Literature Update - April, 2006
Compiled by Dr Deb Friedman, VICNISS ID Physician
Stick to Old-fashioned Surveillance for Now!
Everybody (at least everyone in infection control circles) agrees in the benefit of surveillance for hospital-acquired
infections (HAI). However, the optimal methods for collecting and analysing HAI data remain unclear. In recent years many have
sought to cut corners in an attempt to reduce the workload associated with surveillance.
A recent paper by Sherman et al (Infect Control Hosp Epidemiol 2006;27:332-337), reports on the failure of hospital
administrative data to identify cases of infection. The researchers searched hospital billing data to detect cases in
patients with an infection-specific ICD-9 discharge code. When compared with active targeted surveillance as the gold
standard, they found similar sensitivities for identification of HAI cases by review of administrative data (61%) and by
targeted active surveillance (76%). However, the positive predictive value of identifying HAI cases by review of
administrative data was poor (20%), whereas that of targeted active surveillance was 100%. Importantly, however,
review of administrative data misclassified many cases as HAIs.
They concluded that targeted active surveillance by trained ICPs using definitions developed by the CDC was both
sensitive and accurate for identifying most cases of HAI. Unfortunately, the substantial inaccuracies in identification of
cases of HAI by review of administrative data make hospital billing data a poor source of infection control information.
Sampling for Collection of Central Line–Day Denominators in Surveillance of ICU-Associated
Bloodstream Infections
ICCs who find collecting central line-day data laborious will be happy with the results of a study performed by the CDC
(Infect Control Hosp Epidemiol 2006;27:338-342). Instead of counting central-line days daily, the authors aimed to determine
the feasibility of estimating the number of central line-days at a hospital from a sample of months or individual days in a
year. A total of 247 hospitals were used for sampling whole months and 12 hospitals were used for sampling individual days.
For a 1-month sample of central line-days, the median percentile error comparing CLABSI rates per line-day and rates per
estimated line-day was 3.3 (75th percentile, 7.9; 90th percentile, 15.4). For a 3-month sample, the median percentile difference
was 1.4 (75th percentile, 4.3; 90th percentile, 8.3). The sensitivity, specificity, and predictive values increased for rates per
estimated line-day with an increase in the number of months sampled. With 1 weekday sampled per week, the median percentile error
ranged from 0.65 to 1.40 and the 90th percentile from 2.8 to 5.0.
Their findings indicate that an estimate of the number of central line–days based on a sample yields an annual infection
rate that is not meaningfully different from current practice. In fact, for 90% of units, collecting data on line-days once a week
provided an estimate within 5 percentile points of the line-day rate.
The authors acknowledge that a sample of 1 day a week all year might be easy to implement and other combinations of time might
also be feasible (e.g., first week of each month).
Hospitals with a Greater Surgical Volume have Lower SSI Rates
In light of some background data which suggests that there is an inverse relationship between the number of operations
performed by a particular surgeon (ie, the surgeon volume) or at a particular hospital (ie, the hospital volume) and mortality,
a group from Taiwan (Infect Control Hosp Epidemiol 2006;27:308-311) looked at hospital volume and risk of SSI after bypass
surgery (CABG).
The incidence of SSI for hospital with the lowest volume was significantly higher than that for the highest with the highest
volume of CABGs (8.94% vs 5.34%). This finding was also true for surgeon volume.
Although it is unclear if one can extrapolate these results to other types of surgery in other countries, there is clearly
enough evidence that the volume of procedures performed by a hospital surgical unit, and by a particular surgeon is an
important variable in assessing risk of SSI.
Finger Rings and Handwashing in the Operating Theatre
It is known that jewellery is associated with higher surface bacterial load on hands. A recent study measured the effect of
retaining or removing finger rings on surface bacterial counts before and after scrubbing and at the end of operative procedures
(J Hosp Infect 2006; 62:450-452).
Twenty-eight staff were swabbed extensively on two occasions (separated by 1-16 days), the first with the rings being worn,
and the second with the ring removed after the first set of swabs was taken.
The results before scrubbing showed significantly higher colony counts on the skin under the ring than on the control ring
finger, the ring itself or the skin adjacent to the ring. After scrubbing, colony counts at all sites were significantly reduced.
There were significantly more bacteria on the skin under the ring than the control finger and the skin over which the ring had
been worn before being removed. There were significantly more bacteria on the skin over which the ring had been worn before
removal than in the control finger. In terms of ring type, there was only 1 positive culture from the 28 samples taken from
and adjacent to the 2 silver rings (3.6%), compared with 31% of the gold and platinum rings (P=0.01).
This study adds weight to existing recommendations about wearing jewellery in the operating theatre. Rings reduce the
effectiveness of scrubbing and increase glove microtears around the base of the finger. Interestingly, this study also
highlighted the antiseptic properties of silver.