Susan Huang and colleagues describe an automated statistical software, WHONET-SaTScan, its application in a hospital, and the potential it has to identify hospital infection clusters that had escaped routine detection.
Detection of outbreaks of hospital-acquired infections is often based on simple rules, such as the occurrence of three new cases of a single pathogen in two weeks on the same ward. These rules typically focus on only a few pathogens, and they do not account for the pathogens' underlying prevalence, the normal random variation in rates, and clusters that may occur beyond a single ward, such as those associated with specialty services. Ideally, outbreak detection programs should evaluate many pathogens, using a wide array of data sources.
Methods and Findings
We applied a space-time permutation scan statistic to microbiology data from patients admitted to a 750-bed academic medical center in 2002–2006, using WHONET-SaTScan laboratory information software from the World Health Organization (WHO) Collaborating Centre for Surveillance of Antimicrobial Resistance. We evaluated patients' first isolates for each potential pathogenic species. In order to evaluate hospital-associated infections, only pathogens first isolated >2 d after admission were included. Clusters were sought daily across the entire hospital, as well as in hospital wards, specialty services, and using similar antimicrobial susceptibility profiles. We assessed clusters that had a likelihood of occurring by chance less than once per year. For methicillin-resistant Staphylococcus aureus (MRSA) or vancomycin-resistant enterococci (VRE), WHONET-SaTScan–generated clusters were compared to those previously identified by the Infection Control program, which were based on a rule-based criterion of three occurrences in two weeks in the same ward. Two hospital epidemiologists independently classified each cluster's importance. From 2002 to 2006, WHONET-SaTScan found 59 clusters involving 2–27 patients (median 4). Clusters were identified by antimicrobial resistance profile (41%), wards (29%), service (13%), and hospital-wide assessments (17%). WHONET-SaTScan rapidly detected the two previously known gram-negative pathogen clusters. Compared to rule-based thresholds, WHONET-SaTScan considered only one of 73 previously designated MRSA clusters and 0 of 87 VRE clusters as episodes statistically unlikely to have occurred by chance. WHONET-SaTScan identified six MRSA and four VRE clusters that were previously unknown. Epidemiologists considered more than 95% of the 59 detected clusters to merit consideration, with 27% warranting active investigation or intervention.
Automated statistical software identified hospital clusters that had escaped routine detection. It also classified many previously identified clusters as events likely to occur because of normal random fluctuations. This automated method has the potential to provide valuable real-time guidance both by identifying otherwise unrecognized outbreaks and by preventing the unnecessary implementation of resource-intensive infection control measures that interfere with regular patient care.
Please see later in the article for the Editors' Summary
Admission to a hospital is often a life-saving necessity—individuals injured in a road accident, for example, may need immediate medical and surgical attention if they are to survive. Unfortunately, many patients acquire infections, some of which are life-threatening, during their stay in a hospital. The World Health Organization has estimated that, globally, 8.7% of hospital patients develop hospital-acquired infections (infections that are identified more than two days after admission to hospital). In the US alone, 2 million people develop a hospital-acquired infection every year, often an infection of a surgical wound, or a urinary tract or lung infection. Infections are common among hospital patients because increasing age or underlying illnesses can reduce immunity to infection and because many medical and surgical procedures bypass the body's natural protective barriers. In addition, poor infection control practices can facilitate the transmission of bacteria—including meticillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant enterococci (VRE)—and other infectious agents (pathogens) between patients.
Why Was This Study Done?
Sometimes, the number of cases of hospital-acquired infections increases unexpectedly or a new infection emerges. Such clusters account for relatively few health care–associated infections, but, because they may arise from the transmission of a pathogen within a hospital, they need to be rapidly identified and measures implemented (for example, isolation of affected patients) to stop transmission if an outbreak is confirmed. Currently, the detection of clusters of hospital-acquired infections is based on simple rules, such as the occurrence of three new cases of a single pathogen in two weeks on the same ward. This rule-based approach relies on the human eye to detect infection clusters within microbiology data (information collected on the pathogens isolated from patients), it focuses on a few pathogens, and it does not consider the random variation in infection rates or the possibility that clusters might be associated with shared facilities rather than with individual wards. In this study, the researchers test whether an automated statistical system can detect outbreaks of hospital-acquired infections quickly and accurately.
What Did the Researchers Do and Find?
The researchers combined two software packages used to track diseases in populations to create the WHONET-SaTScan cluster detection tool. They then compared the clusters of hospital-acquired infection identified by the new tool in microbiology data from a 750-bed US academic medical center with those generated by the hospital's infection control program, which was largely based on the simple rule described above. WHONET-SaTScan found 59 clusters of infection that occurred between 2002 and 2006, about three-quarters of which were identified by characteristics other than a ward-based location. Nearly half the cluster alerts were generated on the basis of shared antibiotic susceptibility patterns. Although WHONET-SaTScan identified all the clusters previously identified by the hospital's infection control program, it classified most of these clusters as likely to be the result of normal random variations in infection rates rather than the result of “true” outbreaks. By contrast, the hospital's infection control department only identified three of the 59 statistically significant clusters identified by WHONET-SaTScan. Furthermore, the new tool identified six previously unknown MRSA outbreaks and four previously unknown VRE outbreaks. Finally, two hospital epidemiologists (scientists who study diseases in populations) classified 95% of the clusters detected by WHONET-SaTScan as worthy of consideration by the hospital infection control team and a quarter of the clusters as warranting active investigation or intervention.
What Do These Findings Mean?
These findings suggest that automated statistical software should be able to detect clusters of hospital-acquired infections that would escape detection using routine rule-based systems. Importantly, they also suggest that an automated system would be able to discount a large number of supposed outbreaks identified by rule-based systems. These findings need to be confirmed in other settings and in prospective studies in which the outcomes of clusters detected with WHONET-SaTScan are carefully analyzed. For now, however, these findings suggest that automated statistical tools could provide hospital infection control experts with valuable real-time guidance by identifying outbreaks that would be missed by routine detection methods and by preventing the implementation of intensive and costly infection control measures in situations where they are unnecessary.
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000238.
The World Health Organization's Prevention of Hospital-Acquired Infections, A Practical Guide contains detailed information on all aspects of hospital-acquired infections
MedlinePlus provides links to information on infection control in hospitals (in English and Spanish)
The US Centers for Disease Control and Prevention also provides information on infectious diseases in health care settings (in English and Spanish)
The WHONET/Baclink software and the SatScan software, the two components of WHONET-SaTScan are both available on the internet (the WHONET-SaTScan cluster detection tool is freely available as part of the version of WHONET/BacLink released June 2009)