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Universal vs Risk Factor Screening for Methicillin-Resistant Staphylococcus aureus in a Large Multicenter Tertiary Care Facility in Canada

Published online by Cambridge University Press:  16 October 2015

V. R. Roth*
Affiliation:
Department of Medicine, the Ottawa Hospital and University of Ottawa, Ottawa, Ontario, Canada Ottawa Hospital Research Institute, Ottawa, Ontario, Canada Department of Epidemiology and Community Medicine, University of Ottawa, Ottawa, Ontario, Canada
T. Longpre
Affiliation:
Department of Epidemiology and Community Medicine, University of Ottawa, Ottawa, Ontario, Canada
M. Taljaard
Affiliation:
Ottawa Hospital Research Institute, Ottawa, Ontario, Canada Department of Epidemiology and Community Medicine, University of Ottawa, Ottawa, Ontario, Canada
D. Coyle
Affiliation:
Ottawa Hospital Research Institute, Ottawa, Ontario, Canada Department of Epidemiology and Community Medicine, University of Ottawa, Ottawa, Ontario, Canada
K. N. Suh
Affiliation:
Department of Medicine, the Ottawa Hospital and University of Ottawa, Ottawa, Ontario, Canada Ottawa Hospital Research Institute, Ottawa, Ontario, Canada Department of Epidemiology and Community Medicine, University of Ottawa, Ottawa, Ontario, Canada
K. A. Muldoon
Affiliation:
School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada
K. Ramotar
Affiliation:
Ottawa Hospital Research Institute, Ottawa, Ontario, Canada Department of Pathology and Laboratory Medicine, Ottawa Hospital and University of Ottawa, Ottawa, Ontario, Canada
A. Forster
Affiliation:
Department of Medicine, the Ottawa Hospital and University of Ottawa, Ottawa, Ontario, Canada Ottawa Hospital Research Institute, Ottawa, Ontario, Canada Department of Epidemiology and Community Medicine, University of Ottawa, Ottawa, Ontario, Canada
*
Address correspondence to V. R. Roth, MD, Ottawa Hospital, Division of Infectious Diseases, 501 Smyth Rd, Ottawa, ON. K1H 8L6 (vroth@toh.on.ca).
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Abstract

OBJECTIVE

To assess the clinical effectiveness of a universal screening program compared with a risk factor–based program in reducing the rates of nosocomial methicillin-resistant Staphylococcus aureus (MRSA) among admitted patients at the Ottawa Hospital.

DESIGN

Quasi-experimental study.

SETTING

Ottawa Hospital, a multicenter tertiary care facility with 3 main campuses, approximately 47,000 admissions per year, and 1,200 beds.

METHODS

From January 1, 2006 through December 31, 2007 (24 months), admitted patients underwent risk factor–based MRSA screening. From January 1, 2008 through August 31, 2009 (20 months), all patients admitted underwent universal MRSA screening. To measure the effectiveness of this intervention, segmented regression modeling was used to examine monthly nosocomial MRSA incidence rates per 100,000 patient-days before and during the intervention period. To assess secular trends, nosocomial Clostridium difficile infection, mupirocin prescriptions, and regional MRSA rates were investigated as controls.

RESULTS

The nosocomial MRSA incidence rate was 46.79 cases per 100,000 patient-days, with no significant differences before and after intervention. The MRSA detection rate per 1,000 admissions increased from 9.8 during risk factor–based screening to 26.2 during universal screening. A total of 644 new nosocomial MRSA cases were observed in 1,448,488 patient-days, 323 during risk factor–based screening and 321 during universal screening. Secular trends in C. difficile infection rates and mupirocin prescriptions remained stable after the intervention whereas population-level MRSA rates decreased.

CONCLUSION

At Ottawa Hospital, the introduction of universal MRSA admission screening did not significantly affect the rates of nosocomial MRSA compared with risk factor–based screening.

Infect. Control Hosp. Epidemiol. 2015;37(1):41–48

Type
Original Articles
Copyright
© 2015 by The Society for Healthcare Epidemiology of America. All rights reserved 

Infections caused by methicillin-resistant Staphylococcus aureus (MRSA) are associated with higher hospital readmission rates, poorer prognosis, and increased mortality compared with infections caused by susceptible strains.Reference Haessler, Mackenzie and Kirkland 1 Reference Shorr, Combes, Kollef and Chastre 6 Healthcare organizations have been challenged with implementing effective infection control strategies to reduce the risk of nosocomial MRSA transmission. The emergence of community MRSA compounds this challenge.Reference Stryjewski and Corey 7 Because 85%–90% of patients with MRSA are asymptomatic carriers who can serve as a silent reservoir for further transmission,Reference Salgado, Farr and Calfee 8 screening patients for MRSA on admission to the hospital using rapid detection methods has the potential to identify asymptomatic carriers early, thereby allowing timely implementation of infection control measures.Reference Sehulster, Chinn, ; and ; 9 , Reference Muto, Jernigan and Ostrowsky 10

There is conflicting evidence regarding which admission screening approach is most clinically effective in reducing nosocomial MRSA transmission and infection.Reference Ziakas, Zacharioudakis, Zervou and Mylonakis 11 Reference Leonhardt, Yakusheva and Phelan 20 Whereas risk factor–based screening applies to select patients with certain risk factors for MRSA, universal screening applies to all patients. A recent systematic review demonstrated that there is insufficient evidence to support or refute the utility of universal screening.Reference Glick, Samson, Huang, Vats, Aronson and Weber 21 Our objective was to assess the clinical effectiveness of using a hospital-wide universal MRSA admission screening compared with risk factor–based screening for reducing nosocomial MRSA transmission.

METHODS

Study Design and Setting

This was a quasi-experimental study conducted at the Ottawa Hospital, a large multicenter tertiary care facility. There are approximately 47,000 admissions per year and approximately 1,200 medical, surgical, obstetrical, critical care, mental health, and rehabilitation beds. 22

This study took place during 2 periods. From January 1, 2006 through December 31, 2007 (24 months), patients were screened for MRSA through a standard risk factor–based approach if 1 or more of the following signs were identified at the time of admission: previous hospitalization in the past 6 months, direct transfer from another healthcare facility, or history of MRSA colonization or infection. From January 1, 2008 through August 31, 2009 (20 months), all admitted patients (excluding newborns) underwent universal MRSA screening.

Throughout both phases, all patients with MRSA from a screening or clinical specimen were placed on contact precautions in a private room with dedicated patient care equipment for the duration of their hospitalization and for subsequent admissions. In addition to hand hygiene upon room entry and exit, all staff were required to wear gloves and gowns to enter the room. Decolonization was not routinely performed.

Data Collection

The data required for this analysis were obtained from the Ottawa Hospital Data Warehouse, a relational database that links clinical, laboratory, and administrative data using common identification keys. Data were collected at monthly intervals in order to improve rate stability at each data point.

Primary Outcome

The primary outcome of interest was the nosocomial MRSA incidence rate, calculated as the total number of newly identified nosocomial MRSA patients per 100,000 patient-days. This included patients identified through screening swabs or clinical specimens obtained more than 48 hours after admission, excluding patients previously known to be colonized or infected with MRSA.Reference Klevens, Morrison and Nadle 23 At our institution, only a minority of nosocomial MRSA patients are identified through clinical specimens.Reference Conterno, Shymanski and Ramotar 24

Secondary Outcomes

Throughout both study periods infection control measures, with the exception of screening, remained constant. However, other events external to the intervention could have potentially impacted the nosocomial MRSA rates. Both internal and external control groups were included in order to control for potential threats to validity.

The incidence of nosocomial Clostridium difficile infection (CDI) was used as the internal comparison group because hand hygiene adherence, environmental cleaning practices, and adherence to isolation protocols on nosocomial MRSA were expected to lead to a corresponding impact on nosocomial CDI incidence rates. Thus, any decrease in nosocomial MRSA incidence rates, in the face of constant or increased nosocomial CDI incidence rates, was more likely attributable to the screening intervention. A nosocomial CDI case was defined as any patient with onset of diarrhea 72 hours or more after admission and laboratory confirmation by a positive toxin assay result for C. difficile.

MRSA decolonization therapy may theoretically reduce the in-hospital reservoir of MRSA. Data were collected on the number of inpatients who received mupirocin, a topical antibiotic that is standard therapy for MRSA decolonization. Because MRSA decolonization is not routinely performed, this remains the predominant indication for mupirocin use in our inpatient setting. A decrease in nosocomial MRSA incidence at the Ottawa Hospital while mupirocin incidence rates remained constant would be more likely attributable to the screening intervention than to decolonization practices.

To account for the population prevalence of MRSA in the community, regional MRSA rates (ie, the incidence of MRSA in the region per 100,000 population) were used as the external comparison. The Ottawa Hospital is the sole adult tertiary care center within the Champlain Local Health Integration Network, a health region spanning approximately 18,000 square kilometers with a population of 1.2 million. 25 Hospital and private laboratories in the Champlain health region submitted MRSA isolates and basic epidemiologic data on a voluntary basis to the Microbiology Division of the Ottawa Hospital. Each patient was attributed to only 1 positive MRSA test (always the first 1 detected). The regional rates were calculated as all newly identified MRSA-positive cases in the Champlain health region per 100,000 population. A decrease in nosocomial MRSA incidence at the Ottawa Hospital while regional MRSA incidence remained constant or increased would be more likely attributable to the screening intervention than external factors.

Demographic and Clinical Characteristics

Data extracted from the Ottawa Hospital Data Warehouse for all inpatients included demographic information such as sex, age, campus of admission, admission date, discharge date, total days in the intensive care unit, number of acute care inpatient-days, number of patients in the hospital per day (patient-days), mortality rate, and the Charlson Comorbidity Index.Reference Charlson, Pompei, Ales and MacKenzie 26

Laboratory Methods

Screening swab specimens were obtained from the nares and rectum of each patient, as well as from any open skin lesions (up to a maximum of 2 sites) and catheter exit sites, where applicable. Swabs were inoculated into selective broths, incubated overnight, and tested using a commercial real-time polymerase chain reaction assay. The polymerase chain reaction test has a negative predictive value of 98%; however, with a lower positive predictive value of 65%, broth samples positive by polymerase chain reaction undergo culture confirmation.Reference Conterno, Shymanski and Ramotar 24 Those patients who tested positive by polymerase chain reaction but whose culture results were negative were considered to be false-positives and had their contact precautions discontinued. Results were generally available within 24 hours of specimen collection.

Statistical Analysis

All statistical analyses were conducted using SAS, version 9.1 (SAS Institute). Proportions and percentages were used to display the frequency of all categorical variables. Medians and interquartile ranges were used to display the distribution of continuous variables. Where specified, rates were calculated based on incident cases per 100,000 patient-days.

Controlling for seasonality, a pattern in the data that may be due to seasonal trends or fluctuations, requires at least 12 data points before and 12 after the intervention collected at equally spaced intervals.Reference Carroll 27 , Reference Wagner, Soumerai, Zhang and Ross-Degnan 28 A total of 44 time points (24 preintervention and 20 postintervention) were used and the presence of a seasonal effect was examined using the Dickey-Fuller unit root test and residual plots.Reference Carroll 27 Residual plots and the Durbin-Watson statistic were used to examine the presence of serial autocorrelation. When significant autocorrelation was detected, this was accounted for in the analysis by including the autocorrelation parameter in the segmented regression model. To account for a possible delayed effect of the intervention, all patients screened within the first month of the intervention were excluded from the analyses. Overdispersion, described as extravariability arising from events that may not be considered independent, is often a result of uncontrolled experimental conditions.Reference Pedan 29 A dispersion parameter was introduced into the relationship between the variance and the mean to account for any overdispersion in the model. The dispersion parameter was estimated using both the deviance and Pearson χ2 statistic divided by the degrees of freedom.

Segmented regression analysis of interrupted time series data was chosen because it is able to estimate dynamic changes in various processes and outcomes following intervention intended to change the MRSA transmission rate, while controlling for secular changes that may have occurred in the absence of the intervention. Segmented regression controls for preintervention trends, estimates the size of the intervention effect at different time points, and evaluates changes in trends over time.Reference Carroll 27 Four regression models were constructed to investigate the primary outcome of interest (nosocomial MRSA rates) and 3 secondary outcomes (nosocomial CDI rates, mupirocin prescription rate, regional MRSA rates). Ethics approval was obtained from the Ottawa Hospital Research Ethics Board (ID: 2008620-01H).

RESULTS

Description of the Ottawa Hospital Population

From January 1, 2006 through August 31, 2009, the Ottawa Hospital admitted 147,975 patients. Approximately 57% of the inpatient hospital population was female, with a median (interquartile range) age of 57.0 (37.0–72.0) years. The median (interquartile range) hospitalization was 3.0 (2.0–7.0) days, and 6,820 patients (4.6%) were admitted to the intensive care unit during their encounter. A total of 6,118 inpatients (4.1%) died during their hospitalization. There were no clinically significant differences in the hospital population in the pre- and postintervention periods (Table 1).

TABLE 1 Demographic and Clinical Characteristics of Patients Admitted to Ottawa Hospital January 1, 2006–August 31, 2009

NOTE. Pre- and postintervention totals will not add to total because January 2008 was excluded from intervention months to allow for an integration period. ICU, intensive care unit; IQR, interquartile range.

Description of Nosocomial MRSA Within the Ottawa Hospital

During the study period, there was a total of 644 newly identified nosocomial MRSA cases, 323 cases in the preintervention period and 321 in the postintervention period, for an incidence rate of 41.8 per 100,000 patient-days and 47.5 per 100,000 patient-days, respectively (Table 2). MRSA bacteremia occurred in 28 patients, 14 in each study period, for an incidence rate of 1.8 per 100,000 patient-days in the preintervention period and 2.1 per 100,000 patient-days in the postintervention period. The graphical presentation of pre- and postintervention nosocomial MRSA rates per 100,000 patient-days in Figure 1 shows near-identical pre- and postintervention trends.

FIGURE 1 Rates of nosocomial methicillin-resistant Staphylococcus aureus before and after intervention, per 100,000 patient-days (pt days), January 1, 2006–August 31, 2009.

TABLE 2 Summary of Nosocomial MRSA Cases at the Ottawa Hospital Before and After Implementation of Universal Screening

NOTE. Data excludes newborns. MRSA, methicillin-resistant Staphylococcus aureus.

In the preintervention period under risk factor–based screening, 29.2% (22,271/76,273) of admitted patients were screened within 48 hours of admission compared with 83.9% (51,815/61,782) of admitted patients in the postintervention period using universal screening. Of 76,273 patients screened during the preintervention phase, 745 (1.0%) were positive for MRSA (both previously known and newly identified). Of the 61,782 patients screened during the postintervention phase, 1,621 (2.6%) were MRSA positive. This resulted in a detection rate of 9.8 per 1,000 admitted patients before intervention and 26.2 per 1,000 admitted patients after intervention. The number of newly identified MRSA cases on admission increased from 132 (1.73 per 1,000 admissions) to 273 (4.42 per 1,000 admissions).

Statistical tests investigating the effects of seasonality were not significant. However, negative autocorrelation was detected in the rates of mupirocin prescriptions (P=.020) and positive autocorrelation was detected in the regional rate of MRSA (P=.001) and were therefore adjusted for in the final analysis. Overdispersion was also accounted for in all models because this is a more conservative approach to account for any variability that may have occurred owing to uncontrolled factors.

Segmented Regression Modeling

Table 3 displays the results from the segmented regression modeling. There was no significant change in the monthly rate of nosocomial MRSA from the preintervention to the postintervention phases. At baseline there were 46.79 MRSA cases detected per 100,000 patient-days (Model 1). The preintervention time trend was stable and not significantly different from 0 over the 24 months before the intervention. Immediately following the intervention, there was a nonsignificant decrease in the number of MRSA cases detected through universal screening (1.11 cases per 100,000 patient-days). Over the 20 months of the universal screening, there was a nonsignificant decrease in the monthly rate of MRSA transmission by 0.21 cases per 100,000 patient-days.

TABLE 3 Segmented Regression Analyses Modeling Baseline Rates, Intervention-Specific and Secular Changes Over Time for MRSA Rates, and 3 Secondary Outcomes of CDI Rates, Mupirocin Prescription Rates, and Regional MRSA Rates

NOTE. CDI, Clostridium difficile infection; MRSA, methicillin-resistant Staphylococcus aureus.

Model 2 indicates a baseline nosocomial CDI rate of 41.01 cases per 100,000 patient-days. Significant decreases in the rates of nosocomial CDI were recorded in the risk factor–screening phase (P=.026). There were no significant changes immediately following the intervention or during the postintervention period. This model suggests that there were no significant secular trends detected that would differentially influence nosocomial CDI or MRSA transmission.

Model 3 indicates a baseline rate of 76.22 mupirocin prescriptions per 100,000 patient-days. There were no significant changes in the prescription rate in the preintervention phase, immediately following the intervention, or in the postintervention phase. This model suggests that the rates of mupirocin prescriptions were stable over time and unlikely to affect the MRSA reservoir.

Model 4 displays a baseline regional MRSA rate of 7.39 per 100,000 patient-days. The results suggest a small increasing trend in monthly rates before the intervention (P=.017) and a small decreasing trend in monthly rates after the intervention (P=.004). These results suggest that despite a population-level decrease in the regional MRSA rates, this trend was not mirrored in nosocomial MRSA rates in the Ottawa Hospital.

DISCUSSION

We found that universal MRSA admission screening improved the detection of MRSA by almost 3-fold compared with risk factor–based screening. Despite improved detection, universal screening was not more effective in reducing nosocomial MRSA transmission in our hospital. The strength of this study is the use of internal controls to address potential threats to internal validity by means of competing measures (eg, improved hand hygiene, environmental cleaning, decolonization). Furthermore, we observed a decrease in regional MRSA rates that was not mirrored in our nosocomial rates, further strengthening the validity of our results. The reasons for this decrease are not clear because there was no regionwide intervention introduced during this period. However, similar decreases were noted in other health regions during this period. 30 , 31

Several factors may explain why universal screening did not prove beneficial in our patient population. Adherence to infection control practices is difficult to enforce and measure, and changes in adherence may alter the impact of the intervention. Although we attempted to account for this by using an internal control group, it is possible that the effects were more noticeable within the MRSA rates than the CDI rates. Additionally, other studies have suggested that universal screening may be beneficial only in the setting of high MRSA prevalence.Reference Otter, Tosas-Auguet and Herdman 13 , Reference Forrester and Pettitt 32 Reference Murthy, De Angelis, Pittet, Schrenzel, Uckay and Harbarth 35 Our MRSA prevalence was moderately low (2.6% of admitted patients) compared with prevalence rates in other studies that range from 1.7% to 10%.Reference Robicsek, Beaumont and Paule 16 , Reference Leonhardt, Yakusheva and Phelan 20 , Reference Otter, Herdman, Williams, Tosas, Edgeworth and French 36 Reference Parvez, Jinadatha and Fader 39 This may have lessened the effects of the intervention. Finally, our adherence to universal screening averaged approximately 84% and we are unable to determine whether a higher adherence to admission screening would have altered our results. Nonetheless, our adherence rate is comparable with that of other studiesReference Cairns, Packer, Reilly and Leanord 12 , Reference Robicsek, Beaumont and Paule 16 , Reference Reilly, Stewart and Christie 17 , Reference Leonhardt, Yakusheva and Phelan 20 , Reference Williams, Callery, Vearncombe and Simor 37 and we believe it is a realistic reflection of hospital function.

To the best of our knowledge, this is the first study to compare the clinical effectiveness of a hospital-wide universal MRSA screening intervention in reducing the nosocomial transmission of MRSA compared with risk factor–based screening using robust data and analytical techniques to control for confounding and secular trends.Reference Glick, Samson, Huang, Vats, Aronson and Weber 21 Two previously published studies suggest that universal screening may reduce the incidence of MRSA infections compared with targeted screening, although this difference was significant in only 1 study.Reference Robicsek, Beaumont and Paule 16 , Reference Leonhardt, Yakusheva and Phelan 20 Although the development of MRSA infection is an important health outcome, it represents only a small proportion of patients who acquire MRSA during their hospital stay.Reference Salgado and Farr 40 Such patients serve as a reservoir for further MRSA transmission and are at considerable risk for subsequent MRSA infections after hospital discharge.Reference Huang, Hinrichsen and Datta 41 We chose MRSA transmission rates as our primary outcome measure to provide a more direct assessment of the impact of universal screening on nosocomial MRSA acquisition and the associated reservoir.

Because the results from this study indicated that universal admission screening for MRSA was not clinically effective in reducing nosocomial transmission, our universal screening program was discontinued. We analyzed the data from our universal screening program to develop a prediction rule for MRSA carriage. Since 2010, only high-risk patients as determined by the prediction rule are screened for MRSA on admission (ie, patients admitted through the emergency department, direct transfers from another institution, admissions to an intensive care unit, and admissions to the rehabilitation center).

Although every effort was made to follow sound epidemiologic principles in the design and analysis of this study, some limitations were noted. First, as discussed above, we did not achieve 100% adherence to universal screening. Second, we used a composite measure of nosocomial MRSA including both surveillance swabs and clinical specimens obtained more than 48 hours after admission; as a result we cannot accurately quantify the contribution of each individual approach in case detection. Additionally, we did not conduct discharge surveillance cultures and therefore may have missed some nosocomial cases. Finally, reporting of regional MRSA data was voluntary and incomplete because data were missing from 1 of the 22 area hospitals for the final 2 months of the study period. This is unlikely to have a significant impact on the overall regional rates or to affect the primary outcome of this analysis.

In conclusion, these findings provide further evidence that hospital-wide universal MRSA admission screening is not clinically effective in reducing the nosocomial transmission of MRSA.Reference Leonhardt, Yakusheva and Phelan 20 , Reference Harbarth, Fankhauser and Schrenzel 38 , Reference Girou, Azar, Wolkenstein, Cizeau, Brun-Buisson and Roujeau 42 Reference McKinnell, Bartsch, Lee, Huang and Miller 45 Although MRSA control measures continue to be the subject of much debate, the rates of nosocomial transmission and infection have decreased at the same time as the implementation of local and national control programs.Reference Otter, Tosas-Auguet and Herdman 13 , 15 , 30 , Reference Jarvis, Jarvis and Chinn 46 With increasing evidence that decolonization is an important component of MRSA control,Reference Robotham, Jenkins and Medley 44 , Reference Gidengil, Gay, Huang, Platt, Yokoe and Lee 47 , Reference Huang, Septimus and Kleinman 48 universal decolonization has been proposed owing to its simplicity and the avoidance of screening cultures.Reference Huang, Septimus and Kleinman 48 However, the emergence of resistance is predictable with indiscriminate antimicrobial use and may circumvent any long-term benefits of universal decolonization.Reference Huang, Septimus and Kleinman 48 Reference Robotham, Graves and Cookson 50 These results have directly informed practice at the Ottawa Hospital and have been used to develop a prediction rule to enhance a risk factor–based screening approach to improve the identification of patients at high risk for MRSA on admission.

ACKNOWLEDGMENTS

Financial support. None reported.

Potential conflicts of interest. All authors report no conflicts of interest relevant to this article.

References

REFERENCES

1. Haessler, S, Mackenzie, T, Kirkland, KB. Long-term outcomes following infection with meticillin-resistant or meticillin-susceptible Staphylococcus aureus . J Hosp Infect 2008;69:3945; doi:10.1016/j.jhin.2008.01.008.Google Scholar
2. Blot, SI, Vandewoude, KH, Hoste, EA, Colardyn, FA. Outcome and attributable mortality in critically ill patients with bacteremia involving methicillin-susceptible and methicillin-resistant Staphylococcus aureus . Arch Intern Med 2002;162:22292235; doi:10.1001/archinte.162.19.2229.Google Scholar
3. Lodise, TP, McKinnon, PS. Clinical and economic impact of methicillin resistance in patients with Staphylococcus aureus bacteremia. Diagn Microbiol Infect Dis 2005;52:113122; doi:10.1016/j.diagmicrobio.2005.02.007.Google Scholar
4. Kopp, BJ, Nix, DE, Armstrong, EP. Clinical and economic analysis of methicillin-susceptible and -resistant Staphylococcus aureus infections. Ann Pharmacother 2004;38:13771382; doi:10.1345/aph.1E028.Google Scholar
5. Rello, J, Torres, A, Ricart, M, et al. Ventilator-associated pneumonia by Staphylococcus aureus: comparison of methicillin-resistant and methicillin-sensitive episodes. Am J Respir Crit Care Med 1994;150:15451549; doi:10.1164/ajrccm.150.6.7952612.CrossRefGoogle ScholarPubMed
6. Shorr, AF, Combes, A, Kollef, MH, Chastre, J. Methicillin-resistant Staphylococcus aureus prolongs intensive care unit stay in ventilator-associated pneumonia, despite initially appropriate antibiotic therapy. Crit Care Med 2006;34:700706; doi:10.1097/01.CCM.0000201885.57697.21.Google Scholar
7. Stryjewski, ME, Corey, GR. Methicillin-resistant Staphylococcus aureus: an evolving pathogen. Clin Infect Dis 2014;58:1019; doi:10.1093/cid/cit613.Google Scholar
8. Salgado, CD, Farr, BM, Calfee, DP. Community-acquired methicillin-resistant Staphylococcus aureus: a meta-analysis of prevalence and risk factors. Clin Infect Dis 2003;36:131139; doi:10.1086/345436.Google Scholar
9. Sehulster, L, Chinn, RY ;, CDC ;, HICPAC. Guidelines for environmental infection control in health-care facilities. Recommendations of CDC and the Healthcare Infection Control Practices Advisory Committee (HICPAC). MMWR Recomm Rep 2003;52:142.Google Scholar
10. Muto, CA, Jernigan, JA, Ostrowsky, BE, et al. SHEA guideline for preventing nosocomial transmission of multidrug-resistant strains of Staphylococcus aureus and Enterococcus . Infect Control Hosp Epidemiol 2003;24:362386; doi:10.1086/502213.CrossRefGoogle ScholarPubMed
11. Ziakas, P, Zacharioudakis, IM, Zervou, FN, Mylonakis, E. Methicillin-resistant Staphylococcus aureus prevention strategies in the ICU: a clinical decision analysis. Crit Care Med 2015;43:382393; doi:10.1097/CCM.0000000000000711.CrossRefGoogle ScholarPubMed
12. Cairns, S, Packer, S, Reilly, J, Leanord, A. Targeted MRSA screening can be as effective as universal screening. Br Med J 2014;349:g5075. doi:10.1136/bmj.g5075.CrossRefGoogle ScholarPubMed
13. Otter, JA, Tosas-Auguet, O, Herdman, MT, et al. Implications of targeted versus universal admission screening for meticillin-resistant Staphylococcus aureus carriage in a London hospital. J Hosp Infect 2014;87:171174; doi:10.1016/j.jhin.2014.04.005.Google Scholar
14. Edmond, MB, Wenzel, RP. Screening inpatients for MRSA—case closed. N Engl J Med 2013;368:23142315; doi:10.1056/NEJMe1304831.CrossRefGoogle ScholarPubMed
15. National Services Scotland. NHS Scotland MRSA Screening Pathfinder Programme. Edinburgh, Scotland; 2011.Google Scholar
16. Robicsek, A, Beaumont, JL, Paule, SM, et al. Universal surveillance for methicillin-resistant Staphylococcus aureus in 3 affiliated hospitals. Ann Intern Med 2008;148:409418; doi:10.7326/0003-4819-148-6-200803180-00003.Google Scholar
17. Reilly, JS, Stewart, S, Christie, P, et al. Universal screening for meticillin-resistant Staphylococcus aureus: interim results from the NHS Scotland pathfinder project. J Hosp Infect 2010;74:3541; doi:10.1016/j.jhin.2009.08.013.CrossRefGoogle ScholarPubMed
18. Lee, BY, Bailey, RR, Smith, KJ, et al. Universal methicillin-resistant Staphylococcus aureus (MRSA) surveillance for adults at hospital admission: an economic model and analysis. Infect Control Hosp Epidemiol 2010;31:598606; doi:10.1086/652524.Google Scholar
19. Jain, R, Kralovic, SM, Evans, ME, et al. Veterans Affairs initiative to prevent methicillin-resistant Staphylococcus aureus infections. N Engl J Med 2011;364:14191430; doi:10.1056/NEJMoa1007474.Google Scholar
20. Leonhardt, KK, Yakusheva, O, Phelan, D, et al. Clinical effectiveness and cost benefit of universal versus targeted methicillin-resistant Staphylococcus aureus screening upon admission in hospitals. Infect Control Hosp Epidemiol 2011;32:797803; doi:10.1086/660875.Google Scholar
21. Glick, SB, Samson, DJ, Huang, ES, Vats, V, Aronson, N, Weber, SG. Screening for methicillin-resistant Staphylococcus aureus: a comparative effectiveness review. Am J Infect Control 2014;42:148155. doi:10.1016/j.ajic.2013.07.020.Google Scholar
22. Ottawa Hospital Annual Report. Compassionate People: World Class Care. Ottawa; 2014.Google Scholar
23. Klevens, R, Morrison, MA, Nadle, J, et al. Invasive methicillin-resistant Staphylococcus aureus infections in the United States. JAMA 2007;298:17631771; doi:10.1016/S0084-3954(08)79046-8.Google Scholar
24. Conterno, LO, Shymanski, J, Ramotar, K, et al. Real-time polymerase chain reaction detection of methicillin-resistant Staphylococcus aureus: impact on nosocomial transmission and costs. Infect Control Hosp Epidemiol 2007;28:11341141; doi:10.1086/520099.Google Scholar
25. Champlain Local Health Integration Network. Champlain LHIN: Integrated Health Service Plan 2010–2013. Ottawa; 2009.Google Scholar
26. Charlson, ME, Pompei, P, Ales, KL, MacKenzie, CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 1987;40:373383.Google Scholar
27. Carroll, N. Application of segmented regression analysis to the Kaiser Permanente Colorado Critical Drug Interaction Program. In Proceedings of the Western Users of SAS Software 2008 Conference. Universal City, CA: SAS; 2008:1–8.Google Scholar
28. Wagner, AK, Soumerai, SB, Zhang, F, Ross-Degnan, D. Segmented regression analysis of interrupted time series studies in medication use research. J Clin Pharm Ther 2002;27:299309; doi:10.1046/j.1365-2710.2002.00430.x.CrossRefGoogle ScholarPubMed
29. Pedan, A. Analysis of count data using the SAS system. Stat Data Anal Data Min 2001;247:16.Google Scholar
30. Canadian Nosocomial Infection Surveillance Program (CNISP). Results of the Surveillance of Methicillin Resistant Staphylococcus aureus: From 1995-2009. Ottawa; 2010.Google Scholar
31. European Antimicrobial Resistance Surveillance System (EARSS). EARSS Annual Report 2008. Amsterdam; 2009.Google Scholar
32. Forrester, M, Pettitt, AN. Use of stochastic epidemic modeling to quantify transmission rates of colonization with methicillin-resistant Staphylococcus aureus in an intensive care unit. Infect Control Hosp Epidemiol 2005;26:598606; doi:10.1086/502588.Google Scholar
33. Rubin, RJ, Harrington, CA, Poon, A, Dietrich, K, Greene, JA, Moiduddin, A. The economic impact of Staphylococcus aureus infection in New York City hospitals. Emerg Infect Dis 1999;5:917; doi:10.3201/eid0501.990102.Google Scholar
34. Harbarth, S, Rutschmann, O, Sudre, P, Pittet, D. Impact of methicillin resistance on the outcome of patients with bacteremia caused by Staphylococcus aureus . Arch Intern Med 1998;158:182189.CrossRefGoogle ScholarPubMed
35. Murthy, A, De Angelis, G, Pittet, D, Schrenzel, J, Uckay, I, Harbarth, S. Cost-effectiveness of universal MRSA screening on admission to surgery. Clin Microbiol Infect 2010;16:17471753; doi:10.1111/j.1469-0691.2010.03220.x.Google Scholar
36. Otter, JA, Herdman, MT, Williams, B, Tosas, O, Edgeworth, JD, French, GL. Low prevalence of meticillin-resistant Staphylococcus aureus carriage at hospital admission: implications for risk-factor-based vs universal screening. J Hosp Infect 2013;83:114121; doi:10.1016/j.jhin.2012.10.008.CrossRefGoogle ScholarPubMed
37. Williams, VR, Callery, S, Vearncombe, M, Simor, AE. Universal versus targeted active surveillance for methicillin-resistant Staphylococcus aureus in medical patients. Can J Infect Control 2011;26:105112.Google Scholar
38. Harbarth, S, Fankhauser, C, Schrenzel, J, et al. Universal screening for methicillin-resistant Staphylococcus aureus at hospital admission and nosocomial infection in surgical patients. JAMA 2008;299:11491157; doi:10.1016/S0090-3671(09)79472-8.CrossRefGoogle ScholarPubMed
39. Parvez, N, Jinadatha, C, Fader, R, et al. Universal MRSA nasal surveillance: characterization of outcomes at a tertiary care center and implications for infection control. South Med Assoc 2010;103:10841091.Google Scholar
40. Salgado, CD, Farr, BM. What proportion of hospital patients colonized with methicillin-resistant Staphylococcus aureus are identified by clinical microbiological cultures? Infect Control Hosp Epidemiol 2006;27:116121; doi:10.1086/500624.Google Scholar
41. Huang, SS, Hinrichsen, VL, Datta, R, et al. Methicillin-resistant Staphylococcus aureus infection and hospitalization in high-risk patients in the year following detection. PLOS ONE 2011;6:e24340. doi:10.1371/journal.pone.0024340.Google Scholar
42. Girou, E, Azar, J, Wolkenstein, P, Cizeau, F, Brun-Buisson, C, Roujeau, JC. Comparison of systematic versus selective screening for methicillin-resistant Staphylococcus aureus carriage in a high-risk dermatology ward. Infect Control Hosp Epidemiol 2000;21:583587; doi:10.1086/501807.Google Scholar
43. Wibbenmeyer, L, Appelgate, D, Williams, I, et al. Effectiveness of universal screening for vancomycin-resistant enterococcus and methicillin-resistant Staphylococcus aureus on admission to a burn-trauma step-down unit. J Burn Care Res 2009;30:648656; doi:10.1097/BCR.0b013e3181abff7e.Google Scholar
44. Robotham, JV, Jenkins, DR, Medley, GF. Screening strategies in surveillance and control of methicillin-resistant Staphylococcus aureus (MRSA). Epidemiol Infect 2007;135:328342; doi:10.1017/S095026880600687X.Google Scholar
45. McKinnell, JA, Bartsch, SM, Lee, BY, Huang, SS, Miller, LG. Cost-benefit analysis from the hospital perspective of universal active screening followed by contact precautions for methicillin-resistant Staphylococcus aureus carriers. Infect Control Hosp Epidemiol 2015;36:213; doi:10.1017/ice.2014.1.Google Scholar
46. Jarvis, WR, Jarvis, AA, Chinn, RY. National prevalence of methicillin-resistant Staphylococcus aureus in inpatients at United States health care facilities, 2010. Am J Infect Control 2012;40:194200. doi:10.1016/j.ajic.2012.02.001.Google Scholar
47. Gidengil, CA, Gay, C, Huang, SS, Platt, R, Yokoe, D, Lee, GM. Cost-effectiveness of strategies to prevent methicillin-resistant Staphylococcus aureus transmission and infection in an intensive care unit. Infect Control Hosp Epidemiol 2015;36:1727; doi:10.1017/ice.2014.12.Google Scholar
48. Huang, SS, Septimus, E, Kleinman, K, et al. Targeted versus universal decolonization to prevent ICU infection. N Engl J Med 2013;368:22552265; doi:10.1056/NEJMoa1207290.CrossRefGoogle ScholarPubMed
49. Deeny, SR, Cooper, BS, Cookson, B, Hopkins, S, Robotham, JV. Targeted versus universal screening and decolonization to reduce healthcare-associated meticillin-resistant Staphylococcus aureus infection. J Hosp Infect 2013;85:3344; doi:10.1016/j.jhin.2013.03.011.CrossRefGoogle ScholarPubMed
50. Robotham, JV, Graves, N, Cookson, BD, et al. Screening, isolation, and decolonisation strategies in the control of meticillin resistant Staphylococcus aureus in intensive care units: cost effectiveness evaluation. Br Med J 2011;343:d5694d5694; doi:10.1136/bmj.d5694.Google Scholar
Figure 0

TABLE 1 Demographic and Clinical Characteristics of Patients Admitted to Ottawa Hospital January 1, 2006–August 31, 2009

Figure 1

FIGURE 1 Rates of nosocomial methicillin-resistant Staphylococcus aureus before and after intervention, per 100,000 patient-days (pt days), January 1, 2006–August 31, 2009.

Figure 2

TABLE 2 Summary of Nosocomial MRSA Cases at the Ottawa Hospital Before and After Implementation of Universal Screening

Figure 3

TABLE 3 Segmented Regression Analyses Modeling Baseline Rates, Intervention-Specific and Secular Changes Over Time for MRSA Rates, and 3 Secondary Outcomes of CDI Rates, Mupirocin Prescription Rates, and Regional MRSA Rates