoscopic or open approach procedures. Results:A total of 229 726 patients (mean [SD] age, 74.3 [9.4] years; 128 499 [55.9%] female) underwent colon procedures. There were 105 144 laparoscopic procedures and 124 582 open procedures. The overall mean SSI rate was 6.2%, varying by surgical procedure from 5.8% to 7.6%. Among the full study population, adjusted model results showed a significant association of laparoscopy with lower odds of SSI (odds ratio, 0.43; 95% CI, 0.41-0.46; P 50%) procedures laparoscopically. Conclusions and Relevance:Policy changes that promote surgical education and resources for laparoscopy, especially at low-adoption hospitals, may be associated with reduced colon SSI rates. Support of the development of innovative educational policies may help achieve improvement in patient outcomes and decreased health care use in colon surgery.

Abstract Background Patient movement between hospitals, nursing homes (NH), and long-term acute care facilities (LTACs) contributes to MDRO spread. SHIELD OC is a regional decolonization collaborative among adult facilities with high patient sharing designed to reduce countywide MDRO prevalence. We report pre- and post-intervention MDRO colonization prevalence. Methods Decolonization included chlorhexidine bath (CHG) (4% liquid or 2% cloth) and twice-daily nasal swab 10% povidone–iodine (PI). LTAC and NH used CHG for all baths and PI 5 days on admission and Monday–Friday every other week. Patients in contact precautions (CP) at hospitals had daily CHG and 5-days PI on admission. Point-prevalence screening for MRSA, VRE, ESBL, and CRE using nares, axilla/groin, and peri-rectal swabs was conducted pre-intervention (September 2016–March 2017) and post-intervention (August 2018–April 2019); 50 random LTAC and 50 CP hospitalized patients were sampled; for NH up to 50 were sampled at baseline and all residents post-intervention. Raw impact of the intervention was assessed by the average change in colonization prevalence, with each facility carrying equal weight. Generalized linear mixed models (GLM) stratified by facility type were used to assess the impact on MDRO colonization when clustering by facility. Results Across 35 facilities (16 hospitals, 16 NHs, 3 LTACs), the overall MDRO prevalence was reduced 22% in NHs (OR 0.58, P < 0.001), 34% LTACs (OR = 0.27, P < 0.001), and 11% CP patients (OR = 0.67, P < 0.001, Table 1). For MRSA, raw reductions were 31% NHs (OR = 0.58, P < 0.001), 39% LTACs (OR = 0.51, P = 0.01), and 3% CP patients (OR = 0.88, P = NS). For VRE, raw reductions were 40% NHs (OR = 0.62, P = 0.001), 55% LTACs (OR = 0.26, P < 0.001), and 15% CP patients (OR = 0.67, P = 0.004). For ESBLs, raw reductions were 24% NHs (OR = 0.65, P < 0.001), 34% LTACs (OR = 0.53, P = 0.01), and 26% CP patients (OR = 0.64, P < 0.001). For CRE, raw reductions were 24% NHs (OR = 0.70, P = NS), and 23% LTACs (OR = 0.75, P = NS). CRE increased by 26% in CP averaged across hospitals, although patient -level CRE declined 2.4% to 1.8% (OR = 0.74, P = NS). Conclusion MDRO carriage was common in highly inter-connected NHs, LTACs and hospitals. A regional collaborative of universal decolonization in long-term care and targeted decolonization of CP patients in hospitals led to sizeable reductions in MDRO carriage. Disclosures All Authors: No reported Disclosures.

BackgroundMultidrug-resistant organisms (MDROs) spread between hospitals, nursing homes (NHs), and long-term acute care facilities (LTACs) via patient transfers. The Shared Healthcare Intervention to Eliminate Life-threatening Dissemination of MDROs in Orange County is a regional public health collaborative involving decolonization at 38 healthcare facilities selected based on their high degree of patient sharing. We report baseline MDRO prevalence in 21 NHs/LTACs.MethodsA random sample of 50 adults for 21 NHs/LTACs (18 NHs, 3 LTACs) were screened for methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant Enterococcus spp. (VRE), extended-spectrum β-lactamase-producing organisms (ESBL), and carbapenem-resistant Enterobacteriaceae (CRE) using nares, skin (axilla/groin), and peri-rectal swabs. Facility and resident characteristics associated with MDRO carriage were assessed using multivariable models clustering by person and facility.ResultsPrevalence of MDROs was 65% in NHs and 80% in LTACs. The most common MDROs in NHs were MRSA (42%) and ESBL (34%); in LTACs they were VRE (55%) and ESBL (38%). CRE prevalence was higher in facilities that manage ventilated LTAC patients and NH residents (8% vs

BACKGROUND:Universal skin and nasal decolonisation reduces multidrug-resistant pathogens and bloodstream infections in intensive care units. The effect of universal decolonisation on pathogens and infections in non-critical-care units is unknown. The aim of the ABATE Infection trial was to evaluate the use of chlorhexidine bathing in non-critical-care units, with an intervention similar to one that was found to reduce multidrug-resistant organisms and bacteraemia in intensive care units. METHODS:The ABATE Infection (active bathing to eliminate infection) trial was a cluster-randomised trial of 53 hospitals comparing routine bathing to decolonisation with universal chlorhexidine and targeted nasal mupirocin in non-critical-care units. The trial was done in hospitals affiliated with HCA Healthcare and consisted of a 12-month baseline period from March 1, 2013, to Feb 28, 2014, a 2-month phase-in period from April 1, 2014, to May 31, 2014, and a 21-month intervention period from June 1, 2014, to Feb 29, 2016. Hospitals were randomised and their participating non-critical-care units assigned to either routine care or daily chlorhexidine bathing for all patients plus mupirocin for known methicillin-resistant Staphylococcus aureus (MRSA) carriers. The primary outcome was MRSA or vancomycin-resistant enterococcus clinical cultures attributed to participating units, measured in the unadjusted, intention-to-treat population as the HR for the intervention period versus the baseline period in the decolonisation group versus the HR in the routine care group. Proportional hazards models assessed differences in outcome reductions across groups, accounting for clustering within hospitals. This trial is registered with ClinicalTrials.gov, number NCT02063867. FINDINGS:There were 189 081 patients in the baseline period and 339 902 patients (156 889 patients in the routine care group and 183 013 patients in the decolonisation group) in the intervention period across 194 non-critical-care units in 53 hospitals. For the primary outcome of unit-attributable MRSA-positive or VRE-positive clinical cultures (figure 2), the HR for the intervention period versus the baseline period was 0·79 (0·73-0·87) in the decolonisation group versus 0·87 (95% CI 0·79-0·95) in the routine care group. No difference was seen in the relative HRs (p=0·17). There were 25 (

Rates of invasive pneumococcal disease have declined since widespread introduction of pneumococcal conjugate vaccines (PCVs) in the United States. We evaluated the impact of immunization status and recent antibiotic use on an individual child's risk of colonization. This study extends previously reported data from children

BackgroundSeveral per- and polyfluoroalkyl substances (PFAS) are ubiquitous anthropogenic pollutants almost universally detected in humans. Experimental evidence indicates that PFAS alter glucose metabolism and insulin secretion. However, epidemiological studies have yielded inconsistent results.ObjectiveWe sought to examine associations between plasma PFAS concentrations, glycemic indicators, and diabetes incidence among high-risk adults.MethodsWithin the Diabetes Prevention Program (DPP), a trial for the prevention of type 2 diabetes among high-risk individuals, we quantified baseline plasma concentrations of nine PFAS among 957 participants randomized to a lifestyle intervention or placebo. We evaluated adjusted associations for plasma PFAS concentrations with diabetes incidence and key glycemic indicators measured at baseline and annually over up to 4.6 y.ResultsPlasma PFAS concentrations were similar to those reported in the U.S. population in 1999-2000. At baseline, in cross-sectional analysis, a doubling in plasma perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) concentrations was associated with higher homeostatic model assessment of insulin resistance (HOMA-IR) [βPFOS=0.39; 95% confidence interval (CI): 0.13, 0.66; βPFOA=0.64; 95% CI: 0.34, 0.94], β-cell function (HOMA-β) (βPFOS=9.62; 95% CI: 1.55, 17.70; βPFOA=15.93; 95% CI: 6.78, 25.08), fasting proinsulin (βPFOS=1.37 pM; 95% CI: 0.50, 2.25; βPFOA=1.71 pM; 95% CI: 0.72, 2.71), and glycated hemoglobin (HbA1c) (βPFOS=0.03%; 95% CI: 0.002, 0.07; βPFOA=0.04%; 95% CI: 0.001, 0.07). There was no strong evidence of associations between plasma PFAS concentrations and diabetes incidence or prospective changes in glycemic indicators during the follow-up period.ConclusionsAt baseline, several PFAS were cross-sectionally associated with small differences in markers of insulin secretion and β-cell function. However, there was limited evidence suggesting that PFAS concentrations are associated with diabetes incidence or changes in glycemic indicators during the follow-up period. https://doi.org/10.1289/EHP1612.

Abstract Background MDROs can spread between hospitals, nursing homes (NH), and long-term acute care facilities (LTACs) via shared patients. SHIELD OC is a regional decolonization collaborative involving 38 of 104 countywide adult facilities identified by their high degree of direct and indirect patient sharing with one another. We report baseline MDRO prevalence in these facilities. Methods Adult patients in 38 facilities (17 hospitals, 18 NHs, 3 LTACs) underwent point-prevalence screening between September 2016–April 2017 for MRSA, VRE, ESBL, and CRE using nares, skin (axilla/groin), and peri-rectal swabs. In NHs and LTACs, residents were randomly selected until 50 sets of swabs were obtained. Swabbing in hospitals involved all patients in contact precautions. An additional set of swabs were also performed for all LTAC admissions from November 2016–February 2017. Results The overall prevalence of any MDRO among patients was 64% (44%–88%) in NHs, 80% (range 72%–86%) in LTACs, and 64% (54–84%) in hospitals (contact precaution patients) (Table 1). Only 25%, 64%, and 81% of patients were already known to harbor an MDRO in NHs, LTACs, and hospitals, respectively. Known MDRO patients also harbored another MDRO 49%, 63%, and 34% of the time for NHs, LTACs, and hospitals, respectively. In LTACs, MDRO point prevalence was 38% higher than the usual admission prevalence (65% higher for MRSA, 34% higher for VRE, 95% higher for ESBL, and 50% higher for CRE). Conclusion MDRO carriage in highly inter-connected NHs and LTACs was widespread, rivaling that found in hospitalized patients on contact precautions. MRSA, VRE, and ESBL carriage far outnumbered CRE carriage. A history of MDRO was insensitive for identifying MDRO carriers, and many patients carried multiple MDROs. The extensive MDRO burden and transmission in long-term care settings suggests that regional MDRO prevention efforts must include MDRO control in long-term care facilities. Disclosures R. D. Singh, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; J. A. McKinnell, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; L. G. Miller, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; K. Kleinman, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; L. Heim, Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; T. D. Dutciuc, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; M. Estevez, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; G. Gussin, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; L’Oreal: Consultant, Consulting fee; J. Chang, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; E. M. Peterson, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; B. Y. Lee, GSK: Consultant, Consulting fee; R. A. Weinstein, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; OpGen Company: Study support, Provided services at no charge; M. K. Hayden, Sage Products: Receipt of contributed product, Sage is contributing product to healthcare facilities participating in a regional collaborative on which I am a co-investigator. Neither I nor my hospital receive product.; Clorox: Receipt of contributed product, Research support; CDC: Grant Investigator and Receipt of contributed product, Research grant; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; OpGen Company: Study support, Provided services at no charge for studies; S. K. Gohil, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; S. Park, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; S. Tam, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; R. Saavedra, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; S. Yamaguchi, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; H. Custodio, Xttrium Laboratories: Study coordination, Conducting studies in healthcare facilities that are receiving contributed product; Sage Products: Study coordination, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Study coordination, Conducting studies in healthcare facilities that are receiving contributed product; J. Nguyen, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; T. Tjoa, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; J. He, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; M. H. Coady, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; R. Platt, Sage Products: Receipt of contributed product, Conducting clinical studies in which participating healthcare facilities are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting clinical studies in which participating healthcare facilities are receiving contributed product; Clorox: Receipt of contributed product, Conducting clinical studies in which participating healthcare facilities are receiving contributed product; receive research funds from Clorox, but Clorox has no role in the design; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; S. S. Huang, Sage Products: Receipt of contributed product, Conducting studies in which participating healthcare facilities are receiving contributed product (no contribution in submitted abstract), Participating healthcare facilities in my studies received contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in which participating healthcare facilities are receiving contributed product (no contribution in submitted abstract), Participating healthcare facilities in my studies received contributed product; Clorox: Receipt of contributed product, Conducting studies in which participating healthcare facilities are receiving contributed product (no contribution in submitted abstract), Participating healthcare facilities in my studies received contributed product; 3M: Receipt of contributed product, Conducting studies in which participating healthcare facilities are receiving contributed product (no contribution in submitted abstract), Participating healthcare facilities in my studies received contributed product; Molnlycke: Receipt of contributed product, Conducting studies in which participating healthcare facilities are receiving contributed product (no contribution in submitted abstract), Participating healthcare facilities in my studies received contributed product

Abstract Background The majority of healthcare-associated infections due to MDROs occur in the post-discharge setting. Understanding MDRO spread and containment in NHs can help identify infection prevention activities needed to care for vulnerable patients in a medical home setting. Methods We conducted a baseline point prevalence study of MDRO colonization in residents of 28 Southern California NHs participating in a decolonization trial. In Fall 2016, residents were randomly sampled to obtain a set of 50 nares and skin (axilla/groin) swabs from each NH. Nasal swabs were processed for MRSA and skin swabs were processed for MRSA, VRE, ESBL, and CRE. In addition, environmental swabs were collected from high touch objects in resident rooms (bedrail, call button/TV remote, door knobs, light switch, bathroom) and common areas (nursing station, table, chair, railing, and drinking fountain). Results A total of 2,797 body swabs were obtained from 1400 residents. Overall, 48.6% (N = 680) of residents harbored MDROs. MRSA was found in 37% of residents (29.5% nares, 24.4% skin), followed by ESBL in 16% (Table 1). Resident MDRO status was only known for 11% of MRSA (59/518), 18% ESBL (40/228), 4% VRE (4/99), and none of the CRE (0/13) carriers. Colonization did not differ between long stay (48.8%, 534/1094) vs. post-acute (47.7%, 146/306) residents (P = NS), but bedbound residents were more likely to be MDRO colonized (58.7%, 182/310) vs. ambulatory residents (45.7%, 497/1088, P

BackgroundSurgical site infection (SSI) rates are publicly reported as quality metrics and increasingly used to determine financial reimbursement.ObjectiveTo evaluate the volume-outcome relationship as well as the year-to-year stability of performance rankings following coronary artery bypass graft (CABG) surgery and hip arthroplasty.Research designWe performed a retrospective cohort study of Medicare beneficiaries who underwent CABG surgery or hip arthroplasty at US hospitals from 2005 to 2011, with outcomes analyzed through March 2012. Nationally validated claims-based surveillance methods were used to assess for SSI within 90 days of surgery. The relationship between procedure volume and SSI rate was assessed using logistic regression and generalized additive modeling. Year-to-year stability of SSI rates was evaluated using logistic regression to assess hospitals' movement in and out of performance rankings linked to financial penalties.ResultsCase-mix adjusted SSI risk based on claims was highest in hospitals performing

BackgroundSurgical site infection (SSI) rates are publicly reported as quality metrics and increasingly used to determine financial reimbursement.ObjectiveTo evaluate the volume-outcome relationship as well as the year-to-year stability of performance rankings following coronary artery bypass graft (CABG) surgery and hip arthroplasty.Research designWe performed a retrospective cohort study of Medicare beneficiaries who underwent CABG surgery or hip arthroplasty at US hospitals from 2005 to 2011, with outcomes analyzed through March 2012. Nationally validated claims-based surveillance methods were used to assess for SSI within 90 days of surgery. The relationship between procedure volume and SSI rate was assessed using logistic regression and generalized additive modeling. Year-to-year stability of SSI rates was evaluated using logistic regression to assess hospitals' movement in and out of performance rankings linked to financial penalties.ResultsCase-mix adjusted SSI risk based on claims was highest in hospitals performing

Nursing home residents are at risk for acquiring and transmitting MDROs. A serial point-prevalence study of 605 residents in 3 facilities using random sampling found MDRO colonization in 45% of residents: methicillin-resistant Staphylococcus aureus (MRSA, 26%); extended-spectrum β-lactamase-producing Enterobacteriaceae (ESBL, 17%); vancomycin-resistant Enterococcus spp. (VRE, 16%); carbapenem-resistant Enterobacteriaceae (CRE, 1%). MDRO colonization was associated with history of MDRO, care needs, incontinence, and catheters. Infect Control Hosp Epidemiol 2016;1485-1488.

Whether targeted or universal decolonization strategies for the control of methicillin-resistant Staphylococcus aureus (MRSA) select for resistance to decolonizing agents is unresolved. The REDUCE-MRSA trial (ClinicalTrials registration no. NCT00980980) provided an opportunity to investigate this question. REDUCE-MRSA was a 3-arm, cluster-randomized trial of either screening and isolation without decolonization, targeted decolonization with chlorhexidine and mupirocin, or universal decolonization without screening to prevent MRSA infection in intensive-care unit (ICU) patients. Isolates from the baseline and intervention periods were collected and tested for susceptibility to chlorhexidine gluconate (CHG) by microtiter dilution; mupirocin susceptibility was tested by Etest. The presence of the qacA or qacB gene was determined by PCR and DNA sequence analysis. A total of 3,173 isolates were analyzed; 2 were nonsusceptible to CHG (MICs, 8 μg/ml), and 5/814 (0.6%) carried qacA or qacB At baseline, 7.1% of MRSA isolates expressed low-level mupirocin resistance, and 7.5% expressed high-level mupirocin resistance. In a mixed-effects generalized logistic regression model, the odds of mupirocin resistance among clinical MRSA isolates or MRSA isolates acquired in an ICU in intervention versus baseline periods did not differ across arms, although estimates were imprecise due to small numbers. Reduced susceptibility to chlorhexidine and carriage of qacA or qacB were rare among MRSA isolates in the REDUCE-MRSA trial. The odds of mupirocin resistance were no different in the intervention versus baseline periods across arms, but the confidence limits were broad, and the results should be interpreted with caution.

BackgroundChallenges exist in implementing evidence-based strategies, reaching high compliance, and achieving desired outcomes. The rapid adoption of a publicly available toolkit featuring routine universal decolonization of intensive care unit (ICU) patients may affect catheter-related bloodstream infections.MethodsImplementation of universal decolonization-treatment of all ICU patients with chlorhexidine bathing and nasal mupirocin-used a prerelease version of a publicly available toolkit. Implementation in 136 adult ICUs in 95 acute care hospitals across the United States was supported by planning and deployment tactics coordinated by a central infection prevention team using toolkit resources, along with coaching calls and engagement of key stakeholders. Operational and process measures derived from a common electronic health record system provided real-time feedback about performance. Healthcare-associated central line-associated bloodstream infections (CLABSIs), using National Healthcare Safety Network surveillance definitions and comparing the preimplementation period of January 2011 through December 2012 to the postimplementation period of July 2013 through February 2014, were assessed via a Poisson generalized linear mixed model regression for CLABSI events.ResultsImplementation of universal decolonization was completed within 6 months. The estimated rate of CLABSI decreased by 23.5% (95% confidence interval, 9.8%-35.1%; P = .001). There was no evidence of a trend over time in either the pre- or postimplementation period. Adjusting for seasonality and number of beds did not materially affect these results.ConclusionsDissemination of universal decolonization of ICU patients was accomplished quickly in a large community health system and was associated with declines in CLABSI consistent with published clinical trial findings.

BackgroundA key requirement for a useful power calculation is that the calculation mimic the data analysis that will be performed on the actual data, once that data is observed. Close approximations may be difficult to achieve using analytic solutions, however, and thus Monte Carlo approaches, including both simulation and bootstrap resampling, are often attractive. One setting in which this is particularly true is cluster-randomized trial designs. However, Monte Carlo approaches are useful in many additional settings as well. Calculating power for cluster-randomized trials using analytic or simulation-based methods is frequently unsatisfactory due to the complexity of the data analysis methods to be employed and to the sparseness of data to inform the choice of important parameters in these methods.MethodsWe propose that among Monte Carlo methods, bootstrap approaches are most likely to generate data similar to the observed data. In bootstrap approaches, real data are resampled to build complete data sets based on real data that resemble the data for the intended analyses. In contrast, simulation methods would use the real data to estimate parameters for the data, and would then simulate data using these parameters. We describe means of implementing bootstrap power calculation.ResultsWe demonstrate bootstrap power calculation for a cluster-randomized trial with a censored survival outcome and a baseline observation period.ConclusionsBootstrap power calculation is a natural application of resampling methods. It provides a relatively simple solution to power calculation that is likely to be more accurate than analytic solutions or simulation-based calculations, in the sense that the bootstrap approach does not rely on the assumptions inherent in analytic calculations. This method of calculation has several important strengths. Notably, it is simple to achieve great fidelity to the proposed data analysis method and there is no requirement for parameter estimates, or estimates of their variability, from outside settings. So, for example, for cluster-randomized trials, power calculations need not depend on intracluster correlation coefficient estimates from outside studies. In contrast, bootstrap power calculation requires initial data that resemble data that are to be used in the planned study. We are not aware of bootstrap power calculation being previously proposed or explored for cluster-randomized trials, but it can also be applied for other study designs. We show with a simulation study that bootstrap power calculation can replicate analytic power in cases where analytic power can be accurately calculated. We also demonstrate power calculations for correlated censored survival outcomes in a cluster-randomized trial setting, for which we are unaware of an analytic alternative. The method can easily be used when preliminary data are available, as is likely to be the case when research is performed in health delivery systems or other settings where electronic medical records can be obtained.

BackgroundUrinary tract infections (UTIs) are common health-care-associated infections. Bacteriuria commonly precedes UTI and is often treated with antibiotics, particularly in hospital intensive care units (ICUs). In 2013, a cluster-randomised trial (REDUCE MRSA Trial [Randomized Evaluation of Decolonization vs Universal Clearance to Eradicate MRSA]) showed that body surface decolonisation reduced all-pathogen bloodstream infections. We aim to further assess the effect of decolonisation on bacteriuria and candiduria in patients admitted to ICUs.MethodsWe did a secondary analysis of a three-group, cluster-randomised trial of 43 hospitals (clusters) with patients in 74 adult ICUs. The three groups included were either meticillin-resistant Staphylococcus aureus (MRSA) screening and isolation, targeted decolonisation (screening, isolation, and decolonisation of MRSA carriers) with chlorhexidine and mupirocin, and universal decolonisation (no screening, all patients decolonised) with chlorhexidine and mupirocin. Protocol included chlorhexidine cleansing of the perineum and proximal 6 inches (15·24 cm) of urinary catheters. ICUs within the same hospital were assigned the same strategy. Outcomes included high-level bacteriuria (≥50 000 colony forming units [CFU]/mL) with any uropathogen, high-level candiduria (≥50 000 CFU/mL), and any bacteriuria with uropathogens. Sex-specific analyses were specified a priori. Proportional hazards models assessed differences in outcome reductions across groups, comparing an 18-month intervention period to a 12-month baseline period.Findings122 646 patients (48 390 baseline, 74 256 intervention) were enrolled. Intervention versus baseline hazard ratios (HRs) for high-level bacteriuria were 1·02 (95% CI 0·88-1·18) for screening or isolation, 0·88 (0·76-1·02) for targeted decolonisation, and 0·87 (0·77-1·00) for universal decolonisation (no difference between groups, p=0·26), with no sex-specific reductions (HRs for men: 1·09 [95% CI 0·85-1·40] for screening or isolation, 1·01 [0·79-1·29] for targeted decolonisation, and 0·78 [0·63-0·98] for universal decolonisation, p=0·12; HRs for women: 0·97 [0·80-1·17] for screening and isolation, 0·83 [0·70-1·00] for targeted decolonisation, and 0·93 [0·79-1·09] for universal decolonisation, p=0·49). HRs for high-level candiduria were 1·14 (0·95-1·37) for screening and isolation, 0·99 (0·83-1·18) for targeted decolonisation, and 0·83 (0·70-0·99) for universal decolonisation (p=0·05). Differences between sexes were due to reductions in men in the universal decolonisation group (HRs: 1·21 [95% CI 0·88-1·68] for screening or isolation, 1·01 [0·73-1·39] for targeted decolonisation, and 0·63 [0·45-0·89] for universal decolonisation, p=0·02). Bacteriuria with any CFU/mL was also reduced in men in the universal decolonisation group (HRs 1·01 [0·81-1·25] for screening or isolation, 1·04 [0·83-1·30] for targeted decolonisation, and 0·74 [0·61-0·90] for universal decolonisation, p=0·04).InterpretationUniversal decolonisation of patients in the ICU with once a day chlorhexidine baths and short-course nasal mupirocin could be a potential preventive strategy in male patients because it significantly decreases candiduria and any bacteriuria, but not for women.FundingHAI Program from AHRQ, US Department of Health and Human Services as part of the Developing Evidence to Inform Decisions about Effectiveness (DEcIDE) program, CDC Prevention Epicenters Program.

BackgroundDeep and organ/space surgical site infections (D/OS SSI) cause significant morbidity, mortality, and costs. Rates are publicly reported and increasingly used as quality metrics affecting hospital payment. Lack of standardized surveillance methods threaten the accuracy of reported data and decrease confidence in comparisons based upon these data.MethodsWe analyzed data from national validation studies that used Medicare claims to trigger chart review for SSI confirmation after coronary artery bypass graft surgery (CABG) and hip arthroplasty. We evaluated code performance (sensitivity and positive predictive value) to select diagnosis codes that best identified D/OS SSI. Codes were analyzed individually and in combination.ResultsAnalysis included 143 patients with D/OS SSI after CABG and 175 patients with D/OS SSI after hip arthroplasty. For CABG, 9 International Classification of Diseases, 9th Revision (ICD-9) diagnosis codes identified 92% of D/OS SSI, with 1 D/OS SSI identified for every 4 cases with a diagnosis code. For hip arthroplasty, 6 ICD-9 diagnosis codes identified 99% of D/OS SSI, with 1 D/OS SSI identified for every 2 cases with a diagnosis code.ConclusionsThis standardized and efficient approach for identifying D/OS SSI can be used by hospitals to improve case detection and public reporting. This method can also be used to identify potential D/OS SSI cases for review during hospital audits for data validation.

BackgroundObservational studies rarely account for confounding by indication, whereby empiric antibiotics initiated for signs and symptoms of infection prior to the diagnosis of infection are then viewed as risk factors for infection. We evaluated whether confounding by indication impacts antimicrobial risk factors for methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant enterococci (VRE) acquisition.FindingsWe previously reported several predictors of MRSA and VRE acquisition in 967 intensive care unit (ICU) patients with no prior history of MRSA or VRE who had an initial negative screening culture followed by either a subsequent negative screening culture (controls) or positive screening or clinical culture (cases). Within and prior to this acquisition interval, we collected demographic, comorbidity, daily device and antibiotic utilization data. We now re-evaluate all antibiotics by medical record review for evidence of treatment for signs and symptoms ultimately attributable to MRSA or VRE. Generalized linear mixed models are used to assess variables associated with MRSA or VRE acquisition, accounting for clustering by ward. We find that exclusion of empiric antibiotics given for suspected infection affects 17% (113/661) of antibiotic prescriptions in 25% (60/244) of MRSA-positive patients but only 1% (5/491) of antibiotic prescriptions in 1% (3/227) of VRE-positive patients. In multivariate testing, fluoroquinolones are no longer associated with MRSA acquisition, and aminoglycosides are significantly protective (OR = 0.3, CI:0.1-0.7).ConclusionsNeglecting treatment indication may cause common empiric antibiotics to appear spuriously associated with MRSA acquisition. This effect is absent for VRE, likely because empiric therapy is infrequent given the low prevalence of VRE.

ObjectiveTo determine rates of blood culture contamination comparing 3 strategies to prevent intensive care unit (ICU) infections: screening and isolation, targeted decolonization, and universal decolonization.DesignPragmatic cluster-randomized trial.SettingForty-three hospitals with 74 ICUs; 42 of 43 were community hospitals.PatientsPatients admitted to adult ICUs from July 1, 2009, to September 30, 2011.MethodsAfter a 6-month baseline period, hospitals were randomly assigned to 1 of 3 strategies, with all participating adult ICUs in a given hospital assigned to the same strategy. Arm 1 implemented methicillin-resistant Staphylococcus aureus (MRSA) nares screening and isolation, arm 2 targeted decolonization (screening, isolation, and decolonization of MRSA carriers), and arm 3 conducted no screening but universal decolonization of all patients with mupirocin and chlorhexidine (CHG) bathing. Blood culture contamination rates in the intervention period were compared to the baseline period across all 3 arms.ResultsDuring the 6-month baseline period, 7,926 blood cultures were collected from 3,399 unique patients: 1,099 sets in arm 1, 928 in arm 2, and 1,372 in arm 3. During the 18-month intervention period, 22,761 blood cultures were collected from 9,878 unique patients: 3,055 sets in arm 1, 3,213 in arm 2, and 3,610 in arm 3. Among all individual draws, for arms 1, 2, and 3, the contamination rates were 4.1%, 3.9%, and 3.8% for the baseline period and 3.3%, 3.2%, and 2.4% for the intervention period, respectively. When we evaluated sets of blood cultures rather than individual draws, the contamination rate in arm 1 (screening and isolation) was 9.8% (N = 108 sets) in the baseline period and 7.5% (N = 228) in the intervention period. For arm 2 (targeted decolonization), the baseline rate was 8.4% (N = 78) compared to 7.5% (N = 241) in the intervention period. Arm 3 (universal decolonization) had the greatest decrease in contamination rate, with a decrease from 8.7% (N = 119) contaminated blood cultures during the baseline period to 5.1% (N = 184) during the intervention period. Logistic regression models demonstrated a significant difference across the arms when comparing the reduction in contamination between baseline and intervention periods in both unadjusted (P = .02) and adjusted (P = .02) analyses. Arm 3 resulted in the greatest reduction in blood culture contamination rates, with an unadjusted odds ratio (OR) of 0.56 (95% confidence interval [CI], 0.044-0.71) and an adjusted OR of 0.55 (95% CI, 0.43-0.71).ConclusionIn this large cluster-randomized trial, we demonstrated that universal decolonization with CHG bathing resulted in a significant reduction in blood culture contamination.

BackgroundSurgical site infections (SSIs) following vascular surgery have high morbidity and costs, and are increasingly tracked as hospital quality measures.ObjectiveTo assess the ability of Medicare claims to identify US hospitals with high SSI rates after vascular surgery.Research designUsing claims from fee-for-service Medicare enrollees of age 65 years and older who underwent vascular surgery from 2005 to 2008, we derived hospital rankings using previously validated codes suggestive of SSI, with individual-level adjustment for age, sex, and comorbidities. We then obtained medical records for validation of SSI from hospitals ranked in the best and worst deciles of performance, and used logistic regression to calculate the risk-adjusted odds of developing an SSI in worst-decile versus best-decile hospitals.ResultsAmong 203,023 Medicare patients who underwent vascular surgery at 2512 US hospitals, a patient undergoing surgery in a hospital ranked in the worst-performing decile based on claims had 2.5 times higher odds of developing a chart-confirmed SSI relative to a patient with the same age, sex, and comorbidities in a hospital ranked in the best-performing decile (95% confidence interval, 2.0-3.1). SSI confirmation among patients with claims suggesting infection was similar across deciles, and we found similar findings in analyses limited to deep and organ/space SSIs. We report on diagnosis codes with high sensitivity for identifying deep and organ/space SSI, with one-to-one mapping to ICD-10-CM codes.ConclusionsClaims-based surveillance offers a standardized and objective methodology that can be used to improve SSI surveillance and to validate hospitals' publicly reported data.

BackgroundIn April 2010, a 13-valent pneumococcal conjugate vaccine (PCV13) replaced PCV7 for use in the United States. We evaluated rates of pneumococcal colonization, by serotype and antibiotic resistance, in Massachusetts communities where serial cross-sectional surveillance has been conducted for the past decade.MethodsNasopharyngeal swabs were obtained from children 0 to

BackgroundMethicillin-resistant Staphylococcus aureus (MRSA) colonization predicts later infection, with both host and pathogen determinants of invasive disease.MethodsThis nested case-control study evaluates predictors of MRSA bacteremia in an 8-intensive care unit (ICU) prospective adult cohort from 1 September 2003 through 30 April 2005 with active MRSA surveillance and collection of ICU, post-ICU, and readmission MRSA isolates. We selected MRSA carriers who did (cases) and those who did not (controls) develop MRSA bacteremia. Generating assembled genome sequences, we evaluated 30 MRSA genes potentially associated with virulence and invasion. Using multivariable Cox proportional hazards regression, we assessed the association of these genes with MRSA bacteremia, controlling for host risk factors.ResultsWe collected 1578 MRSA isolates from 520 patients. We analyzed host and pathogen factors for 33 cases and 121 controls. Predictors of MRSA bacteremia included a diagnosis of cancer, presence of a central venous catheter, hyperglycemia (glucose level, >200 mg/dL), and infection with a MRSA strain carrying the gene for staphylococcal enterotoxin P (sep). Receipt of an anti-MRSA medication had a significant protective effect.ConclusionsIn an analysis controlling for host factors, colonization with MRSA carrying sep increased the risk of MRSA bacteremia. Identification of risk-adjusted genetic determinants of virulence may help to improve prediction of invasive disease and suggest new targets for therapeutic intervention.

Key Points: Question: Is implementation of a regional hospital and nursing home decolonization collaborative (coordinated intervention adopted by participating health care facilities) associated with a reduction in multidrug-resistant organisms (MDROs), infection-related hospitalizations, costs, and deaths? Findings: In this quality improvement study of 35 health care facilities in Orange County, California, using quasi-experimental design, chlorhexidine bathing and nasal decolonization were associated with significantly lower MDRO prevalence and incident clinical cultures. Infection-related hospitalizations, associated costs, and deaths among nursing home residents also decreased. Meaning: In this study, a regional decolonization collaborative involving universal decolonization in long-term care facilities and targeted decolonization among hospital patients in contact precautions was associated with lower MDRO carriage, infections, hospitalizations, costs, and deaths. Importance: Infections due to multidrug-resistant organisms (MDROs) are associated with increased morbidity, mortality, length of hospitalization, and health care costs. Regional interventions may be advantageous in mitigating MDROs and associated infections. Objective: To evaluate whether implementation of a decolonization collaborative is associated with reduced regional MDRO prevalence, incident clinical cultures, infection-related hospitalizations, costs, and deaths. Design, Setting, and Participants: This quality improvement study was conducted from July 1, 2017, to July 31, 2019, across 35 health care facilities in Orange County, California. Exposures: Chlorhexidine bathing and nasal iodophor antisepsis for residents in long-term care and hospitalized patients in contact precautions (CP). Main Outcomes and Measures: Baseline and end of intervention MDRO point prevalence among participating facilities; incident MDRO (nonscreening) clinical cultures among participating and nonparticipating facilities; and infection-related hospitalizations and associated costs and deaths among residents in participating and nonparticipating nursing homes (NHs). Results: Thirty-five facilities (16 hospitals, 16 NHs, 3 long-term acute care hospitals [LTACHs]) adopted the intervention. Comparing decolonization with baseline periods among participating facilities, the mean (SD) MDRO prevalence decreased from 63.9% (12.2%) to 49.9% (11.3%) among NHs, from 80.0% (7.2%) to 53.3% (13.3%) among LTACHs (odds ratio [OR] for NHs and LTACHs, 0.48; 95% CI, 0.40-0.57), and from 64.1% (8.5%) to 55.4% (13.8%) (OR, 0.75; 95% CI, 0.60-0.93) among hospitalized patients in CP. When comparing decolonization with baseline among NHs, the mean (SD) monthly incident MDRO clinical cultures changed from 2.7 (1.9) to 1.7 (1.1) among participating NHs, from 1.7 (1.4) to 1.5 (1.1) among nonparticipating NHs (group × period interaction reduction, 30.4%; 95% CI, 16.4%-42.1%), from 25.5 (18.6) to 25.0 (15.9) among participating hospitals, from 12.5 (10.1) to 14.3 (10.2) among nonparticipating hospitals (group × period interaction reduction, 12.9%; 95% CI, 3.3%-21.5%), and from 14.8 (8.6) to 8.2 (6.1) among LTACHs (all facilities participating; 22.5% reduction; 95% CI, 4.4%-37.1%). For NHs, the rate of infection-related hospitalizations per 1000 resident-days changed from 2.31 during baseline to 1.94 during intervention among participating NHs, and from 1.90 to 2.03 among nonparticipating NHs (group × period interaction reduction, 26.7%; 95% CI, 19.0%-34.5%). Associated hospitalization costs per 1000 resident-days changed from $64 651 to $55 149 among participating NHs and from $55 151 to $59 327 among nonparticipating NHs (group × period interaction reduction, 26.8%; 95% CI, 26.7%-26.9%). Associated hospitalization deaths per 1000 resident-days changed from 0.29 to 0.25 among participating NHs and from 0.23 to 0.24 among nonparticipating NHs (group × period interaction reduction, 23.7%; 95% CI, 4.5%-43.0%). Conclusions and Relevance: A regional collaborative involving universal decolonization in long-term care facilities and targeted decolonization among hospital patients in CP was associated with lower MDRO carriage, infections, hospitalizations, costs, and deaths. This quality improvement study evaluates whether implementation of a decolonization collaborative is associated with reduced regional multidrug-resistant organism prevalence, incident clinical cultures, infection-related hospitalizations, costs, and deaths. [ABSTRACT FROM AUTHOR]