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We assessed the impact of personal protective equipment (PPE) doffing errors on healthcare worker (HCW) contamination with multidrug-resistant organisms (MDROs).
Design:
Prospective, observational study.
Setting:
The study was conducted at 4 adult ICUs at 1 tertiary-care teaching hospital.
Participants:
HCWs who cared for patients on contact precautions for methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant Enterococci, or multidrug-resistant gram-negative bacilli were enrolled. Samples were collected from standardized areas of patient body, garb sites, and high-touch environmental surfaces in patient rooms. HCW hands, gloves, PPE, and equipment were sampled before and after patient interaction. Research personnel observed PPE doffing and coded errors based on CDC guidelines.
Results:
We enrolled 125 HCWs; most were nurses (66.4%) or physicians (19.2%). During the study, 95 patients were on contact precautions for MRSA. Among 5,093 cultured sites (HCW, patient, environment), 652 (14.7%) yielded the target MDRO. Moreover, 45 HCWs (36%) were contaminated with the target MDRO after patient interactions, including 4 (3.2%) on hands and 38 (30.4%) on PPE. Overall, 49 HCWs (39.2%) made multiple doffing errors and were more likely to have contaminated clothes following a patient interaction (risk ratio [RR], 4.69; P = .04). All 4 HCWs with hand contamination made doffing errors. The risk of hand contamination was higher when gloves were removed before gowns during PPE doffing (RR, 11.76; P = .025).
Conclusion:
When caring for patients on CP for MDROs, HCWs appear to have differential risk for hand contamination based on their method of doffing PPE. An intervention as simple as reinforcing the preferred order of doffing may reduce HCW contamination with MDROs.
To identify Choosing Wisely items for the American Board of Internal Medicine Foundation.
METHODS
The Society for Healthcare Epidemiology of America (SHEA) elicited potential items from a hospital epidemiology listserv, SHEA committee members, and a SHEA–Infectious Diseases Society of America compendium with SHEA Research Network members ranking items by Delphi method voting. The SHEA Guidelines Committee reviewed the top 10 items for appropriateness for Choosing Wisely. Five final recommendations were approved via individual member vote by committees and the SHEA Board.
RESULTS
Ninety-six items were proposed by 87 listserv members and 99 SHEA committee members. Top 40 items were ranked by 24 committee members and 64 of 226 SHEA Research Network members. The 5 final recommendations follow: 1. Don’t continue antibiotics beyond 72 hours in hospitalized patients unless patient has clear evidence of infection. 2. Avoid invasive devices (including central venous catheters, endotracheal tubes, and urinary catheters)and, if required, use no longer than necessary. They pose a major risk for infections. 3. Don’t perform urinalysis, urine culture, blood culture, or Clostridium difficile testing unless patients have signs or symptoms of infection. Tests can be falsely positive leading to overdiagnosis and overtreatment. 4. Do not use antibiotics in patients with recent C. difficile without convincing evidence of need. Antibiotics pose a high risk of C. difficile recurrence. 5. Don’t continue surgical prophylactic antibiotics after the patient has left the operating room. Five runner-up recommendations are included.
CONCLUSIONS
These 5 SHEA Choosing Wisely and 5 runner-up items limit medical overuse.
Methicillin-resistant Staphylococcus aureus (MRSA) infections due to USA300 have become widespread in community and healthcare settings. It is unclear whether risk factors for bloodstream infections (BSIs) differ by strain type.
OBJECTIVE
To examine the epidemiology of S. aureus BSIs, including USA300 and non-USA300 MRSA strains.
DESIGN
Retrospective observational study with molecular analysis.
SETTING
Large urban public hospital.
PATIENTS
Individuals with S. aureus BSIs from January 1, 2007 through December 31, 2013.
METHODS
We used electronic surveillance data to identify cases of S. aureus BSI. Available MRSA isolates were analyzed by pulsed-field gel electrophoresis. Poisson regression was used to evaluate changes in BSI incidence over time. Risk factor data were collected by medical chart review and logistic regression was used for multivariate analysis of risk factors.
RESULTS
A total of 1,015 cases of S. aureus BSIs were identified during the study period; 36% were due to MRSA. The incidence of hospital-onset (HO) MRSA BSIs decreased while that of community-onset (CO) MRSA BSIs remained stable. The rate of CO– and HO– methicillin-susceptible S. aureus infections both decreased over time. More than half of HO-MRSA BSIs were due to the USA300 strain type and for 4 years, the proportion of HO-MRSA BSIs due to USA300 exceeded 60%. On multivariate analysis, current or former drug use was the only epidemiologic risk factor for CO- or HO-MRSA BSIs due to USA300 strains.
CONCLUSIONS
USA300 MRSA is endemic in communities and hospitals and certain populations (eg, those who use illicit drugs) may benefit from enhanced prevention efforts in the community.
Infect. Control Hosp. Epidemiol. 2015;36(12):1417–1422
Previous work has shown that daily skin cleansing with Chlorhexidine gluconate (CHG) is effective in preventing infection in the medical intensive care unit (MICU). A colorimetric, semiquantitative indicator was used to measure CHG concentration on skin (neck, antecubital fossae, and inguinal areas) of patients bathed daily with CHG during their MICU stay and after discharge from the MICU, when CHG bathing stopped.
Patients and Setting.
MICU patients at Rush University Medical Center.
Methods.
CHG concentration on skin was measured and skin sites were cultured quantitatively. The relationship between CHG concentration and microbial density on skin was explored in a mixed-effects model using gram-positive colony-forming unit (CFU) counts.
Results.
For 20 MICU patients studied (240 measurements), the lowest CHG concentrations (0–18.75 μg/mL) and the highest gram-positive CFU counts were on the neck (median, 1.07 log10 CFUs; P = .014). CHG concentration increased postbath and decreased over 24 hours (P < .001). In parallel, median log10 CFUs decreased pre- to postbath (0.78 to 0) and then increased over 24 hours to the baseline of 0.78 (P = .001). A CHG concentration above 18.75 μg/mL was associated with decreased gram-positive CFUs (P = .004). In all but 2 instances, CHG was detected on patient skin during the entire interbath (approximately 24-hour) period (18 [90%] of 20 patients). In 11 patients studied after MICU discharge (80 measurements), CHG skin concentrations fell below effective levels after 1–3 days.
Conclusion.
In MICU patients bathed daily with CHG, CHG concentration was inversely associated with microbial density on skin; residual antimicrobial activity on skin persisted up to 24 hours. Determination of CHG concentration on the skin of patients may be useful in monitoring the adequacy of skin cleansing by healthcare workers.
Investigators and medical decision makers frequently rely on administrative databases to assess methicillin-resistant Staphylococcus aureus (MRSA) infection rates and outcomes. The validity of this approach remains unclear. We sought to assess the validity of the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) code for infection with drug-resistant microorganisms (V09) for identifying culture-proven MRSA infection.
Design.
Retrospective cohort study.
Methods.
All adults admitted to 3 geographically distinct hospitals between January 1, 2001, and December 31, 2007, were assessed for presence of incident MRSA infection, defined as an MRSA-positive clinical culture obtained during the index hospitalization, and presence of the V09 ICD-9-CM code. The k statistic was calculated to measure the agreement between presence of MRSA infection and assignment of the V09 code. Sensitivities, specificities, positive predictive values, and negative predictive values were calculated.
Results.
There were 466,819 patients discharged during the study period. Of the 4,506 discharged patients (1.0%) who had the V09 code assigned, 31% had an incident MRSA infection, 20% had prior history of MRSA colonization or infection but did not have an incident MRSA infection, and 49% had no record of MRSA infection during the index hospitalization or the previous hospitalization. The V09 code identified MRSA infection with a sensitivity of 24% (range, 21%–34%) and positive predictive value of 31% (range, 22%–53%). The agreement between assignment of the V09 code and presence of MRSA infection had a k coefficient of 0.26 (95% confidence interval, 0.25–0.27).
Conclusions.
In its current state, the ICD-9-CM code V09 is not an accurate predictor of MRSA infection and should not be used to measure rates of MRSA infection.
To compare incidence rates of Clostridium difficile infection (CDI) during a 6-year period among 5 geographically diverse academic medical centers across the United States by use of recommended standardized surveillance definitions of CDI that incorporate recent information on healthcare facility (HCF) exposure.
Methods.
Data on C. difficile toxin assay results and dates of hospital admission and discharge were collected from electronic databases. Chart review was performed for patients with a positive C. difficile toxin assay result who were identified within 48 hours after hospital admission to determine whether they had any HCF exposure during the 90 days prior to their hospital admission. CDI cases, defined as any inpatient with a stool toxin assay positive for C. difficile, were categorized into 5 surveillance definitions based on recent HCF exposure. Annual CDI rates were calculated and evaluated by use of the χ2 test for trend and the χ2 summary test.
Results.
During the study period, there were significant increases in the overall incidence rates of HCF-onset, HCF-associated CDI (from 7.0 to 8.5 cases per 10,000 patient-days; P < .001); community-onset, HCF-associated CDI attributed to a study hospital (from 1.1 to 1.3 cases per 10,000 patient-days; P = .003); and community-onset, HCF-associated CDI not attributed to a study hospital (from 0.8 to 1.5 cases per 1,000 admissions overall; P < .001). For each surveillance definition of CDI, there were significant differences in the total incidence rate between HCFs.
Conclusions.
The increasing incidence rates of CDI over time and across healthcare institutions and the correlation of CDI incidence in different surveillance categories suggest that CDI may be a regional problem and not isolated to a single HCF within a community.
To compare incidence of hospital-onset Clostridium difficile infection (CDI) measured by the use of International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) discharge diagnosis codes with rates measured by the use of electronically available C. difficile toxin assay results.
Methods.
Cases of hospital-onset CDI were identified at 5 US hospitals during the period from July 2000 through June 2006 with the use of 2 surveillance definitions: positive toxin assay results (gold standard) and secondary ICD-9-CM discharge diagnosis codes for CDI. The x2 test was used to compare incidence, linear regression models were used to analyze trends, and the test of equality was used to compare slopes.
Results.
Of 8,670 cases of hospital-onset CDI, 38% were identified by the use of both toxin assay results and the ICD-9-CM code, 16% by the use of toxin assay results alone, and 45% by the use of the ICD-9-CM code alone. Nearly half (47%) of cases of CDI identified by the use of a secondary diagnosis code alone were community-onset CDI according to the results of the toxin assay. The rate of hospital-onset CDI found by use of ICD-9-CM codes was significantly higher than the rate found by use of toxin assay results overall (P<.001), as well as individually at 3 of the 5 hospitals (P<.001 for all). The agreement between toxin assay results and the presence of a secondary ICD-9-CM diagnosis code for CDI was moderate, with an overall k value of 0.509 and hospital-specific k values of 0.489–0.570. Overall, the annual increase in CDI incidence was significantly greater for rates determined by the use of ICD-9-CM codes than for rates determined by the use of toxin assay results (P = .006).
Conclusions.
Although the ICD-9-CM code for CDI seems to be adequate for measuring the overall CDI burden, use of the ICD-9-CM discharge diagnosis code for CDI, without present-on-admission code assignment, is not an acceptable surrogate for surveillance for hospital-onset CDI.
Controlled studies that took place in medical intensive care units (MICUs) have demonstrated that bathing patients with Chlorhexidine gluconate (CHG) can reduce skin colonization with potential pathogens and can lessen the risk of central venous catheter (CVC)-associated bloodstream infection (BSI).
Objective.
TO examine, without oversight of practice by research study staff, the effectiveness or real-world effect of patient cleansing with CHG on rates of CVC-associated BSI.
Design.
In the fall of 2005, the MICU at Rush University Medical Center discontinued bathing patients daily with soap and water and substituted skin cleansing with no-rinse, 2% CHG-impregnated cloths. This change was a clinical management decision without research input.
Setting.
A 21-bed MICU at Rush University Medical Center.
Patients.
Patients hospitalized in the MICU during the period from September 2004 through October 2006.
Methods.
In a pre-post study design, we gathered data from administrative and laboratory databases, infection control practitioner logs, and patient medical charts to compare rates of CVC-associated BSI and blood culture contamination between the baseline soap-and-water bathing period (September 2004-October 2005) and the CHG bathing period (November 2005-October 2006). Rates of secondary BSI, Clostridium difficile infection (CDI), ventilator-associated pneumonia (VAP), and urinary tract infection (UTI) served as control variables that were not expected to be affected by CHG bathing.
Results.
Bathing with CHG was associated with a statistically significant decrease in the rate of CVC-associated BSI (from 5.31 to 0.69 cases per 1,000 CVC-days; P = .006) and in the rate of blood culture contamination (from 6.99 to 4.1 cases per 1,000 patient-days; P = .04). Rates of secondary BSI, CDI, VAP, and UTI did not change significantly.
Conclusions.
In our analysis of real-world practice, daily bathing of MICU patients with CHG was effective at reducing rates of CVC-associated BSI and blood culture contamination. Controlled studies are needed to determine whether these beneficial effects extend outside the MICU.
To evaluate the impact of cases of community-onset, healthcare facility (HCF)-associated Clostridium difficile infection (CDI) on the incidence and outbreak detection of CDI.
Design.
A retrospective multicenter cohort study.
Setting.
Five university-affiliated, acute care HCFs in the United States.
Methods.
We collected data (including results of C. difficile toxin assays of stool samples) on all of the adult patients admitted to the 5 hospitals during the period from July I, 2000, through June 30, 2006. CDI cases were classified as HCF-onset if they were diagnosed more than 48 hours after admission or as community-onset, HCF-associated if they were diagnosed within 48 hours after admission and if the patient had recently been discharged from the HCF. Four surveillance definitions were compared: cases of HCF-onset CDI only (hereafter referred to as HCF-onset CDI) and cases of HCF-onset and community-onset, HCF-associated CDI diagnosed within 30, 60, and 90 days after the last discharge from the study hospital (hereafter referred to as 30-day, 60-day, and 90-day CDI, respectively). Monthly CDI rates were compared. Control charts were used to identify potential CDI outbreaks.
Results.
The rate of 30-day CDI was significantly higher than the rate of HCF-onset CDI at 2 HCFs (P < .01 ). The rates of 30-day CDI were not statistically significantly different from the rates of 60-day or 90-day CDI at any HCF. The correlations between each HCF's monthly rates of HCF-onset CDI and 30-day CDI were almost perfect (ρ range, 0.94-0.99; P < .001). Overall, 12 time points had a CDI rate that was more than 3 standard deviations above the mean, including 11 time points identified using the definition for HCF-onset CDI and 9 time points identified using the definition for 30-day CDI, with discordant results at 4 time points (k = 0.794; P < .001).
Conclusions.
Tracking cases of both community-onset and HCF-onset, HCF-associated CDI captures significantly more CDI cases, but surveillance of HCF-onset, HCF-associated CDI alone is sufficient to detect an outbreak.