Previous studies suggested that a bundled intervention was associated with lower rates of Staphylococcus aureus surgical site infections (SSIs) among patients having cardiac or orthopedic operations.
To evaluate whether the implementation of an evidence-based bundle is associated with a lower risk of S aureus SSIs in patients undergoing cardiac operations or hip or knee arthroplasties.
Design, Setting, and Participants
Twenty hospitals in 9 US states participated in this pragmatic study; rates of SSIs were collected for a median of 39 months (range, 39-43) during the preintervention period (March 1, 2009, to intervention) and a median of 21 months (range, 14-22) during the intervention period (from intervention start through March 31, 2014).
Patients whose preoperative nares screens were positive for methicillin-resistant S aureus (MRSA) or methicillin-susceptible S aureus (MSSA) were asked to apply mupirocin intranasally twice daily for up to 5 days and to bathe daily with chlorhexidine-gluconate (CHG) for up to 5 days before their operations. MRSA carriers received vancomycin and cefazolin or cefuroxime for perioperative prophylaxis; all others received cefazolin or cefuroxime. Patients who were MRSA-negative and MSSA-negative bathed with CHG the night before and morning of their operations. Patients were treated as MRSA-positive if screening results were unknown.
Main Outcomes and Measures
The primary outcome was complex (deep incisional or organ space) S aureus SSIs. Monthly SSI counts were analyzed using Poisson regression analysis.
After a 3-month phase-in period, bundle adherence was 83% (39% full adherence; 44% partial adherence). Overall, 101 complex S aureus SSIs occurred after 28 218 operations during the preintervention period and 29 occurred after 14 316 operations during the intervention period (mean rate per 10 000 operations, 36 for preintervention period vs 21 for intervention period, difference, −15 [95% CI, −35 to −2]; rate ratio [RR], 0.58 [95% CI, 0.37 to 0.92]). The rates of complex S aureus SSIs decreased for hip or knee arthroplasties (difference per 10 000 operations, −17 [95% CI, −39 to 0]; RR, 0.48 [95% CI, 0.29 to 0.80]) and for cardiac operations (difference per 10 000 operations, −6 [95% CI, −48 to 8]; RR, 0.86 [95% CI, 0.47 to 1.57]).
Conclusions and Relevance
In this multicenter study, a bundle comprising S aureus screening, decolonization, and targeted prophylaxis was associated with a modest, statistically significant decrease in complex S aureus SSIs.
Staphylococcus aureus carriage increases the risk of S aureus surgical site infections (SSIs).1-4 The risk for these infections may be decreased by screening patients for nasal carriage of S aureus and decolonizing carriers during the preoperative period.2,5 In addition, perioperative prophylaxis with agents such as vancomycin may reduce rates of methicillin-resistant S aureus (MRSA) SSIs.6,7 A meta-analysis found that a bundle comprising screening for S aureus nasal carriage, decolonizing carriers with intranasal mupirocin and chlorhexidine gluconate (CHG) bathing, and using vancomycin for prophylaxis among MRSA carriers was associated with lower rates of S aureus SSIs among patients undergoing select cardiac operations or hip or knee arthroplasties.8
Despite this evidence, surveys in the United States indicate that adoption of screening and decolonization bundles varies substantially; most clinicians do not screen patients for S aureus carriage before operations and those that screen patients often screen for MRSA alone.9,10 Similarly, clinicians that decolonize patients preoperatively usually decolonize only patients carrying MRSA despite the greater frequency of colonization by methicillin-susceptible S aureus (MSSA) and the severity of MSSA infections.9,10
The effectiveness of the bundle assessed in the meta-analysis8 had, to our knowledge, not been evaluated in a multicenter study. Thus, we conducted a 20-hospital quasi-experimental pragmatic study—the Study to Optimally Prevent SSIs in Select Cardiac and Orthopedic Procedures (STOP SSI)—to determine whether an evidence-based bundle (screening for S aureus, decolonizing carriers, and prescribing optimal perioperative antibiotics) would be associated with a lower incidence of S aureus SSIs compared with standard practice. We hypothesized that bundle implementation would be associated with a lower incidence of complex (ie, deep incisional or organ space11,12) S aureus SSIs among patients undergoing cardiac operations or hip or knee arthroplasties.
The Hospital Corporation of America (HCA) research group determined that the intervention was a quality improvement initiative and not human participants research.13 Institutional review boards from the University of Iowa and The Joint Commission exempted the study because analyzing de-identified data (University of Iowa) and evaluating implementation (The Joint Commission) were not human participants research. Twenty HCA-affiliated hospitals participated in a 5-year, quasi-experimental, pragmatic study14,15 that utilized preintervention observational measurements, a prospective intervention group, and time-series analysis to evaluate an evidence-based bundle to prevent S aureus SSIs (trial protocol in Supplement 1). The preintervention period extended from March 1, 2009, to the date on which a hospital began the intervention. Hospitals implemented the bundle on a rolling basis with the earliest implementations occurring June 1, 2012, and the latest October 9, 2012.
Hospital staff swabbed patients’ nares during scheduled preoperative clinic visits (usually 10-14 days, but no more than 30 days before the operations). Each laboratory used their standard tests (eg, polymerase chain reaction, culture on chromogenic agar, standard bacterial culture) to determine MRSA and MSSA carrier status. The most common tests were chromogenic agar for MRSA and standard culture for MSSA. Patients with positive screening tests for either MRSA or MSSA applied mupirocin intranasally twice daily and bathed with CHG once daily for up to 5 days immediately before their operations. Patients that received fewer than 10 doses of mupirocin before their operations received the remaining doses during the postoperative period. The CHG bathing was not continued after the operation. Patients with negative MRSA and MSSA nasal screens bathed with CHG the night before and the morning of their operations.8,13
Perioperative prophylaxis was administered using weight-based dosing and redosing according to the 2013 American Society of Health-System Pharmacists (ASHP) guidelines.16 The antimicrobial agents used for perioperative prophylaxis varied by the patients’ S aureus carrier status; noncarriers and MSSA carriers received either cefazolin or cefuroxime for perioperative prophylaxis, whereas MRSA carriers received both cefazolin or cefuroxime and vancomycin. If a patient had a confirmed β-lactam allergy, surgeons were encouraged to provide perioperative prophylaxis with vancomycin rather than cefazolin or cefuroxime and to add either gentamicin or aztreonam for gram-negative coverage. Patients with negative screening tests but with documented histories of MRSA carriage or infection were treated as carriers. Patients who were either not screened because they had emergent operations or whose screening results were not known at the time of their operations received vancomycin and cefazolin or cefuroxime for perioperative prophylaxis. In these situations, nasal swabs were obtained for MSSA and MRSA screening and patients began the decolonization regimen immediately before their operations. Mupirocin was continued until screening test results were known; mupirocin was discontinued if test results were negative.
We categorized each operation as fully adherent, partially adherent, or not adherent based on the elements of the bundle that the patient received (eTable 1 in Supplement 2). Because implementation of the bundle elements varied among individual surgeons, we also documented the extent of surgeon implementation as “full,” “partial” (eg, did not give vancomycin prophylaxis to patients undergoing emergent operations), or “not at all.”
Recruitment and Eligibility Criteria
Hospital sites were selected as described previously.13 Hospitals using some, but not all, bundle elements during the preintervention period could participate (eAppendix 1 in Supplement 2). Eligible patients were 18 years or older and underwent scheduled, urgent, or emergent primary hip or knee arthroplasty (ie, replacement or resurfacing) or primary cardiac operation through a median sternotomy incision (eTable 2 in Supplement 2). Arthroplasty revisions, cardiac transplants, transapical valve implantation, and operations performed using percutaneous or thoracotomy approaches were not eligible for this study. We excluded operations among patients with preexisting infections at the surgical site.
Surveillance and Data Collection
Patients were followed up for 90 days after their operations by infection preventionists at participating hospitals. The infection preventionists identified patients who met the Centers for Disease Control and Prevention (CDC) National Healthcare Safety Network’s (NHSN) SSI definitions.17-20 An NHSN form was completed for each SSI in both the preintervention and intervention periods. The site infection preventionists were instructed to perform surveillance consistently throughout the study period. We attributed SSIs to the months during which the operations were performed. Each site audited at least 5 cases per month for concurrent review to assess adherence to bundle elements and identify areas for improvement. Additionally, an experienced infection preventionist reviewed medical records from 10% of patients with SSIs and confirmed that all met the CDC NHSN SSI definition. Other variables were obtained from corporate data warehouses, which undergo validation until 99% to 100% accuracy is achieved.
Antimicrobial Susceptibility Testing
Available S aureus isolates from SSIs occurring during the intervention period were sent to a reference laboratory and tested for mupirocin and chlorhexidine susceptibility. For CHG susceptibility testing, laboratory staff used chlorhexidine digluconate 20% aqueous solution (Sigma-Aldrich) and the standard Clinical and Laboratory Standards Institute broth dilution method with a complete inhibition end point at 18 to 24 hours of incubation.21 Staff assessed mupirocin susceptibility with the epsilometer method (Etest, bioMérieux).22
qac Polymerase Chain Reaction
Laboratory staff tested isolates for the genes encoding quaternary ammonium compound (qac) efflux proteins (qacA/B genes), which have been associated with CHG nonsusceptibility. They used single primer pair sequences to detect qacA/B.23
To minimize ascertainment bias, the primary study outcome was the rate of complex MSSA or MRSA SSIs. Patients with complex SSIs after cardiac operations or joint replacements were likely to be seen by their surgeons for diagnosis and treatment. Thus, infection preventionists would identify these patients during routine surveillance, whereas patients with superficial infections could be missed. We conducted subgroup analyses to assess rates of complex S aureus SSIs stratified by the following variables chosen a priori: MRSA or MSSA and operation group (ie, cardiac operations or joint arthroplasties). Also, based on our experiences with the study implementation, we performed stratified analyses on the following variables chosen ad hoc: operation scheduling, adherence with the bundle elements, and the extent of surgeon implementation.
Other outcomes of interest chosen a priori were the rates of all SSIs (superficial and complex SSI, caused by any pathogen); all gram-negative SSIs; all complex SSIs; the patient’s postoperative length of stay during the index admission (available for operations performed after June 2011); and readmissions to the index hospital or another facility for treatment of SSIs within the first 90 days after the operation. Study-related adverse events were documented by each study site using standardized forms (Supplement 3).
On the basis of the surgical volumes and SSI rates at the 20 hospitals during 2010 (67 S aureus SSIs/10 000 cardiac operations, 92/10 000 hip arthroplasties, 43/10 000 knee arthroplasties), we needed at least 8905 operations in the intervention group to reach 70% power to detect a 30% relative reduction (rate ratio [RR], 0.70) in the S aureus SSI rate. Thus, the sample size at the 20 participating hospitals was sufficient.
We used SAS software (SAS Institute), version 9.2, to perform intention-to-treat analyses comparing patients during the intervention period with patients during the preintervention period. The significance level was .05 using a 2-sided test.
We used logistic regression to evaluate the intervention’s association with SSIs and with readmissions related to SSIs while adjusting for patient-level confounders (age, diabetes, Charlson comorbidity index,24 history of MRSA). We used traditional regression to analyze log-transformed postoperative length of stay while adjusting for patient-level confounders. We fit all models with generalized estimating equations to accommodate hospital-level clustering effects and we used an exchangeable working correlation structure.
Hospital-Level Time-Series Analysis of SSI Rates
We analyzed monthly SSI counts (ie, time-series data) using Poisson regression models with a log link and with log-transformed monthly operation counts as an offset variable. If a hospital implemented the intervention in the middle of a month, we attributed the SSI rate for that month to the intervention period. To account for temporal autocorrelation within hospitals and for hospital-level clustering effects, we fit the models with generalized estimating equations, specifying a first-order autoregressive working correlation structure. We built separate models for each SSI outcome and for each operation group, using rate ratios to express the association between the intervention and the SSI outcome.
We obtained estimates of mean SSI rates for the preintervention and the intervention periods, and estimates of their corresponding differences, from Poisson regression models. To obtain CIs for the mean SSI rate differences for all operations, hip or knee arthroplasties, and cardiac operations, we analyzed monthly SSI rates using Gaussian linear regression models with an identity link. This model was fit using generalized estimating equations as previously described. Because the SSI rates were right-skewed, Gaussian regression was a suboptimal modeling framework in this setting, yet it provided a convenient method for obtaining interval estimates for mean rate differences.
Twenty urban hospitals in 9 US states met the eligibility criteria and were willing to participate in the study. Bed size ranged from 52 to 514 beds; 5 hospitals were minor teaching hospitals and 15 were nonteaching (eAppendix 2 in Supplement 2). Eight hospitals implemented the bundle for joint arthroplasties, 4 for cardiac operations, and 8 for both categories. Eleven hospitals (55%) implemented the bundle by July 1, 2012. One hospital stopped the intervention on March 31, 2013; 19 continued through March 31, 2014. The median preintervention period was 39 months (range, 39-43) and the median intervention period was 21 months (range, 14-22).
During the study period, participating sites performed 43 087 operations of interest (28 593 preintervention; 14 494 intervention). We removed 552 operations from this cohort: 292 were performed among pediatric patients, 219 were performed among patients with infections, and 41 were revision arthroplasties. The final study population was 42 534 operations among 38 049 unique patients (preintervention period, 28 218 operations; intervention period, 14 316 operations). Among patients undergoing cardiac operations, those during the intervention period were more likely to have diabetes mellitus than those during the preintervention period. Among patients having hip or knee arthroplasties, those during the intervention period were younger, had lower Charlson comorbidity index scores, and were less likely to have a history of MRSA carriage than those during the preintervention period (Table 1). During the intervention period, 2135 patients (14.9%) had documented β-lactam allergies.
During the preintervention period, there were 101 complex S aureus SSIs (MRSA, 45; MSSA, 44; unknown methicillin susceptibility, 12) compared with 29 during the intervention period (MRSA, 14; MSSA, 13; unknown methicillin susceptibility, 2) . In the patient-level analysis, a logistic regression model controlling for age, diabetes, Charlson comorbidity index, and MRSA history found that implementation of the bundle was associated with a significant reduction in complex S aureus SSIs (odds ratio [OR], 0.60 [95% CI, 0.37-0.98]). The number of months without any complex S aureus SSIs increased from 2 of 39 months (5.1%) to 8 of 22 months (36.4%; P = .006 by Fisher exact test). In the hospital-level time-series analysis, a Poisson regression model found that the monthly rates of complex S aureus SSIs decreased significantly from 36 to 21 per 10 000 operations (mean difference, −15 [95% CI, −35 to −2]; rate ratio [RR], 0.58 [95% CI, 0.37 to 0.92]) during the intervention (Figure 1 and Table 2). The rates of MRSA (RR, 0.60 [95% CI, 0.32 to 1.14]) and the rates of MSSA (RR, 0.64 [95% CI, 0.38 to 1.07]) complex SSIs did not change significantly when analyzed separately.
In the subgroup analyses, the rates of complex S aureus SSIs decreased significantly after scheduled operations (RR, 0.55 [95% CI, 0.35 to 0.86]) but did not decrease after urgent or emergent operations (Table 2). The rates of complex S aureus SSIs decreased significantly after hip or knee arthroplasties (difference per 10 000 operations, −17 [95% CI, −39 to 0]; RR, 0.48 [95% CI, 0.29 to 0.80]), whereas the rates of complex S aureus SSIs after cardiac operations did not (difference per 10 000 operations, −6 [95% CI, −48 to 8]; RR, 0.86 [95% CI, 0.47 to 1.57]). Similarly, the rates of all S aureus SSIs (mean rate per 10 000 operations, 47 for the preintervention period vs 30 for the intervention period; RR, 0.64 [95% CI, 0.38 to 1.09]), all gram-negative SSIs (mean rate per 10 000 operations, 28 for the preintervention period vs 23 for the intervention period; RR, 0.86 [95% CI, 0.42 to 1.75]), and of complex SSIs caused by any pathogen (mean rate per 10 000 operations, 68 for the preintervention period vs 45 for the intervention period; RR, 0.67 [95% CI, 0.44 to 1.00]) did not decrease significantly.
After a 3-month phase-in period, bundle adherence remained constant at 83% (full adherence, 39%; partial adherence, 44%; Figure 2). Figure 3 illustrates adherence by operation scheduling and by screening results; eFigure 1 in Supplement 2 illustrates adherence to each bundle element. The complex S aureus SSI rates decreased significantly among patients in the fully adherent group compared with the preintervention period (RR, 0.26 [95% CI, 0.10-0.69]), but rates did not decrease significantly in the partially adherent or nonadherent group (RR, 0.80 [95% CI, 0.49-1.31]).
During the intervention period, surgeons that implemented at least some bundle elements (fully and partially implemented) performed 10 850 scheduled operations (92.3%) and 909 emergent operations (7.7%). Among these surgeons, bundle adherence was 87.6% for scheduled operations (full adherence, 47.8%; partial adherence, 39.8%) compared with 61.8% for urgent or emergent operations (full adherence, 1.7%; partial adherence, 60.1%). The rates of complex S aureus SSIs decreased significantly (RR, 0.54 [95% CI, 0.34-0.88]) after operations performed by these surgeons, but not after operations done by surgeons that did not implement any bundle elements (RR, 0.80 [95% CI, 0.33-1.98]).
Patients reported they did not use mupirocin or CHG as directed before 328 operations. The most common reasons for nonadherence were problems with the prescription or supply (27.1%), patients forgot or did not understand instructions (18.0%), elements were not applicable (14.9%), allergy (2.1%), and patient preference (1.5%).
The median postoperative length of stay for both the preintervention and intervention periods was 3 days. A smaller proportion of patients was readmitted for SSIs within 90 days of their operations during the intervention period (0.12%) than during the preintervention period (0.21%; OR, 0.57 [95% CI, 0.33-0.97]). After adjusting for age, diabetes, Charlson comorbidity index, and MRSA history, the intervention was not associated with a significant decrease in postoperative length of stay (multiplicative mean decrease, 0.95 [95% CI, 0.87-1.03]) or readmissions (OR, 0.58 [95% CI, 0.22-1.52]).
Four patients reported mild skin irritation associated with preoperative CHG bathing; symptoms quickly abated when the product was discontinued. No patients reported adverse reactions to mupirocin.
Thirty-six S aureus isolates from wound cultures were tested for mupirocin and CHG susceptibility, of which 1 isolate had high-level resistance to mupirocin. CHG minimum inhibitory concentrations clustered at 1 to 2 µg/mL; 1 isolate had a CHG minimum inhibitory concentration of 4 µg/mL. No isolates carried qac.
This multicenter study showed that implementation of an SSI prevention bundle was associated with reduced S aureus SSI rates. We did not find evidence suggesting that SSIs caused by other pathogens replaced those caused by S aureus and we identified very few adverse events. These results are notable because this was a pragmatic study that included operations often excluded in randomized clinical trials (eg, emergent operations). To our knowledge, STOP SSI is the largest study to test an SSI prevention bundle under pragmatic clinical conditions. Even though the baseline rate of complex S aureus SSI was low (0.36 per 10 000 operations), the full adherence rate was only 39%, and hospitals had implemented some bundle elements before the study began, rates of complex S aureus SSIs decreased significantly. Given that approximately 400 000 cardiac operations and 1 million total joint arthroplasties are performed in the United States each year,25 numerous S aureus SSIs, which can have catastrophic consequences, may be preventable. Moreover, 1 SSI adds from $13 000 to $100 000 to the cost of health care.26-28 Thus, implementation of this bundle might reduce patient morbidity and the costs of care substantially.
Our results suggest that adherence to the full bundle is important. Given that adherence rates for patients who had urgent or emergent operations performed by surgeons who implemented the bundle were substantially lower than for patients who underwent scheduled operations, we hypothesize that institutional barriers may prevent full bundle adherence for patients undergoing urgent or emergent operations.
This bundle is concordant with current SSI prevention guidelines. For example, the bundle stipulates that vancomycin be given as perioperative prophylaxis only for patients who are MRSA-positive or for patients whose S aureus carriage status is unknown at the time of the operation, which meets Surgical Care Improvement Project criteria.29 Similarly, guidelines from ASHP, the Society of Thoracic Surgeons, the Infectious Diseases Society of America, the Surgical Infection Society, and the Society for Healthcare Epidemiology of America state that mupirocin may have utility among S aureus carriers, and that patients carrying MRSA should receive vancomycin and cefazolin or cefuroxime because vancomycin is not active against gram-negative organisms16,30 and it prevents MSSA SSIs less effectively than cefazolin or cefuroxime.8 Cefazolin or cefuroxime also provide some gram-negative coverage, which is important because these organisms cause an estimated 34% of SSIs after cardiac operations and 18% after total joint arthroplasty.11
Consistent with results of prior studies, only 1 S aureus isolate in this study had high-level resistance to mupirocin.31,32 As surgical patients are at risk for SSI during a relatively narrow period18 and 70% of S aureus nasal carriers treated preoperatively with mupirocin and CHG are still decolonized after a mean of 156 days,33 a single short course of mupirocin should be adequate to protect patients and minimize the risk of selecting resistant isolates.5 Although screening and decolonization are more difficult than treating all patients with intranasal mupirocin, we screened patients for MRSA and MSSA nasal carriage and treated carriers to lower the risk of resistance further.
This was a pragmatic study because each hospital implemented the bundle to accommodate their resources and practice patterns.14,15 Nevertheless, resources from the health system—a shared electronic medical record, a quality and infection prevention infrastructure, and corporate support for system-wide implementation of best practices—facilitated bundle implementation and data collection at individual hospitals. Recently, investigators demonstrated that bundled interventions for preventing catheter-related bloodstream infections34 or surgical complications35 can be maintained long-term. Similarly, the current bundle should be relatively simple to maintain because it does not require expensive technology or additional staff.
This study had limitations. First, surveillance for SSI varied somewhat among the hospitals. For example, some infection preventionists did active surveillance after discharge and some learned that specific patients had SSIs from other clinicians in the area. A survey conducted after the intervention found that sites had not changed surveillance practices during the study, which was more important to this study design than having all hospitals use identical surveillance methods, particularly because the primary outcome (complicated S aureus SSIs) should be identified by any surveillance system. Second, the study results may not be generalizable to large academic health centers or to hospitals without strong infrastructures for quality improvement. However, the results may be more generalizable than the results of most randomized trials because this pragmatic study more closely mimicked the clinical situation.14,15 Third, neither patients nor facilities were randomized and thus the results may be biased by regression to the mean, seasonal effects, or secular trends.36 However, these biases are unlikely because we compared monthly endemic SSI rates during a 39- to 43–month preintervention period and a 14- to 22–month intervention period, and modeling analyses did not identify evidence of long-term trends or seasonal effects over these periods. The results of the subset analyses also mitigate this concern because complex S aureus SSIs decreased significantly only among the subset of patients who had scheduled operations and the subset of fully adherent patients but not among the subset of patients who had urgent or emergent operations and the subset of partially adherent or nonadherent patients. If our results were due to temporal biases, the decrease would be seen among all subsets. Rolling implementation may have helped reduce the likelihood of bias due to seasonal maturation. Additionally, these hospitals did not change other aspects of SSI prevention or surveillance during the entire study. Last, we found some statistically significant differences in patient characteristics between the preintervention group and the intervention group. The presence of these measured confounders, and unmeasured confounders, could have led to biased results.
In this multicenter study, a bundle comprising S aureus screening, decolonization, and targeted prophylaxis was associated with a modest, statistically significant decrease in complex S aureus SSIs.
Corresponding Author: Loreen A. Herwaldt, MD, Department of Internal Medicine, University of Iowa Hospitals and Clinics, 200 Hawkins Dr, Iowa City, IA 52242 (email@example.com).
Author Contributions: Dr Schweizer had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Schweizer, Septimus, Braun, Hickok, Perencevich, Richards, Cavanaugh, Herwaldt.
Acquisition, analysis, or interpretation of data: Schweizer, Chiang, Septimus, Moody, Braun, Hafner, Ward, Hickok, Perencevich, Diekema, Richards, Cavanaugh, Perlin, Herwaldt.
Drafting of the manuscript: Schweizer, Chiang, Septimus, Moody, Ward, Cavanaugh, Herwaldt.
Critical revision of the manuscript for important intellectual content: Schweizer, Chiang, Septimus, Braun, Hafner, Hickok, Perencevich, Diekema, Richards, Cavanaugh, Perlin, Herwaldt.
Statistical analysis: Chiang, Septimus, Ward, Cavanaugh.
Obtained funding: Schweizer, Braun, Hafner, Perencevich, Richards, Cavanaugh, Perlin, Herwaldt.
Administrative, technical, or material support: Schweizer, Septimus, Moody, Braun, Hafner, Ward, Hickok, Diekema, Richards, Perlin.
Study supervision: Schweizer, Septimus, Braun, Hafner, Hickok, Perencevich, Cavanaugh, Perlin, Herwaldt.
Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Dr Septimus reports receiving support from Sage and Molnlycke. Ms Moody reports receiving grant funding from the Centers for Disease Control and Prevention (CDC) and the National Institutes of Health (NIH) and nonfinancial support from Sage and Molnlycke. Mr Hickok reports receiving grant support from the CDC and NIH and nonfinancial support from Sage and Molnlycke. Dr Perencevich reports receiving grant support from Cubist Pharmaceuticals. Dr Diekema reports being chair of the CDC Healthcare Infection Control Practices Advisory Committee and receiving grant funding from bioMerieux. Dr Perlin reports receiving grant funding from the CDC and nonfinancial support from Sage and Molnlycke. No other disclosures were reported.
Funding/Support: This project was funded by the Agency for Healthcare Research and Quality (AHRQ; HHSA2902006100021I and grant HS022467-02), US Department of Health and Human Services. It also received support from the VA Health Services Research and Development (CDA 11-211; Dr Schweizer).
Role of the Funder/Sponsor: The sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Disclaimer: The opinions expressed in this document are those of the authors and do not reflect the official position of AHRQ, the US Department of Health and Human Services, or the US Department of Veterans Affairs.
Additional Contributions: We thank our technical expert panel: Michael Banbury, MD; Dale Bratzler, DO, MPH; Joseph Buckwalter, MD, MS; E. Patchen Dellinger, MD; Richard Embrey, MD, MBA; Stephan Harbarth, MD; Keith Kaye, MD, MPH; Matthew Koff, MD; Randy Loftus, MD; Vincent Pellegrini, MD; James Steinberg, MD; and Edward Wong, MD. We would also like to thank Jacqueline Dourlet Drew (The Joint Commission) for administrative support and Caren Spencer-Smith, Lorraine Rognstad, Thomas Hoy, Lindsey Vanatta, Jennifer Singer, Amanda Foster, Nicholas Bryant, Praveen Komarraju, and Pridhviraj Nandarapu (all from HCA Information Technology) for informatics and data management services. We also thank Kacie Kleja, MS, and Joe Dunn, MA (HCA Clinical Services Group), for assistance with the creation and distribution of the preintervention and postintervention surveys, and Kim Korwek, PhD (HCA), for assistance with manuscript edits. We thank STOP SSI study liaisons and clinical champions for their outstanding efforts to collect data, encourage adherence, and provide site management: Janna Jernigan Matautia, Kathleen Wright, Mariamma Mathew, Michael Washington, and David Jason Oberste (Capital Regional Medical Center); Sheila Gebel, Denise Leaptrot, and Sande Day (Coliseum Medical Center); Manuel Feliberti and Pat Mayberry (Del Sol Medical Center); Larry Feinman, Paula (Doris) Bates, Julie Hunter, Cindy Pulley, and Olga Somek (Largo Medical Center); Michael Driks, Stacey Estes-Juve, Joan Jenne, and Mary Young (Lee’s Summit Medical Center); Muddasar Chaudry, Sheri Franklin, and Teresa Stowasser (Lewis Gale Medical Center); Stuart Gardner, Maribeth Coluni, and Teresa Kenyon (Lewis Gale Hospital—Montgomery); James Lovelace and Christine Ludwig (Lewis Gale Hospital—Pulaski); Mark Hebert, Leonard “Gale” Charns, Regina Suniga, and Christi Zumwalt (Medical City Dallas Hospital); Darien Bradford, Belinda Holley, Toni Polk, Sharon Kurtz, and Cynthia Brown (Medical Center of Arlington); Joe Johnston, Christopher Phelps, James Garrison Jr, Pablo Feuillet, Maria Robles, Mayra Castillo, Monica Yates, Patrice Stark, and Kelley Boston (Methodist Stone Oak Hospital); Preston Blake, Carol Harmon, Debra Douglas, and Laura Netardus (North Florida Regional Medical Center); Eric Keyser, Barbara Wallace, Marcy Frisina, and Sheryl Creech (Ocala Regional Medical Center); Aida Jimenez-Sanchez, Trudy Jackson, and Charlotte Evans (Osceola Regional Medical Center); David Itkin and Martha Wassell (Portsmouth Regional Hospital); Vanda Davidson, Charlotte Pate, and Clarence Book (Rapides Regional Medical Center); Richard Sall, Trudy Grillo, Cindy Robinson, and Anne Finnerty (Reston Hospital); Robert Maddalon, Eleanor Cardwell, and Debra Tichy (South Bay Hospital); Eric Stem, James Dalton Jr, William Jones, and Becky Robinson (Summerville Medical Center); Michaela Schulte, Teresa Jones, and Ginna Maggard (West Valley Medical Center). Members of the technical expert panel were compensated for their time from the AHRQ contract. No other contributors received compensation for their contribution.
et al. Nasal carriage of Staphylococcus aureus
as a major risk factor for wound infections after cardiac surgery. J Infect Dis
. 1995;171(1):216-219.PubMedGoogle ScholarCrossref
et al; Mupirocin And The Risk Of Staphylococcus Aureus Study Team. Intranasal mupirocin to prevent postoperative Staphylococcus aureus
infections. N Engl J Med
. 2002;346(24):1871-1877.PubMedGoogle ScholarCrossref
et al. Risk of methicillin-resistant Staphylococcus aureus
surgical site infection in patients with nasal MRSA colonization. Am J Infect Control
. 2013;41(12):1253-1257.PubMedGoogle ScholarCrossref
TM. The significance of nasal carriage of Staphylococcus aureus
and the incidence of postoperative wound infection. J Hosp Infect
. 1995;31(1):13-24.PubMedGoogle ScholarCrossref
et al. Preventing surgical site infections in nasal carriers of Staphylococcus aureus. N Engl J Med
. 2010;362(1):9-17.PubMedGoogle ScholarCrossref
et al. Vancomycin vs cefazolin prophylaxis for cardiac surgery in the setting of a high prevalence of methicillin-resistant staphylococcal infections. J Thorac Cardiovasc Surg
. 2002;123(2):326-332.PubMedGoogle ScholarCrossref
EE. Antibiotic prophylaxis in primary hip and knee arthroplasty: comparison between cefuroxime and 2 specific antistaphylococcal agents. J Arthroplasty
. 2010;25(7):1078-1082.PubMedGoogle ScholarCrossref
et al. Effectiveness of a bundled intervention of decolonization and prophylaxis to decrease Gram positive surgical site infections after cardiac or orthopedic surgery: systematic review and meta-analysis. BMJ
. 2013;346:f2743.PubMedGoogle ScholarCrossref
TM. Variable screening and decolonization protocols for Staphylococcus aureus
carriage prior to surgical procedures. Infect Control Hosp Epidemiol
. 2014;35(7):880-882.PubMedGoogle ScholarCrossref
et al. Current practice in Staphylococcus aureus
screening and decolonization. Infect Control Hosp Epidemiol
. 2011;32(10):1042-1044.PubMedGoogle ScholarCrossref
et al. Activity of commonly used antimicrobial prophylaxis regimens against pathogens causing coronary artery bypass graft and arthroplasty surgical site infections in the United States, 2006-2009. Infect Control Hosp Epidemiol
. 2014;35(3):231-239.PubMedGoogle ScholarCrossref
KS. Complex surgical site infections and the devilish details of risk adjustment: important implications for public reporting. Infect Control Hosp Epidemiol
. 2008;29(10):941-946.PubMedGoogle ScholarCrossref
et al; CONSORT group; Pragmatic Trials in Healthcare (Practihc) group. Improving the reporting of pragmatic trials: an extension of the CONSORT statement. BMJ
. 2008;337:a2390.PubMedGoogle ScholarCrossref
et al. A pragmatic-explanatory continuum indicator summary (PRECIS): a tool to help trial designers. J Clin Epidemiol
. 2009;62(5):464-475.PubMedGoogle ScholarCrossref
et al; American Society of Health-System Pharmacists; Infectious Disease Society of America; Surgical Infection Society; Society for Healthcare Epidemiology of America. Clinical practice guidelines for antimicrobial prophylaxis in surgery. Am J Health Syst Pharm
. 2013;70(3):195-283.PubMedGoogle ScholarCrossref
et al; National Healthcare Safety Network (NHSN) Team and Participating NHSN Facilities. Antimicrobial-resistant pathogens associated with health care–associated infections: summary of data reported to the National Healthcare Safety Network at the Centers for Disease Control and Prevention, 2009-2010. Infect Control Hosp Epidemiol
. 2013;34(1):1-14.PubMedGoogle ScholarCrossref
MC. Modern approaches to preventing surgical site infections. In: Wenzel
RP, ed. Prevention and Control of Nosocomial Infections.4th ed. Philadelphia, PA: Lippincott Williams & Wilkins; 2003:369.
et al. Beyond 30 days: does limiting the duration of surgical site infection follow-up limit detection? Infect Control Hosp Epidemiol
. 2012;33(2):202-204.PubMedGoogle ScholarCrossref
N. Evaluation of disc diffusion and Etest for determining the susceptibility of Staphylococcus aureus
to mupirocin. J Antimicrob Chemother
. 1998;42(5):577-583.PubMedGoogle ScholarCrossref
et al. Chlorhexidine and mupirocin susceptibilities of methicillin-resistant Staphylococcus aureus
from colonized nursing home residents. Antimicrob Agents Chemother
. 2013;57(1):552-558.PubMedGoogle ScholarCrossref
MA. Adapting a clinical comorbidity index for use with ICD-9-CM
administrative databases. J Clin Epidemiol
. 1992;45(6):613-619.PubMedGoogle ScholarCrossref
Agency for Healthcare Research and Quality. Healthcare Cost and Utilization Project net (HCUPnet) website.http://hcupnet.ahrq.gov/
. Accessed April 15, 2014.
EN, Vaughan Sarrazin
MS. Costs associated with surgical site infections in Veterans Affairs hospitals. JAMA Surg
. 2014;149(6):575-581.PubMedGoogle ScholarCrossref
et al. Determinants of hospital charges for coronary artery bypass surgery: the economic consequences of postoperative complications. Am J Cardiol
. 1990;65(5):309-313.PubMedGoogle ScholarCrossref
SR. Cost-effectiveness of preoperative nasal mupirocin treatment in preventing surgical site infection in patients undergoing total hip and knee arthroplasty: a cost-effectiveness analysis. Infect Control Hosp Epidemiol
. 2012;33(2):152-159.PubMedGoogle ScholarCrossref
et al; Workforce on Evidence-Based Medicine, Society of Thoracic Surgeons. The Society of Thoracic Surgeons practice guideline series: antibiotic prophylaxis in cardiac surgery, part II: antibiotic choice. Ann Thorac Surg
. 2007;83(4):1569-1576.PubMedGoogle ScholarCrossref
MJ. Clinical relevance of mupirocin resistance in Staphylococcus aureus. J Hosp Infect
. 2013;85(4):249-256.PubMedGoogle ScholarCrossref
MJ. Eradication of methicillin-resistant Staphylococcus aureus
carriage: a systematic review. Clin Infect Dis
. 2009;48(7):922-930.PubMedGoogle ScholarCrossref
III. The persistence of Staphylococcus aureus
decolonization after mupirocin and topical chlorhexidine: implications for patients requiring multiple or delayed procedures. J Arthroplasty
. 2012;27(6):870-876.PubMedGoogle ScholarCrossref
et al. An intervention to decrease catheter-related bloodstream infections in the ICU. N Engl J Med
. 2006;355(26):2725-2732. PubMedGoogle ScholarCrossref
et al; Safe Surgery Saves Lives Study Group. A surgical safety checklist to reduce morbidity and mortality in a global population. N Engl J Med
. 2009;360(5):491-499.PubMedGoogle ScholarCrossref
EN. The use and interpretation of quasi-experimental studies in infectious diseases. Clin Infect Dis
. 2004;38(11):1586-1591.PubMedGoogle ScholarCrossref