To evaluate the effects of an active surveillance program for Staphylococcus aureus linked to a decolonization protocol on the incidence of healthcare-associated infection and new nasal colonization due to S. aureus.

Retrospective quasi-experimental study.

An 18-bed medical intensive care unit at a tertiary care center in Cleveland, Ohio.

From January 1, 2006, through December 31, 2007, all patients in the medical intensive care unit were screened for S. aureus nasal carriage at admission and weekly thereafter. During the preintervention period, January 1 through September 30,2006, only surveillance occurred. During the intervention period, January 1 through December 31,2007, S. aureus carriers received mupirocin intranasally. Beginning in February 2007, carriers also received Chlorhexidine gluconate baths.

During the preintervention period, 604 (73.7%) of 819 patients were screened for S. aureus nasal carriage, yielding 248 prevalent carriers (30.3%). During the intervention period, 752 (78.3%) of 960 patients were screened, yielding 276 carriers (28.8%). The incidence of S. aureus carriage decreased from 25 cases in 3,982 patient-days (6.28 cases per 1,000 patient-days) before intervention to 18 cases in 5,415 patient-days (3.32 cases per 1,000 patient-days) (P = .04; relative risk [RR], 0.53 [95% confidence interval {CI}, 0.28-0.97]) and from 9.57 to 4.77 cases per 1,000 at-risk patient-days (P = .02; RR, 0.50 [95% CI, 0.27-0.91]). The incidence of S. aureus hospital-acquired bloodstream infection during the 2 periods was 2.01 and 1.11 cases per 1,000 patient-days, respectively (P = .28). The incidence of S. aureus ventilator-associated pneumonia decreased from 1.51 to 0.18 cases per 1,000 patient-days (P = .03; RR, 0.12 [95% CI, 0.01-0.83]). The total incidence of S. aureus hospital-acquired infection decreased from 3.52 to 1.29 cases per 1,000 patient-days (P = .03; RR, 0.37 [95% CI, 0.14-0.90]).

Active surveillance for S. aureus nasal carriage combined with decolonization was associated with a decreased incidence of S. aureus colonization and hospital-acquired infection.

To evaluate the long-term impact of successive interventions on rates of methicillin-resistant Staphylococcus aureus (MRSA) colonization or infection and MRSA bacteremia in an endemic hospital-wide situation.

Quasi-experimental, interrupted time-series analysis. The impact of the interventions was analyzed by use of segmented regression. Representative MRSA isolates were typed by use of pulsed-field gel electrophoresis.

A 950-bed teaching hospital in Seville, Spain.

All patients admitted to the hospital during the period from 1995 through 2008.

Three successive interventions were studied: (1) contact precautions, with no active surveillance for MRSA; (2) targeted active surveillance for MRSA in patients and healthcare workers in specific wards, prioritized according to clinical epidemiology data; and (3) targeted active surveillance for MRSA in patients admitted from other medical centers.

Neither the preintervention rate of MRSA colonization or infection (0.56 cases per 1,000 patient-days [95% confidence interval {CI}, 0.49-0.62 cases per 1,000 patient-days]) nor the slope for the rate of MRSA colonization or infection changed significantly after the first intervention. The rate decreased significantly to 0.28 cases per 1,000 patient-days (95% CI, 0.17-0.40 cases per 1,000 patient-days) after the second intervention and to 0.07 cases per 1,000 patient-days (95% CI, 0.06-0.08 cases per 1,000 patient-days) after the third intervention, and the rate remained at a similar level for 8 years. The MRSA bacteremia rate decreased by 80%, whereas the rate of bacteremia due to methicillin-susceptible S. aureus did not change. Eighty-three percent of the MRSA isolates identified were clonally related. All MRSA isolates obtained from healthcare workers were clonally related to those recovered from patients who were in their care.

Our data indicate that long-term control of endemic MRSA is feasible in tertiary care centers. The use of targeted active surveillance for MRSA in patients and healthcare workers in specific wards (identified by means of analysis of clinical epidemiology data) and the use of decolonization were key to the success of the program.

To compare 3 measures of hand hygiene adherence—direct observation, product usage, and electronic counting devices—in an intensive care unit.

A 12-week observational study.

A 40-bed medical-surgical intensive care unit at a private tertiary care hospital.

Over a 12-week period, we assessed hand hygiene adherence by 3 different methods: direct observation of practice, collection of data from electronic counters for dispensers of alcohol-based hand rub, and measurement of the amount of product used (alcohol-based hand rub and chlorhexidine).

There were 2,249 opportunities for hand hygiene observed, and the overall rate of hand hygiene adherence was 62.3% (representing 1,402 cleansing episodes). A total of 76,389 dispensing episodes were recorded by the electronic devices. The mean number of dispensing episodes per patient-day was 53.8. There was 64.1 mL of alcohol-based hand rub used per patient-day (representing 65.5% of total product used) and 33.8 mL of Chlorhexidine used per patient-day (representing 34.5%). There was no significant correlation between observed hand hygiene adherence and total product used per patient-day (r = 0.18; P = .59).

Direct observation cannot be considered the gold standard for assessing hand hygiene, because there was no relationship between the observed adherence and the number of dispensing episodes or the volume of product used. Other means to monitor hand hygiene adherence, such as electronic devices and measurement of product usage, should be considered.

To gather baseline data on hand hygiene (HH) practices in an African hospital with a newly established infection prevention and control team.

Cross-sectional, observational study.

Komfo Anokye Teaching Hospital, a large teaching hospital in Ghana with approximately 1,000 beds.

All hospital staff with patient contact were eligible for assessment of HH practices.

HH observations were conducted using a standardized data collection tool and method based on the World Health Organization's “5 Moments of Hand Hygiene.” Small-group interviews were conducted to gather additional information on perceptions of HH and barriers to its use. HH resource needs were also assessed using a standardized tool.

HH was attempted in 12% of the opportunities and was performed appropriately in 4% of the opportunities. Most main wards (89%) had at least 1 functional HH station. The most commonly identified barriers to HH were limited resources and lack of knowledge on appropriate times to perform HH.

We developed and applied tools to evaluate HH resources and practices in a large African hospital. These assessments were undertaken to guide future efforts to improve HH at this hospital but can also serve as a model of the way to perform a systematic assessment at acute care hospitals in developing countries.

Show how detailed incubation period estimates can be used to identify and investigate potential healthcare-associated infections and dangerous diseases.

We used the incubation period of 9 respiratory viruses to derive decision rules for distinguishing between community- and hospital-acquired infection. We developed a method, implemented in a simple spreadsheet, that can be used to investigate the exposure history of an individual patient and more specifically to identify the probable time and location of infection. Illustrative examples are used to explain and evaluate this technique.

If the risks of hospital and community infection are equal, 95% of patients who develop symptoms of adenovirus infection within 5 days of hospital admission will have been infected in the community, as will 95% of patients who develop symptoms within 3 days for human-coronavirus infection, 2.5 days for severe acute respiratory syndrome, 1 day for influenza A, 0.5 day for influenza B, 12 days for measles, 2 days for parainfluenza, 4 days for respiratory syncytial virus infection, and 1.5 days for rhinovirus infection. Sources of infection suggested by analysis of the symptom onset times of individual patients are consistent with those from detailed investigations.

This work shows how a detailed understanding of the incubation period can be an effective tool for identifying the source of infection, ultimately ensuring patient safety.

To describe factors associated with a rectal swab or stool sample positive for norovirus, rotavirus, or adenovirus.

Retrospective study.

Charleston Area Medical Center, a regional academic medical center in Charleston, West Virginia.

Rectal swab or stool samples were obtained from patients suspected of having viral gastroenteritis. These samples were sent to the Charleston Area Medical Center virology laboratory for testing in 2007. Viral antigen in rectal swab and stool samples is detected by use of commercially available immunoassay kits for each virus. Data were extracted from the virology laboratory database for the following 1-year time period: January 1, 2007, through December 31, 2007. When necessary, additional information was obtained from electronic administrative data on patients.

There were 2,867 rectal swab and stool samples available for viral testing. Of these samples, 1,261 (44%) were positive for a virus. Of these positive samples, 972 (77%) were positive for norovirus, 182 (14%) were positive for rotavirus, and 110 (9%) were positive for adenovirus. The patients in the youngest age group had the highest number of test results positive for all 3 viruses. When the test results for the youngest age group (0-9 years) were compared with those for all the other age groups combined (10-99 years), the proportion of positive cases was highest for the youngest age group (P<.001). There were significant seasonal trends for all 3 viruses. Multivariate analysis of norovirus showed that season, source, sex, and age were significant predictors of a positive test result. Multivariate analysis of rotavirus showed that season and source were significant predictors of a positive test result. Multivariate analysis of adenovirus showed that season and age were significant predictors of a positive test result.

We conclude (1) that these 3 viruses are common causes of gastroenteritis in Charleston, West Virginia; (2) that infants and young children are more likely to test positive for these viruses than are older individuals; (3) that norovirus was the most common cause of gastroenteritis; and (4) that there are seasonal trends for all 3 viruses.

Robot-assisted surgery is minimally invasive and associated with less blood loss and shorter recovery time than open surgery. We aimed to determine the duration of robot-assisted surgical procedures and the incidence of postoperative surgical site infection (SSI) and to compare our data with the SSI incidence for open procedures according to national data.

Retrospective cohort study.

A 689-bed academic medical center.

All patients who underwent a surgical procedure with use of a robotic surgical system during the period from 2000-2007.

SSIs were defined and procedure types were classified according to National Healthcare Safety Network criteria. National data for comparison were from 1992-2004. Because of small sample size, procedures were grouped according to surgical site or wound classification.

Sixteen SSIs developed after 273 robot-assisted procedures (5.9%). The mean surgical duration was 333.6 minutes. Patients who developed SSI had longer mean surgical duration than did patients who did not (558 vs 318 minutes; P<.001). The prostate and genitourinary group had 5.74 SSIs per 100 robot-assisted procedures (95% confidence interval [CI], 2.81–11.37), compared with 0.85 SSIs per 100 open procedures from national data. The gynecologic group had 10.00 SSIs per 100 procedures (95% CI, 2.79–30.10), compared with 1.72 SSIs per 100 open procedures. The colon and herniorrhaphy groups had 33.33 SSIs per 100 procedures (95% CI, 9.68–70.00) and 37.50 SSIs per 100 procedures (95% CI, 13.68–69.43), respectively, compared with 5.88 and 1.62 SSIs per 100 open procedures from national data. Patients with a clean-contaminated wound developed 6.1 SSIs per 100 procedures (95% CI, 3.5–10.3), compared with 2.59 SSIs per 100 open procedures. No significant differences in SSI rates were found for other groups.

Increased incidence of SSI after some types of robot-assisted surgery compared with traditional open surgery may be related to the learning curve associated with use of the robot.

Bacteremia is relatively common in patients with skin and skin-structure infection (SSSI) severe enough to require hospitalization. We used selected demographic and clinical characteristics easily assessable at initial evaluation to develop a model for the early identification of patients with SSSI who are at higher risk for bacteremia.

A large database of adults hospitalized with SSSI at 97 hospitals in the United States during the period from 2003 through 2007 and from whom blood samples were obtained for culture at admission.

We compared selected candidate predictor variables for patients shown to have bacteremia and patients with no demonstrated bacteremia. Using stepwise logistic regression to identify independent risk factors for bacteremia, we derived a model by using 75% of a randomly split cohort, converted the model coefficients into a risk score system, and then we validated it by using the remaining 25% of the cohort.

Bacteremia was documented in 1,021 (11.7%) of the 8,747 eligible patients. Independent predictors of bacteremia (P<.001) were infected device or prosthesis, respiratory rate less than 10 or more than 29 breaths per minute, pulse rate less than 49 or more than 125 beats per minute, temperature less than 35.6°C or at least 38.0°C, white blood cell band percentage of 7% or more, white blood cell count greater than 11 x 109/L, healthcare-associated infection, male sex, and older age. The bacteremia rates ranged from 3.7% (lowest decile) to 30.6% (highest decile) (P< .001). The model C statistic was 0.71; the Hosmer-Lemeshow test P value was .36, indicating excellent model calibration.

Using data available at hospital admission, we developed a risk score that differentiated SSSI patients at low risk for bacteremia from patients at high risk. This score may help clinicians identify patients who require more intensive monitoring or antimicrobial regimens appropriate for treating bacteremia.