Lennox K. Archibald
William R. Jarvis
In the current era of managed care, U.S. healthcare systems are evolving from the traditional acute care hospital inpatient setting to a new integrated, extended care model that includes acute care hospitals, outpatient clinics, ambulatory center, long-term care facilities (LTCFs), and the home. As expected, healthcare-associated infections (HAIs) and antimicrobial resistance may occur at any of these levels of care. Except for the acute care hospitals, however, the relative importance of each of these settings for the acquisition of HAIs remains largely uncharacterized or unknown. The term nosocomial infection has traditionally defined infections acquired in the hospital inpatient setting [1]. Although the term has now been extrapolated to encompass infections acquired in other healthcare settings outside the acute care hospital, there is a paucity of published surveillance data regarding the occurrence of HAIs in LTCFs or the home. This chapter describes (1) the incidence and prevalence rates of common HAI pathogens in the United States, (2) secular trends in the occurrence of some sentinel HAIs, (3) the nature of HAI outbreaks in various healthcare settings, and (4) the implications for patient outcome and healthcare workers (HCWs).
Each year, approximately 35 million people are hospitalized in the United States, accounting for 168 million inpatient-days [2]. HAIs affect approximately 2 million (5.6%) of these patients and contribute to at least 90,000 deaths annually [3]. Almost 85% of these HAIs is associated with bacterial pathogens, and 33% is thought to be preventable just by maintaining infection surveillance and control programs without even taking individual preventive practices into consideration (e.g., catheter or wound care) [4]. The problem of HAIs is compounded by the emergence of antimicrobial resistant pathogens. Antimicrobial resistance contributes substantially to the higher death rates and escalating healthcare costs that currently are attributable to HAIs in the United States. A myriad of published data from single center studies has characterized the HAI pathogens and their susceptibility profiles to commonly available antimicrobials. The financial burden associated with HAIs includes the immediate costs of treating an unexpected infection, the added costs of antimicrobial resistance (e.g., inpatient care requirements, protracted duration of admissions, costly alternative antimicrobials, or toxicity to alternative antimicrobials) and the potential costs, such as lost productivity and untreatable infections.
P.484
Endemic HAIs
Infection Rates
Because of their documented impact on prevention, surveillance and control of HAIs have become priorities within the various healthcare settings. A key objective of managed care is to improve the quality of medical care provided while controlling costs. To achieve this objective, key components of the managed care business model included substantial down sizing of general hospitals and monitoring quality of care and the occurrence, effects, and outcomes of HAIs through the estimation of infection rates using approaches that are strikingly similar to the principles of W. E. Deming for quality improvement in manufacturing [5]. However, to use HAI rates as a basis for measuring quality of care, rates must be valid to begin with and meaningful for comparison, either from one hospital to another or within a hospital over time [6]. Published reports have addressed the importance of adjusting for risk factors (e.g., device use, severity of illness) when comparing mortality rates among hospitals [7,8]. Similar approaches for HAI rates also are necessary [9].
A rate is an expression of the probability of occurrence of an event during a certain time interval. The numerator of an infection rate is always the number of infections of a particular type that have occurred within a particular group of patients over a particular period of time. The group of patients chosen and the choice of the denominator used in calculating the infection rates are what separate comparative rates from those that are not. The concept of a comparable rate is one that controls for variations in the distribution of a major risk factor associated with the event so that the rate could be meaningfully compared internally within the hospital or to an external standard or benchmark. Such risk factors could either be intrinsic or extrinsic: The former includes diseases (congenital or acquired), underlying conditions such as immunosuppression, age and gender, and severity of illness; extrinsic risk factors include various forms of therapy, exposure to antimicrobials, various treatments and procedures (including surgical), exposure to devices such as intravascular catheters, mechanical ventilators, urinary catheters, chest tubes or ventriculostomy catheters, receipt of solid organs or allograft tissues, duration of hospitalization, or exposure to HCWs. HAI surveillance enables healthcare facilities to objectively analyze and follow the trends of their own HAI over time.
The estimation of HAI rates in the United States began with surveillance studies of the prevalence and incidence of infections in individual hospitals [10,11,12]. The first systematic effort to estimate the magnitude of the problem on a wider scale was made by the Centers for Disease Control (now the Centers for Disease Control and Prevention [CDC]) in a collaborative study of eight community hospitals known as the Comprehensive Hospital Infections Project (CHIP) [10]. Performed in the late 1960s and early 1970s, this study involved intensive surveillance efforts to detect both nosocomial and community-acquired infections. At that time, data from these surveillance efforts suggested that approximately 5% of patients in community hospitals acquired ≥1 HAI, an estimate that was subsequently widely held to be the national HAI rate.
In 1970, CDC extended its HAI surveillance activities to a group of 80 volunteer hospitals of diverse sizes and types to help create a national HAI database, improve surveillance methods in acute care hospitals, guide the prevention efforts of infection control professionals (ICPs), and establish national risk-adjusted benchmarks for HAI rates [13,14,15]. This group of hospitals became the foundation of the National Nosocomial Infections Surveillance (NNIS) system, for many years the only source of national data on the epidemiology of HAIs, the pathogens that cause these infections and their respective antimicrobial susceptibility profiles [16]. Participation in the NNIS system is voluntary and is limited to U.S. acute care hospitals ≥100 beds. LTCFs, such as rehabilitation, mental health, or nursing homes, are not included in the NNIS system, which evolved over the years to a format in which participating hospitals collect and report to CDC their HAI data on medical and surgical intensive care unit (ICU) patients using standardized protocols, called surveillance components: adult and pediatric ICU, high-risk nursery, and surgical inpatient [15]. All HAIs in these groups of patients are collected using uniform definitions for HAIs and infection sites [1]. The identities of all NNIS hospitals remain confidential under section 308(d) of the U.S. Public Health Service Act.
In January 1999, the NNIS hospitalwide component was discontinued and a new component that included antimicrobial use data was incorporated. Reasons for eliminating the collection of hospitalwide data included the inordinate amount of time and resources required to collect these data, inaccurate case-finding in this setting, and the fact that hospitalwide rates are not amenable to risk adjustment and therefore not meaningful for national comparison [16]. During 2004, the NNIS system was combined with two other national healthcare surveillance systems into a single internet-based system—the National Healthcare Safety Network (NHSN) [17]. CDC has not yet released results of NHSN data analyses. Since the establishment of NHSN, approximately 243 hospitals regularly report ICU HAI data to CDC.
Various analyses of the NNIS data have yielded rough estimates of overall HAI rates that mirrored the 5% ascertained in the community hospitals that participated in CHIP. During 1974–1983, CDC carried out the Study on the Efficacy of Nosocomial Infection Control (SENIC) project [4]. One of the objectives of the SENIC project was to derive a more precise estimate of the nationwide HAI rate from a statistical sample of U.S. hospitals [18].
P.485
With 338 randomly selected general medical and surgical hospitals with ≥50 beds taking part and examination of more than one-third million patient medical records, two key findings of the SENIC project were first, that hospitals with the lowest HAI rates had both strong surveillance or prevention and control programs and second, different categories of HAIs required specific control programs whose effectiveness were not necessarily transferable when applied arbitrarily for control of any class of HAI. On the basis of direct estimates made in the 338 participating hospitals, it was estimated that ≥2.1 million HAIs occurred among the 37.7 million admissions to the 6,449 acute care U.S. hospitals in a 12-month period from 1975 to 1976 [19]. This gave rise to a nationwide overall rate of 5.7 HAIs per 100 admissions (i.e., ~4.5% of hospitalized patients experienced ~1 HAI).
CDC investigators recognized early on that overall HAI rates, such as those cited, were crude rates (i.e., imprecise, meaningless, and not valid unless they were risk adjusted). A crude overall HAI rate is the total number of HAIs at all sites (e.g., urinary tract infections [UTIs], pneumonias, surgical site infections [SSIs], bloodstream infections [BSIs], and others) divided by a measure of the population at risk (e.g., the number of admissions, discharges, or patient-days). Using a crude HAI rate to characterize a hospital's HAI problem has been seriously questioned or rejected [20,21]. Many investigators and organizations, including the Task Force on Infection Control for the Joint Commission on Accreditation of Healthcare Organizations (JCAHO), have rejected this rate as a valid indicator of quality of care [22]. The reasons were stated by Dr. Robert Haley himself, the task force chair and a principal investigator in the SENIC project: “A hospital's crude overall nosocomial infection rate was considered to be too time-consuming to collect because of the need to do continuous, comprehensive surveillance, unlikely to be accurate, and thus misleading to interpret, and unusable for interhospital comparison because of the lack of a suitable risk index of infection of all types” [23]. Before HAI rates are used for interhospital or intrahospital comparison or as indicators of quality of care, they require risk adjustment. As presently derived, a crude overall HAI rate of a hospital provides no means of adjustment for inpatients' intrinsic or extrinsic risks and is meaningless. Thus, CDC has stated categorically that such a rate should not be used for interhospital comparison [24].
Definitions of HAIs
HAI definitions usually involve clinical, laboratory, and imaging parameters. If they involve only laboratory or imaging parameters, there may be no clinical relevance to the event. One may not know that the patient really had an HAI because nearly all laboratory tests have false negatives. Alternatively, there may be no single laboratory test for the event. However, if only clinical parameters are used, for example, a doctor's note or diagnosis, there may be too much subjective variation for the event to be useful to examine across hospitals. Finding and documenting events in hospitals (i.e., case-finding) such as mortality can occasionally be straightforward. However, finding HAIs requires considerable training before an HCW can reliably and accurately determine whether a patient has the infection. Medical record abstractors have consistently performed poorly at HAI case-finding compared with ICPs or electronic data capture methods [25].
The NNIS system has definitions for 13 major anatomic sites, each with 1–8 specific site codes. Each site code has ≥1 criteria that may include various combinations of the defining parameters as outlined earlier. Experience in the NNIS system has confirmed that targeted surveillance is better than hospitalwide surveillance for three main reasons [26]. First, case-finding is more accurate if targeted in a specific area, for example, a surgical ICU or other specialized units. Second, in practical terms, targeting a specialized unit is more efficient for the ICP and the allocation of limited resources. Third, risk adjustment is much more feasible for patients in targeted units [6].
With increasing numbers of patients currently being managed at home for malignant neoplasms that require intravenous chemotherapy, autoimmune conditions that require immunosuppressive therapy, SSI care following hospital discharge, chronic infections (e.g., osteomyelitis or endocarditis) that require long-term antimicrobial therapy, chronic urinary problems or renal failure with in-dwelling urinary catheters or ambulatory peritoneal dialysis, HAIs associated with the respective indwelling devices or surgical wounds commonly ensue. In addition, increasing numbers of LTCFs have established high dependency units to manage critically ill residents, who inevitably acquire infections once they become exposed to invasive devices or procedures. Notwithstanding the recognition of an increasing problem with infections associated with home healthcare, there are still too few guidelines for uniform standards and definitions of infections acquired in the home or LTCFs. Moreover, formal documentation of infections in these settings remains limited, largely because few facilities have designated surveillance personnel or, if they do, the designated personnel are unsure about what numerator or denominator data to collect. Infections in outpatients and ambulatory care settings are common. However, problems that preclude institution of surveillance activities for infections in these settings include the obvious queries: What infections to survey? What definitions to use? Who would be responsible for surveillance data collection? Where should the data be sent for aggregation and analyses? One of the few successes has been in the area of ambulatory hemodialysis centers. In 1999, CDC established the Dialysis Surveillance Network (DSN), a voluntary national system to monitor and prevent infections in patients undergoing hemodialysis [27,28]. With >100 participating hemodialysis centers, the DSN
P.486
collects and reports outcome events, including vascular access site infections to CDC.
Rates by Site of HAI
HAIs involve diverse anatomic sites. However, the relative frequencies of these infections vary by site and by pathogen. Among all NNIS ICUs combined, the most common HAIs stratified by anatomic site are ventilator-associated pneumonia (VAP)(29%), UTIs (23%), BSIs (17%), and SSIs (7%) (Figure 29-1). However, the overall HAI rates and relative frequencies of different sites of HAIs tend to vary by type of ICU [16]. For example, among adult medical ICUs, the most common HAIs are UTIs (31%), VAP (27%), or primary BSIs (19%) [29]. The corresponding rates for NNIS pediatric ICUs are 15%, 21%, and 28%, respectively [30]. Moreover, the distribution of infection sites and pathogens in pediatric ICU patients differs with age and from those reported from adult ICUs [30]. In 2004, the median rate of VAP per thousand ventilator-days in NNIS hospitals ranged from 2.9 in pediatric ICUs to 15.2 in trauma ICUs [16].
|
Figure 29-1 The most common nosocomial pathogens isolated from the four major infection sites, intensive care unit component, National Nosocomial Infections Surveillance system (NNIS) hospitals, 1990–1998. |
Unlike ICU infections where one risk factor (medical devices) predominates, the risk of SSIs among patients who have undergone surgical procedures is related to a number of factors, which include the operative procedure performed, the experience of the surgeon, the degree of microbiologic contamination of the operative field, duration of operation, and the intrinsic risk of the patient [19,31,32,33]. An SSI risk index that effectively adjusts SSI rates for most operations was developed by CDC for NNIS hospitals [34]. This risk index is based on a system that scores each operation on a scale of 0–3 by counting the number of risk factors present from among the following three: (1) a patient with an American Society of Anesthesiologists (ASA) preoperative assessment score of 3, 4, or 5, (2) an operation classified as contaminated or dirty-infected, and (3) an operation lasting over T hours, where T is the approximate 75th percentile of the duration of surgery for the respective operative procedures reported to the NNIS data base. T, of course, will depend on the operative procedure being performed. The NNIS risk index is a better predictor of SSI risk than the traditional wound classification system, performs well across a broad range of operative procedures, and predicts varying SSI risks within a wound class. This suggests that all clean operations do not necessarily carry the same risk of SSI. Thus, SSI rates should be stratified by risk categories before comparisons are made among institutions and surgeons or across time. Exceptions are spinal fusion, craniotomy, ventricular shunts, and caesarean section operations in which SSI risk is not predicted by the risk index.
P.487
Nosocomial BSIs cause substantial morbidity and mortality with at least 250,000 confirmed BSIs occurring each year in United States hospitals [35]. BSIs are either primary or secondary. The former are culture-documented BSIs in which no other site of infection was found to be seeding the bloodstream and usually ensue following direct infection. Of nosocomial BSIs reported to NNIS, approximately 64% are primary. Intravascular catheter use is the major cause of primary BSI. The microbiologic features of primary BSI have changed since the early 1980s. In 2004, CDC reported the highest mean rates (number BSIs per 1000 central line-days) of central venous catheter-associated BSIs (CVC-BSIs) in trauma ICUs (7.4), followed in descending order by burn ICUs (7.0), pediatric ICU (6.6), and medical ICUs (5.0); the lowest BSI rates (2.7) were found in cardiothoracic units [16].
On the basis of its microbiologic features, the pathogenesis of secondary BSIs (not included in Figure 29-1) appears to be different from primary BSIs. The risk of secondary BSI is highest after lower respiratory infections (7.8%), SSIs (6.6%), or UTIs (4.4%). Complications of infection by secondary BSI are most common on the cardiac surgery service (9.0%), followed by general surgery service (6.5%), the high-risk nursery (6.4%), the burn or trauma service (5.6%), and the urology service (4.9%). Secondary BSI was least likely on the otolaryngology service (2.6%), the orthopedic service (2.5%), and the gynecology service (2.3%). Secondary BSIs also are more likely in teaching hospitals. The organisms most commonly associated with secondary BSIs include Staphylococcus aureus (20.9%), Escherichia coli (11.3%), Pseudomonas aeruginosa (9.6%), and Enterococcus spp (9.2%).
Among the few investigations that have characterized BSIs outside the acute inpatient setting, three epidemiologic studies implicated the use of needleless devices as risk factors for acquisition of BSIs in home healthcare settings [36,37,38,39]. Associated risk factors included receipt of total parenteral nutrition and use of a multilumen catheter. DSN data from 109 participating hemodialysis centers reported that during 1999 through 2001, the vascular access infection rate per 100 patient-months was 3.2 overall and varied by type of vascular access: 0.6 for native arteriovenous fistulas, 1.4 for synthetic arteriovenous grafts, 8.4 for cuffed catheters, and 12.0 for noncuffed catheters [40].
|
TABLE 29-1 |
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
HAI Rates by Pathogen
CDC data indicate that eight pathogens account for approximately 70% of HAIs in U.S. hospitals (Table 29-1); compounding the problem, all eight pathogens demonstrate antimicrobial resistance to ≥1 commonly used antimicrobials [41]. For example, the incidence and prevalence rates of resistance among isolates of S. aureus resistant to methicillin group penicillins (MRSA), Enterococcus spp. to vancomycin (VRE), and Klebsiella pneumoniae to third-generation cephalosporins have been increasing significantly over the past two decades; these rate increases are more marked in the ICU vs. non-ICU inpatient settings [41]. The percentage of MRSA among S. aureus HAIs in NNIS ICUs increased from 2.4% in 1975 to >55.0% in 2001; during 1989 to 2003, the proportion of ICU Enterococcus spp. HAIs reported to NNIS that were caused by VRE increased from 0.4% to >28.0%. This rate increase, in particular, is of enormous clinical importance because
P.488
the documentation during the 1990s suggested that at least 83% of VRE isolates were resistant to most of the available antimicrobials [42,43]. Although newer agents (e.g., daptomycin or linezolid) have proven effective against VRE, treatment options for patients with VRE-HAIs remain limited, often to unproven combinations of other antimicrobials or experimental compounds. That Enterococcus spp. infections now present a serious challenge for physicians is underscored by the fact that this is the most common SSI pathogen and the second most common BSI pathogen after coagulase-negative staphylococcus in all NNIS ICUs combined (Table 29-1) [41].
Of the microorganisms that predominate among the four major infection sites (BSI, SSI, VAP, or UTI), Enterococcus spp. are the most common cause of SSIs (16%), followed by coagulase-negative staphylococcus (13%), S. aureus (12%), and P. aeruginosa (10%) (Figure 29-1). Although coagulase-negative staphylococcus remains the most commonly reported cause of nosocomial BSIs (37%), this rate of occurrence is probably inflated largely because coagulase-negative staphylococcus is a common blood culture contaminant in hospitals and, not infrequently, a single blood culture that yields growth of coagulase-negative staphylococcus is deemed clinically significant when in fact it is not. That said, coagulase-negative staphylococcal BSIs remain the best marker of intravascular device-related infections in ICUs. Tokars et al. have shown that for blood cultures positive for coagulase-negative staphylococcus, the positive predictive value for clinical significance was 55% for 1 positive culture result of 1 culture performed, 20% for 1 positive result of 2 performed, and only 5% for 1 positive result of 3 performed [44]. In addition, he showed that for 2 positive culture results of 2 cultures performed, the positive predictive value is 98%, if both samples were obtained through the vein [44]. Further studies like this one and improvements in surveillance definitions and laboratory techniques are needed to further clarify the roles of coagulase-negative staphylococci, anaerobic bacteria, and viruses whose true roles as causes of HAIs have not yet been fully characterized.
NNIS data confirm that in addition to coagulase-negative staphylococcus, other common nosocomial BSI in descending order of frequency include Enterococcus spp. (14%), S. aureus(13%), Candida albicans (5%), and Enterobacter spp. (5%). Data from the Surveillance and Control of Pathogens of Epidemiological Importance (SCOPE) study, a multicenter surveillance system for BSIs in the United States, have established that gram-positive organisms are associated with 65.0% of nosocomial BSIs while gram-negative organisms and fungi cause 25.0% and 9.5%, respectively [45]. The frequencies of BSI pathogens in the SCOPE study were as follows: coagulase-negative staphylococcus (31%), S. aureus (20%), Enterococcusspp. (9%), and Candida spp. (9%)—similar to NNIS data.
The increasing role of gram-negative pathogens as important causes of HAIs has been highlighted in a relatively recent editorial [46]. For example, gram-negative BSIs predominate in patients with malignancies, burn patients with catheters, and patients with needleless intravascular devices [38]. Although S. aureus remains the most common (18%) cause of nosocomial pneumonia in NNIS hospitals, the next four most common causes are gram-negative microorganisms: P. aeruginosa (17%), Enterobacter spp. (11%), K. pneumoniae (7%), and Acinetobacter spp. (5%). In a recent NNIS analysis, Gaynes et al. found that gram-negative bacilli are still commonly associated with HAIs in ICUs and that during 1986 through 2003 were associated with 24% of BSIs, 65% of pneumonias, 34% of SSIs, and 71% of UTIs [47]. In addition, they found that the percentage of BSIs or SSIs associated with gram-negative bacilli decreased from 33.2% in 1986 to 23.8% in 2003 and from 56.5% in 1986 to 33.8% in 2003, respectively. Although the percentages of pneumonias and UTIs associated with gram-negative bacilli remained constant during the study period, the proportion of Acinetobacter spp. associated with ICU pneumonias increased from 4.0% in 1986 to 7.0% in 2003 [47].
Risk Factors and Determinants Associated with HAIs
The strongest determinants of HAI risk are the characteristics and exposures of patients that predispose them to infection and the complex interactions of agent (microorganism causing infection), host (susceptible patient), and environment (e.g., hospital ICU, outpatient, hemodialysis center, or home). Agent, host, and environment make up a triad that is a useful model for the characterization of infectious disease epidemiology in healthcare and other settings [48]. In this model, the environment is the backdrop against which a microorganism interacts with a susceptible patient to cause infection. The success of this process depends on both the microorganism and the host: it is increased in the nonimmunized or immunocompromised host and depends on the intrinsic properties (infectivity, pathogenicity, and virulence) of the microorganism. Other factors that are important to the production of disease include the infecting dose, the microorganism's ability to produce toxins, its immunogenicity and ability to resist or overcome the human immune defense system, and its ability to replicate only in certain type of cells, tissues, or patients. Other intrinsic and genetically determined properties of a microorganism may be important for it to survive in the host or environment. In the inpatient setting, these include the organism's response to the effects of heat, drying, disinfection or sterilization, or antimicrobials; its ability to compete with other microorganisms within the host or the environment; and its ability to independently multiply in the environment [48].
For transmission and infection to occur, the microorganism must remain viable in a reservoir or the environment until direct or indirect transfer to a susceptible host and
P.489
contact with the host has been sufficiently long enough to cause infection and disease. The entire transmission process constitutes a chain of infection. If this chain of infection remains unbroken, the size of the reservoir may increase in the continuing chain of transmission. Examples of reservoirs that allow the agent to survive or multiply include HCW carriage of S. aureus in the anterior nares, P. aeruginosa under false fingernails, Serratia marcescens in soap preparations or damp areas around sinks, Legionella spp. in central humidifiers of air conditioning systems that disseminate the organism through the air in droplet nuclei, dialysis fluids that are intrinsically contaminated at the manufacturer, multidose vials that become contaminated during access with a needle and syringe (this becomes a major problem if numerous patients receive fluid from a single contaminated multidose vial), or sterile infusates that become extrinsically contaminated in the hospital pharmacy [49,50,51,52,53].
Indirect-contact transmission is the most common mechanism of transfer of the microorganisms that cause HAIs and commonly occurs via HCW hands. Other examples of indirect contact transmission include contaminated inanimate objects (fomites), work surfaces, and biological fluids (e.g., respiratory, salivary, gastrointestinal, or genital secretions; blood; urine; or stool). Medical devices contaminated with bloodborne pathogens (e.g., hepatitis B and C viruses, cytomegalovirus, or human immunodeficiency virus [HIV]) are sources of infection for both patients and HCWs in hospitals, outpatients, LTCFs, or the home. In pediatric populations, fecal-oral spread is an important means of indirect-contact transmission of a variety of bacterial, viral, and parasitic diseases. The mechanisms are commonly stool-to-hand-to-mouth or stool-object-mouth. Thus, in the United States, rotaviruses account for approximately 50% of all cases of nosocomial gastroenteritis in pediatric patients [54]. The airborne transfer of droplet nuclei is the principal route of transmission ofMycobacterium tuberculosis, varicella (chicken pox), measles or Legionella spp.
Patient factors (e.g., age, state of debilitation, immune or nutritional status, device usage, invasive procedures, or antimicrobial therapy) play important roles in determining whether or not a patient will acquire an HAI. Special units for intensive medical or surgical care and for extensive burns, trauma, transplantation, and cancer chemotherapy frequently house patients who are susceptible to infection and disease caused by endemic organisms. In these patients, reduced inocula of pathogens may cause infection and disease, and nonpathogenic agents (e.g., coagulase-negative staphylococcus) may cause serious disease or death. Frequent opportunistic infections in these patients require repeated, broad, and extended therapy with multiple antimicrobials, leading to increasingly resistant resident microbial populations. Commensal microorganisms can become opportunistic pathogens under appropriate conditions. Patients with immunosuppression (e.g., patients with hematology conditions or HIV infection or who have had solid organ or bone marrow transplants or are receiving antineoplastic drugs) are at high risk of opportunistic bacterial, fungal, or protozoal infections.
Whether an infecting agent produces clinical or subclinical infections also depends on the agent and certain host factors, e.g., age and immune status. For example, P. aeruginosa, a ubiquitous pathogen that thrives in aquatic environments, soil, and vegetation, seldom causes disease in healthy populations. However, in debilitated populations, such as those with burns, malignancies, leukemia, critical care patients with multiple in situ invasive medical devices, or children with cystic fibrosis, this pathogen remains a significant cause of nosocomial pneumonia and BSIs [29,30].
Over the past three decades, much epidemiologic and clinical research have been carried out, either through formal studies or outbreak investigations, to characterize the risk factors associated with the occurrence of HAIs in various U.S.healthcare settings. It has not always been clear whether identified risk factors are merely associations with infection but not necessarily the underlying cause, or are indeed the true cause of the HAI. Undoubtedly, some risk factors will be the true cause of infection while others will be only coincidentally associated with infection because they follow infection, occur along with the truly causal factors, or are merely surrogate markers for the true risk factors. Complicating matters further is the fact that ≥2 independent risk factors often occur simultaneously in the same patient, sometimes exerting additive or even synergistic effects. Such risk factors are strongly intercorrelated.
NNIS data show increased HAI rates in ICUs [26,55,56,57,58,59]. The reasons for this increase include (1) increased ICU patient census due to greater need for intensive care, (2) a greater number of susceptible patients (e.g., the very young or elderly, and those with severe underlying disease, burns, malnourishment, or immunosuppression) being admitted to ICUs, (3) increased use of invasive medical devices in ICUs, or (4) HAIs due to lapses in infection control (IC) crowding, decreased nurse-to-patient ratio in the ICU, or increased presence of nosocomial pathogens in the environment [13,60,61,62,63,64].
Environmental factors, the third component of the triad, facilitate the transmission and acquisition of HAI through three principal modes of interaction with agent and host that determine infection or disease (i.e., agent-host, agent-environment, and host-environment interactions). The relative contribution of each of these interactions to acquisition of infection or disease is rendered complex because of the wide variety of infectious agents, hosts, environmental factors, and variability of parameters that make up each of these components. For example, NNIS data suggest that the ICU is currently the area of highest risk for the transmission of HAIs [26]. Moreover, MRSA, VRE, and P. aeruginosa already are endemic in many NNIS ICUs [26,65]. A complex
P.490
interaction of factors, such as a pathogenic microorganism that is endemic in the ICU environment, a population of susceptible patients, inadequate hand hygiene or infection control practices among HCWs, fluctuating staffing levels, unexpected increases in patient census relative to staffing levels in the ICU, or an unexpected increase in the number of severely ill patients with multiple invasive devices could all concomitantly contribute to HAI acquisition caused by these endemic organisms [13,63]. Adding to the complexity of the process would be the transmission of the agent from host to HCW, HCW to HCW, and host to environment. Thus, acceptable HAI prevention and control measures dictate that the hospital epidemiologist looks at and analyzes the interrelationships among all components of the triad of agent, host, and environment.
It is well known that the social environment is extremely important in determining human behavior that affects the direct transmission of agents (e.g., artificial nails worn by HCWs in ICUs) [49]. Equally relevant is the impact of other social factors (e.g., distribution of and access to medical resources) use of preventive services or enforcement of infection control practice recommendations, acceptance of advice or guidelines on the appropriate use of antimicrobials, or appreciation by relatives, patients, and HCWs and personnel alike that patients who are aged, severely ill, born prematurely, or have congenital abnormalities, have numerous indwelling medical devices or have had multiple invasive procedures or surgery will be especially susceptible to HAIs. Finally, there must be a willingness of all involved to appreciate the limitations of medical technology and antimicrobials when all other clinical evidence and experience suggest that the condition of the sick person is irreversible.
To design strategies for preventing HAIs, it is important to differentiate among coincidental indicators of risk, independent causal factors, and synergistic interactions of causal factors. In a study of 169,526 patients who made up a representative sample of patients admitted to acute care U.S. hospitals in 1975 and 1976, population estimates of HAI rates for each of the four major types of infection were calculated within each category of exposure to between 10 and 20 separate risk factors [4,66,67]. A striking finding was that all of the risk factors were associated with HAI at all four major anatomic sites. At first, this seems surprising because one would not expect a direct causal association between mechanical ventilation, for example, and acquiring a urinary tract infection. The explanation, of course, is that some of the associations indicate direct causal relationships; others indicate partial causal relationships, potentiated or diminished by other concurrent influences; and others (such as that between respirators and urinary tract infection) represent largely coincidental associations (most patients on respirators also have indwelling urinary catheters that predispose them to UTI).
The two factors that appeared to exert the strongest causal influences in all four sites of infection were indicators of the degree of the patient's underlying illness: (1) in surgical patients, the duration of the patient's operation, and (2) an index of the number and type of distinct diagnoses and surgical procedures recorded (intrinsic risk index). After these, several factors were strongly associated with infections at one or two sites but not with all four. Having a combined thoracoabdominal operation was strongly associated with pneumonia and SSI; undergoing a “dirty” (or contaminated) operation was associated with SSI; having an indwelling urinary catheter was linked to UTI; being on a respirator, with VAP or BSI; previous HAI, with BSI; and receiving immunosuppressive therapy with BSI. Examples of risk factors that had weaker associations with all four sites were age, gender, previous community-acquired infection, and length of preoperative hospitalization.
Multivariate modeling has demonstrated that the risk of HAI is primarily determined by definable causal factors reflecting the patient's underlying susceptibility to infection or the degree to which microorganisms have access to vulnerable body sites. Modification of ≥1 of these factors can alter a patient's risk. Multivariate statistical models can be developed to predict accurately a patient's HAI risk from measurable risk factors.
Colonization is the presence of a microorganism in or on a host with growth and multiplication but without any overt clinical expression or detected immune reaction in the host at the time the microorganism is isolated. In a colonized patient, an infectious agent may establish itself as part of a patient's flora in multiple or specific anatomic sites or may cause low-grade chronic disease after an acute infection. Under suitable conditions, various patient populations who are colonized with S. aureus are at an increased risk of developing infection and disease [68,69]. For example, nasal colonization with S. aureus may be a risk factor for SSI in pediatric patients undergoing heart operations or for catheter-related infections in pediatric patients on chronic peritoneal dialysis [70,71]. HCW hands, colonized with gram-negative pathogens such as S. marcescens or P. aeruginosa, may become potential sources of outbreaks in neonatal ICUs [49,50].
Severity of Illness
In the NNIS system, the validity of HAI rates from ICUs, adjusted for extrinsic risk factors, would be enhanced if they were better adjusted with a direct measurement of patients' severity of illness. Otherwise, hospitals providing care for patients with a greater severity of illness may have higher HAI rates. Properties of a severity of illness score should include specificity for a particular HAI and site of infection.
CDC researchers performed a search of the medical literature to identify a severity of illness scoring system (SISS) that would be useful for further adjusting ICU HAI rates [72]. Eleven studies reported use of an SISS; four correlated SISS with all HAI sites but did not meet with
P.491
success; six showed some predictive value between SISS and nosocomial pneumonia. The Acute Physiology and Chronic Health Evaluation (APACHE II) score was the most commonly used SISS but performed inconsistently and may not be available in many ICUs. Thus, although existing scores predict mortality and resource use, none are presently available for prediction of HAI risk. Until such measures are available, comparative HAI rates will be limited in their use as definitive indicators of quality of care.
Pediatric/Neonatal Populations
The major HAI risk factors in pediatric or neonatal populations include intrinsic host factors that are important to the development and severity of infection or disease. These include gestational age, gender, birth weight, congenital abnormalities, age at infection, race, nutritional status, genetically determined immune status, immunosuppression associated with other infections, therapy, and vaccination status or previous exposure to the relevant microorganism. Extrinsic factors for adults are similar and include invasive medical or surgical procedures, use of medical devices, such as intravenous catheters or mechanical ventilators, duration of hospitalization, or exposure to HCWs [73].
The risk of acquisition and transmission of infectious diseases among pediatric populations in healthcare settings are better characterized if the patients' immune status or immune response is known. Immunization is the most effective method of individual and community protection against epidemic diseases and plays an important role in the prevention and control of certain HAIs acquired by inpatient pediatric populations. As the proportion of a population immunized by previous exposure to the agent or by vaccination increases, the probability and opportunity for transmission of the agent within that population declines. Viruses are a frequent cause of HAI, morbidity, and mortality in pediatric populations [54,59]. Both symptomatic and asymptomatic patients with viral infections can be a source of transmission [74]. At present, the influenza vaccine is the only vaccine available to prevent infection caused by respiratory viruses. Children at high risk for severe influenza infection who should be vaccinated include those with chronic lung disease, congenital heart disease associated with significant hemodynamic disturbances, hemoglobinopathies (e.g., sickle cell disease), and children being treated with immunosuppressive agents [54,59].
Seasonality and Secular Trends of HAIs
Seasonality
The occurrence of HAIs is a dynamic process. Changes are constantly occurring in the types of patients admitted to hospitals, risk factors to which they are exposed, character of the pathogens predominating in the hospital milieu, quality of patient care, thrust of infection control efforts, and other important factors. Two indicators of the dynamic nature of the problem are the seasonality of certain types of HAIs and the long-term secular trends that may occur. Analyses of NNIS data repeatedly have shown seasonal variations in the occurrence of HAIs involving certain gram-negative bacteria [75,76,77,78]. The report of the 1980 to 1982 results showed clear seasonal peaks of infections in the summer and early fall for Klebsiella, Enterobacter, Serratia, Acinetobacter species, and P. aeruginosa; staphylococcal and streptococcal infections show no significant seasonal variation in the hospital. No seasonal variation was observed for infections caused by other common pathogens, such as E. coli, Enterococcus spp., Enterobacter spp., or anaerobes. More recent analyses have confirmed that the frequency of Acinetobacter spp. infections is increasing in critical care units in NNIS hospitals and are seasonal in nature [78]. Seasonal variation in the occurrence of Acinetobacter spp. HAIs is thought to be associated with changes in climate: summer weather increases the number of Acinetobacter spp. in the natural environment and may affect the hospital environment, promoting nosocomial transmission [79]. Nosocomial viral respiratory infections occur mostly during the seasons in which they occur in the community (e.g., influenza and respiratory syncytial virus infections in the winter and early spring) [80,81].
Clostridium difficile-associated diarrhea currently is the major nosocomial gastrointestinal infection and is endemic in many U.S. general hospitals [82,83]. During 1987–2001, there was overall seasonal variation in the occurrence of C. difficile-associated diarrhea in NNIS hospitals: Higher rates were documented during the winter months (January–March) vs. the nonwinter months [84]. Reasons for this variation include persistence of viable spores during the winter months and increased patient census or reduced nurse-to-patient ratios resulting in overcrowding in the ICUs during the winter. Also, because hospitals tend to admit higher numbers of patients with respiratory infections during winter months, one would naturally expect a parallel rise in antimicrobial use, a major risk factor for C. difficile-associated diarrhea, during this time of the year. However, the magnitude of the difference between winter and nonwinter rates varied by year [84]. Thus, factors other than climatic conditions (e.g., variation in antimicrobial use, staffing, or severity of illness on admission) may be playing additional roles in the seasonal occurrence of C. difficile-associated diarrhea in hospitals [84].
Secular Trends of HAIs
In prevalence studies performed over several decades, the relatively small sample sizes have hampered the detection of secular changes. An analysis of secular trends in the NNIS System from 1970 to 1979 suggested that SSIs decreased slightly over the decade, BSIs might have increased, while other HAI types remained unchanged [75]. NNIS data indicate changes in the entire distribution of HAI rates
P.492
following the dissemination of comparative HAI rates back to clinicians. Since 1987, when NNIS began reporting device-associated, device-day rates, there has been a 7% to 10% annual reduction in mean rates for device-associated infections in ICUs [85]. During 1980–1989, however, coagulase-negative staphylococci emerged as one of the most frequently occurring BSI pathogens [86]. During 1990–1999, risk-adjusted rates for BSI, VAP, and UTI decreased significantly in NNIS medical ICUs [87]. NNIS adult and pediatric ICU surveillance data from 1987 through 1996 show a downward trend in the rate of Acinetobacter spp. infections overall (cf., the increase in ICU pneumonia caused by Acinetobacter spp. from 4% in 1986 to 7% in 2003) [47]. The exact reasons for the decreases in risk-adjusted rates for BSI, VAP, or UTI have not been well studied but might be secondary to more hospitals participating in organized, surveillance systems that stimulated infection-prevention efforts [88].
During 1980–1990, the rate of nosocomial fungal infections increased at all four major anatomic sites of infection. Patients with BSIs who had a central intravascular catheter were more likely to have a fungal pathogen isolated than were other patients with BSI [89]. NNIS data from January 1989 through December 1999 have shown a significant decrease in the incidence of C. albicans BSIs; however, during the same time, the incidence of Candida glabrata BSIs increased [90]. The decrease in C. albicans BSIs is likely a reflection of the overall decrease in BSI rates associated with bacterial and fungal pathogens in NNIS hospitals over the past decade and potentially the increased use of antifungal prophylaxis [14].
In 2004, a CDC report confirmed that the incidence of C. difficile-associated disease steadily increased from 1987 through 2001 [84]. This report also confirmed that the incidence rate of C. difficile-associated disease during this 15-year period increased significantly in the ICUs of hospitals with >500 beds and that the major independent risk factors were longer duration of patient ICU stay, mechanical ventilators, intravascular devices, or urinary catheters. This upward trend in C. difficile rates could be due to three major factors: increasing antimicrobial use in U.S. hospitals, increasing ICU patient census, or increased frequency and sensitivity of diagnostic testing.
Although there was a general decrease in the total number of beds in NNIS hospitals during the 1990s, the number of ICU beds increased during the same period [26]. This increase in the numbers of ICU beds would have meant a potentially higher number of patients admitted to ICUs, higher numbers of severely ill patients, and increased antimicrobial use. More recently, Kyne et al. have established that patients who acquired C. difficile-associated disease were significantly more likely to have a higher severity of illness score at admission [91]. This, combined with the obvious prolongation of ICU stay and increase in use of invasive medical devices and antimicrobial use that one would expect in the ICU, would be obvious risk factors for acquiring C. difficile-associated disease as was subsequently confirmed in the CDC report [84].
Rates by Service
HAI rates differ by service and specialty areas. The accuracy of HAI rates would be enhanced if better adjusted with, for example, direct measurement of severity of illness or service specialty. The SENIC project showed that surgery patients were not only at highest risk of SSI but compared with medical service patients also were at higher risk of VAP (four times higher), UTI, and BSI (one and one-half times higher). These results, however, reflecting combined data from the ICU and hospitalwide components, were not risk adjusted, and, therefore, were not valid for inter- or intrahospital comparison. By the early 1990s, CDC had begun to report HAI rates that had been adjusted for service. For example, NNIS data during 1990–1994 showed a stepwise decrease in HAI rates (calculated as the number of infections per 1,000 patient-days) by service as follows: burn or trauma service (15.0), cardiac surgery service (12.5), neurosurgery service (12.0), high-risk nursery (9.8), general surgery service (9.2), and oncology service (7.0). Lowest rates were found on the pediatric service (3.3), the well-baby nursery (1.7), and the ophthalmology service (0.6). In the most recent NNIS report summary (January 1992 through June 2004), rates are risk adjusted for device use and type of ICU [16]. CDC data also have shown that medical service inpatients appear to be at greater risk of contracting C. difficile-associated disease compared with inpatients on the surgical, pediatric, or obstetrics and gynecology services [84].
Because of this variability with service, risk adjustment according to service is mandatory when conducting inter- or intrahospital HAI rate comparisons. The importance of risk adjusting by service is underscored by the disparate device-associated infection rates in the urinary tract, bloodstream, or respiratory tract reported in the most recent NNIS surveillance report (Table 29-2).
Rates by Hospital Type and Geographic Region
It has long been apparent that, overall, HAI rates differ substantially from one hospital to another. In the mid-nineteenth century, Sir James Y. Simpson found that the rate of death from infection of amputated extremities varied directly with the size of the hospital in which the operation was performed (with larger hospitals having higher rates), a phenomenon he called “hospitalism” [92]. The average HAI rates of NNIS hospitals were reported to vary from 1.7% in small community hospitals to >11.0% in chronic disease hospitals [93]. However, as discussed earlier in this chapter, overall HAI rates like these are meaningless.
Among the numerous NNIS data analyses conducted over the years, characteristics consistently found to be
P.493
associated with higher HAI rates include affiliation with a medical school (i.e., teaching vs. nonteaching), size of the hospital and ICU categorized by the number of beds (large hospitals and larger ICUs generally had higher HAI rates), type of control or ownership of the hospital (municipal, nonprofit, investor owned), and region of the country [94]. These relationships were consistent for each of the four major anatomic sites of infection. In addition, within these four hospital groups, rates of UTI, SSI, or BSI were generally higher in the northeast and north-central regions, whereas VAP rates were higher in the west. More recent NNIS data show increased rates of C. difficile or Acinetobacter spp. infections in the northeast [78,84]. For C. difficile, the lowest rates were in nonteaching hospitals, and intermediate rates in teaching hospitals with <500 beds; highest rates were observed in teaching hospitals with ≥500 beds.
|
TABLE 29-2 |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Various analyses of the SENIC and NNIS data have found that indices of patients' risk factors explained the greatest part of the interhospital differences. After controlling for patients' risk factors, average length of stay, and measures of the completeness of diagnostic workups for infection (e.g., culturing rates), the differences in the average HAI rates of the various hospital groups virtually disappeared. These findings suggest that much of the difference in observable HAI rates of various types of hospitals is due to differences in the intrinsic degree of illness of their patients, related factors (e.g., age, co-morbid conditions), and whether or not the hospital has a functioning HAI surveillance system. For these reasons, the overall HAI rate per se usually gives little insight into whether the hospital's infection control efforts are effective.
Trends in HAI Rates vs. Antimicrobial Resistance Rates Associated with Nosocomial Pathogens
Failure to fully apply infection control precautions may result in unmitigated spread of HAI pathogens in ICUs, especially where there is already heavy invasive device use, empiric antimicrobial prescribing, a population of critically ill patients who are more susceptible to overgrowth of endogenous resistant pathogens, high patient census, and numerous opportunities for cross-transmission due to frequent close contacts between the various HCWs who work in such units and patients. A combination of all of these factors with failure to fully identify those patients who are colonized or infected with antimicrobial-resistant pathogens and with the fact that there has been a significant increase in numbers of U.S. ICUs might be the reason for the upward secular trends in antimicrobial resistance among HAI pathogens. Although patients admitted to ICUs in U.S. hospitals are at greatest risk of acquiring HAIs, NNIS data suggest that overall rates of device-associated HAIs are decreasing while rates of HAIs caused by antimicrobial-resistant pathogens continue to increase.
Epidemic HAIs
Incidence, Recognition, and Control
Each year, numerous publications describe the investigation of HAI outbreaks at individual institutions, the findings and inferences of these investigations, and the resulting prevention and control measures that ensue. However, there is a paucity of published data on the frequencies of the underlying causes of these epidemics or on the comparative nature of HAI outbreaks among institutions. The earliest study on this subject was the CDC's CHIP study in the early 1970s [95]. Among seven community hospitals participating in CHIP during 12 months in 1972 to 1973, a computerized threshold program screened the regularly reported episodes of HAI for clusters of infection that might indicate an outbreak, and a CDC epidemiologist analyzed the data to eliminate purely coincidental clusters. Next, CDC personnel visited the hospitals that had potential outbreaks to confirm the nature of the problem and recommend control measures if needed. From these data it was estimated that one true outbreak occurred for every 10,000
P.494
hospital admissions and that HAI outbreaks accounted for approximately 2.0% of all documented HAIs. Wenzel et al. estimated that 3.7% of HAIs in a large, university-affiliated referral hospital occurred in outbreaks [96]. Although confined to a relatively small number of hospitals, these estimates appear to confirm the prevailing view that HAI outbreaks account for a fairly small proportion of HAIs in healthcare institutions [95,96]. Other data have indicated that >90% of HAIs do not occur in recognized epidemics [97].
The CHIP investigations also demonstrated that 40% of the outbreaks likely resolved spontaneously whereas the remaining 60% continued until control measures were instituted [95]. Half of the outbreaks that continued were controlled by measures taken by the hospitals' IC staff and the other half completely resolved only after implementation of measures recommended by outside investigators. This relatively high rate of spontaneous resolution might explain the underlying argument against surveillance expressed by some people. However, if these figures are representative of community hospitals in general—and it should be borne in mind that these were hospitals with active HAI surveillance systems—then a large number of outbreaks may be going unrecognized and uncontrolled despite the advanced state of IC programs.
HAI Outbreaks
Investigation of HAI outbreaks requires a systematic approach that includes ascertainment that an epidemic does indeed exist, formulation of an appropriate case definition, and implementation of epidemiologic methods to identify risk factors and determine whether the relation between the factor and infection is associative or causative, which is essential for understanding the mechanisms of infection acquisition and transmission and for implementing appropriate control and preventive measures. This process assumes some previous knowledge of the usual or endemic rate of occurrence of the infection or disease under study. Moreover, for this determination, one must have an understanding of the epidemiology of the infection or disease (i.e., the possible common sources, putative modes of transmission, usual reservoirs, incubation periods, and the microbiology of the microorganism of concern, including pathogenicity and virulence). This information is essential for the formulation of hypotheses and the design of relevant epidemiologic, observational, and microbiologic studies necessary for confirming the hypothesis.
Many factors influence the types of investigations of HAI outbreaks conducted by CDC. These include the types of outbreaks that are recognized, the expertise of the personnel who request CDC's assistance, whether outbreaks are of sufficient potential public health importance (e.g., attributable morbidity or mortality) to warrant CDC's involvement, investigator availability, and whether a CDC investigation might add to infection control knowledge to help prevent or control similar outbreaks in the future. Thus, CDC outbreak investigations often reflect problems that are unique, urgent, perplexing to ascertain, or difficult to control.
From 1956 to 1979, CDC carried out 252 hospital outbreak investigations; these have been summarized by Stamm and co-workers [97]. In the ensuing 16 years through 1995, CDC assisted in another 193 outbreak investigations. In the early years (1956–1962), the two most common problems investigated were epidemics of gastrointestinal disease, primarily due to Salmonella species or enteropathogenic E. coli, or staphylococcal infections; both types of epidemics were most frequently encountered in newborn nurseries. In the early 1960s, the investigation of staphylococcal infections abruptly decreased and was followed in the 1970s by a decrease in the number of gastrointestinal outbreak investigations in healthcare settings. This likely reflected a decrease in the incidence of such outbreaks because of improved understanding of the epidemiology and control of such infections or the improved ability of IC personnel to recognize and control such outbreaks without CDC's assistance.
From the late 1960s through the 1980s, there was an increase in the number of investigations of nosocomial BSI outbreaks, SSI, and problems related to ICUs, newly introduced medical devices, and various surgical and invasive medical procedures. Many of these outbreaks were associated with gram-negative pathogens. During the 1970s, outbreaks of BSIs in healthcare settings were the most common types of investigations carried out by CDC. However, increasing numbers of HAI outbreaks were associated with anatomic sites other than the bloodstream, respiratory tract, urinary tract, and surgical wounds or medical devices: These included outbreaks of hepatitis A virus or hepatitis B virus infections; necrotizing enterocolitis in nurseries; sternal wound infections after open heart surgery, particularly those caused by rapidly growing mycobacteria; and nosocomial Legionnaires' disease. Also during this period, CDC recorded increasing numbers of outbreaks associated with microorganisms resistant to multiple antimicrobials, particularly aminoglycoside-resistantEnterobacteriaceae and non fermentative gram-negative bacilli, and MRSA.
In a review of outbreak investigations in healthcare settings conducted by CDC during 1980 through 1990, Jarvis documented a total of 125 on-site epidemiologic investigations of HAI outbreaks across the United States [98]. Among these 125 outbreaks, 77 (62%) were caused by bacterial pathogens, 11 (9%) by fungi, 10 (8%) by viruses, and five (4%) by mycobacteria; 22 (18%) were caused by toxins or other organisms. In addition, BSIs predominated, followed by SSIs and pneumonia. Many of the BSI outbreaks resulted from inadequately disinfected transducers in ICU patients or improper reprocessing of dialyzers [99,100,101]. Although gram-negative organisms accounted for >50% of the outbreaks during the first half of the 1980s, from 1985 to 1990,
P.495
outbreak investigations increasingly involved gram-positive organisms, fungi, viruses, or mycobacteria. During this decade, no outbreaks of UTIs were investigated, <10% of the outbreaks involved nosocomial pneumonia, and rapidly growing mycobacteria were recognized as causes of SSIs, chronic otitis media, and hemodialysis-associated infections [102,103,104]. Several outbreak investigations implicated noninfectious causes, such as vitamin E toxicity in neonates in ICUs and pyrogenic reactions and chemical toxin exposures in hemodialysis centers (e.g., chloramine, hydrogen peroxide) [105,106,107].
The characteristics of the investigations conducted throughout the 1980s likely reflected the increasing use of invasive procedures and devices and the introduction of an ever-increasing number of products. Approximately 33% of the outbreaks investigated occurred in ICU settings, and nearly 25% involved patients who had undergone surgery. Fourteen (11%) outbreaks were device related, 16 (13%) were procedure related, and 28 (22%) were product related. The proportion of outbreaks involving products, procedures, or devices increased from 47% during 1980–1985 to 67% between 1986 and July 1990. For example, nine episodes of Yersinia enterocolitica sepsis were associated with transfusion of contaminated packed red blood cells [108,109]. Each of these independent events was traced to mildly symptomatic or asymptomatic infection in the blood donor. Prolonged storage of the blood cells allowed the proliferation of the Y. enterocolitica, which resulted in sepsis or endotoxin shock when the blood was transfused [108]. In another outbreak investigation, separate episodes of BSI, SSI, or endophthalmitis were traced to extrinsic contamination of a newly introduced anesthetic agent [110,111,112]. The manufacturer of this soybean oil–based product, which did not contain a preservative, did not recommend refrigeration. Laboratory studies demonstrated that when contaminated with low numbers of microorganisms, rapid microbial proliferation ensued [110].
In a more recent review of CDC outbreak investigations in healthcare settings carried out during January 1990 through December 1999, Jarvis documented 114 on-site investigations [113]. These outbreaks occurred in 39 states or territories and reflected the increasing use of invasive procedures and devices, the introduction of an ever-increasing number of products within and outside the traditional acute care hospital setting: 81 (71%) occurred in the hospital inpatient setting, 15 (12%) in dialysis centers, 9 (8%) in the outpatients, 6 (5%) in LTCFs, and 5 (4%) in home healthcare settings [37,113]. Of the outbreaks that occurred in the inpatient setting, 23 (28%) occurred in ICUs and 58 (72%) in non-ICU areas. Overall, 44 (39%) of the 114 outbreaks involved BSIs, 17 (15%) the respiratory tract, 10 (9%) SSIs, and 3 (3%) the gastrointestinal tract; the remaining 34% involved ≥2 systems.
Throughout the 1990s, 93 (82%) of the outbreaks were associated with infections: bacteria (61; 53%), mycobacteria (12; 11%), fungi (10; 9%), viruses (8; 7%), or parasites (2; 2%) [113]. The remaining 21 (18%) outbreaks were associated with endotoxin or noninfectious agents: The noninfectious disease outbreaks included aluminum toxicity in dialysis patients, anaphylactic reactions associated with latex hypersensitivity, and carbon monoxide poisoning in surgical patients [114,115,116]. Viral infection outbreaks included hepatitis A virus transmitted among HCWs in a bone marrow transplant unit, hepatitis B virus infection among LTCF residents or dialysis patients, hepatitis C virus transmission associated with intramuscular immune globulin, and (HIV) transmitted through inadvertent injection of HIV-contaminated material or during dialysis [113,117,118,119].
Fifty-two (46%) of the 114 outbreaks were associated with either an invasive device or invasive procedure. Dialyzers (10; 43%) were the most common invasive devices associated with outbreaks followed by needleless intravascular device use among patients in inpatient, outpatient, or home care settings (7; 29%) [36,37,38,120,121]. The most common invasive procedures were surgery (21; 50%), dialysis (16; 37%), or cardiac catheterization (3; 7%). Twenty (17.5%) of the 114 outbreak investigations were associated with contaminated products, including intravenous anesthetics (9; 8.0%), parenteral solutions (5; 4.4%), or blood products (2; 1.8%). Twenty-one (28.6%) of the infectious disease outbreaks were associated with multidrug-resistant organisms, including multidrug-resistant M. tuberculosis; VRE; S. aureus with reduced susceptibility to vancomycin, vancomycin-resistantStaphylococcus epidermidis, or extended spectrum beta-lactamase producing E. coli and K. pneumoniae [113,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137].
The anatomic sites of infection involved in CDC HAI epidemic investigations differ markedly from those involved in endemic infections (Table 29-3). Of the epidemics investigated by CDC in the 1980s, BSIs predominated, followed by SSIs and pneumonia. Among endemic infections documented during this period, UTIs predominated, followed by SSIs, pneumonia, and BSIs. In addition, the distribution of pathogens associated with epidemic and endemic infections varied markedly. In the 1980s, Pseudomonas or Serratia spp., S. aureus, andCandida species were the most common organisms associated with epidemics, whereas E. coli, coagulase-negative staphylococci, and S. aureus were the predominant endemic HAI pathogens in U.S. hospitals.
During the 1990s, CDC assisted in increased numbers of outbreak investigations caused by M. tuberculosis, Enterococcus spp., Aspergillus spp., and Enterobacteriaceae. In addition, seminal outbreak investigations during that decade heralded the emergence of Enterococcus spp. that were completely resistant to vancomycin and of S. aureus with reduced susceptibility to vancomycin [129,130,136]. Endemic HAI pathogens in NNIS hospitals during the 1990s included S. aureus, E. coli, coagulase-negative staphylococci, Enterococcusspp., P. aeruginosa, Enterobacter spp., and K. pneumonia; these seven pathogens alone were associated with two-thirds of reported HAIs at NNIS hospitals.
P.496
CDC HAI outbreak investigations during the 1990s were essentially similar to the outbreaks of the 1980s: BSIs predominated as before; however, pneumonia moved up to the second place in frequency followed in descending order by SSIs, gastrointestinal infections, and meningitis; among the outbreaks associated with procedures, surgery and hemodialysis predominated. In contrast to the 1980s, the order of occurrence of endemic HAIs reversed during the 1990s with BSIs predominating, followed by pneumonia, and SSIs in that order (Table 29-3).
|
TABLE 29-3 |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Epidemic infections commonly involved more unusual organisms, such as multidrug-resistant M. tuberculosis (described earlier), Ewingella americana, Tsukamurella spp.,Rhodococcus bronchialis, Nocardia facinica, Enterobacter hormaechei, Acremonium kiliense, Malassezia pachydermatis, Ochrabactrum anthropi, various nontuberculous mycobacterai, viruses, and fungi [98,138,139,140,141,142,143,144]. The profile of these outbreaks likely reflected the facts that HAIs vary by service or location (i.e., ICU vs. non-ICU) and that clusters of infections caused by unusual organisms or usual organisms with unusual antimicrobial susceptibility profiles are more easily recognized, whereas clusters of infections caused by common organisms with unremarkable antimicrobial susceptibility patterns are less likely to be recognized as significant. Also, these differences reflect the fact that unusual outbreaks are more likely to be investigated as are outbreaks in which a common-source or personnel carrier is involved than the more common problem of direct
P.497
or indirect contact transmission of endemic infections in which organisms are commonly transferred from patient to patient, patient to HCW, or HCW to patient, via the hands, fomites, or the environment.
A number of selection biases influence which outbreaks are investigated by CDC. First, a problem must be recognized at the institutional (e.g., hospital, outpatients, home) level. Once an outbreak is recognized, the degree of available local expertise influences whether CDC assistance will be sought or requested. Second, if a problem at the hospital level is recognized and brought to the attention of the state health department, interest or expertise at the state level might determine whether the state concurs with the hospital's request for CDC's assistance. CDC is not a regulatory agency. Thus, any request for its assistance to conduct an onsite investigation requires an invitation by the facility's administration and IC and the local and state health departments. Finally, if CDC is invited to assist in an on-site epidemiologic investigation, several factors will determine CDC's response to the invitation. First is the potential public health importance of the problem and its implications for patient safety. For example, if an outbreak is potentially product related or is associated with substantial morbidity or mortality, all efforts will be made to respond. Second is whether the outbreak appears to be caused by an unusual pathogen or a common pathogen with unusual characteristics (e.g., an unusual or uncommon reservoir or mode of transmission), third is the availability of trained personnel to travel to the facility, and fourth is whether the field of healthcare epidemiology can be advanced by the investigation.
All investigations are conducted as collaborative efforts, and close working relationships with local, state, and federal personnel are desirable. These and other selection biases undoubtedly contribute to the profile of epidemic HAIs described in this chapter. Of greatest value to IC is the knowledge gained by an investigation regarding the most common sources and modes of transmission of various pathogens in outbreaks. These data help ICPs focus their preventive interventions on the areas most likely to result in containment of ongoing outbreaks.
In general, the mode of transmission of an outbreak pathogen can be categorized into one of the several groups outlined earlier in this chapter: (1) common source, (2) human reservoir (carrier), (3) cross-infection (person to person), (4) airborne, (5) other environmental (e.g., fomites, extrinsic or intrinsic contamination of medications, or introduction of a new type of medical device), or (6) uncertain modes of transmission. In a recent report, Diekema et al. opined that outbreaks are, by definition, “special cause” events and should be preventable, and almost always reflects poorly on IC practice in a hospital [145]. However, the reason why outbreaks occur is more complex than the above categorization and opinion would suggest, especially as the final occurrence of infection and disease involves multifaceted interactions between the patient, the pathogen, and the environment (the healthcare setting). A review of CDC outbreaks in healthcare settings suggests that although poor IC almost always play a role, outbreaks invariably occur when a series of events (including IC practices) go wrong at the same time. Thus, complex occurrences or failure of ≥2 factors, including unsatisfactory hand hygiene and IC practices among HCWs; fluctuating staffing levels; an unexpected increase in patient census relative to staffing levels in the ICU; an unexpected increase in the number of severely ill patients with multiple invasive devices; immunosuppression caused by illness, therapy, or disease; failure to conduct quality control in the laboratory; failure of engineering to maintain negative pressure differential in an operating room that should have been kept at positive pressure; inadvertent contamination (intrinsic or extrinsic) of soaps, medications, vials, allograft tissues, or devices; poor surgical technique; inadvertent bacteriostasis when conducting quality assurance cultures; or even misinterpretation of existing IC guidelines could all contribute to the transmission of an organism that is already endemic in the healthcare facility, a colonizer of patients, staff, or even relatives, or recently introduced into the facility [13,26,50,51,53,63,146,147,148]. Thus, when outbreaks are classified in terms of mode of transmission, various site-pathogen combinations, often specific to certain patient groups, will almost certainly become apparent and knowledge of these site-pathogen combinations can facilitate initial investigative efforts by focusing on the most likely source or modes of transmission and hypothesis development.
The danger, of course, is for a hospital epidemiologist to make premature inferences regarding association or causation based previous knowledge of site-pathogen combinations. For example, although nosocomial Salmonella spp. infections can be transmitted from person to person and previous salmonella outbreaks in healthcare settings have indeed been linked to common-source food, salmonella in ICUs has been traced to IC practices and device use [113]. Clusters of Pseudomonas cepacia infections should certainly alert IC personnel to the possibility of contaminated solutions, including antiseptics such as povidone–iodine solution [149]; however, Pseudomonas spp. infection has been traced to other very different sources (e.g., external ventricular devices in neurosurgical patients) [150]. Although nontuberculous mycobacteria infection associated with endoscopic procedures should certainly lead one to review endoscope disinfection/sterilization practices, sources of tap water, and causes of endoscope washer reservoir contamination, this class of mycobacteria has been associated with other modes of transmission including liposuction and pedicures or foot baths in nail salons [144,151,152,153,154,155]. Similarly, Group A streptococcal SSIs almost always are traced to an HCW carrier, and carriage can involve the rectum, vagina, scalp, or other sites [156]; thus, the underlying reason for transmission must certainly be ascertained. Outbreaks of gram-negative BSIs
P.498
have been traced to myriad causes, including inadequately disinfected intra-arterial pressure-monitoring transducers, platelet transfusions, soap, contaminated multidose vials, the compounding machine in a hospital pharmacy, and even to staffing levels [13,50,51,53,99,101,157]. Thus, in any HAI outbreak investigation, knowledge of site-pathogen combinations has to be evaluated in the context of the epidemiologic findings during the investigation. Epidemiologic methods should be used to investigate and relate causal factors to an outbreak and are essential for understanding the mechanisms of infection acquisition and transmission and identifying putative risk factors.
The preceding site-pathogen discussion does not lessen the importance of using knowledge of site-pathogen combinations as precedent during the conduct of an outbreak investigation. For example, clusters of Legionella spp. pulmonary infections or invasive Aspergillus spp. SSIs, especially in immunocompromised patients, should stimulate a search for an environmental source for airborne transmission [158,159]. Clusters of patients with nosocomial acquisition of M. tuberculosis or HCWs with tuberculin skin test conversions should lead to an evaluation of tuberculosis patient identification and isolation practices, pressure differentials in isolation rooms, and review of HCW respiratory protective device use [122,123,126,128,160,161]. Recognition of patients infected or colonized with vancomycin-resistant enterococci should lead to an evaluation of IC, hand hygiene, and isolation practices and procedures, antimicrobial use, and whether current recommendations are being fully implemented [129].
The most common cause of both endemic and epidemic infections is cross-infection, whereby organisms are transmitted from HCWs to patients, HCWs to HCWs, patient-to-patient, or patient-to-HCWs. Although almost any organism can be transmitted by cross-infection, gram-negative organisms and S. aureus are the most commonly recognized. Nosocomial viral infections, which frequently occur in pediatric patients, also are often transmitted by cross-infection. Thus, acceptable prevention and control measures of HAIs dictate that the hospital epidemiologist look at and analyze the interrelationships between all components of the triad of agent, host, and environment. What must be understood to be equally relevant is an appreciation by relatives, patients, lawyers, administrators, and HCWs alike that patients who were born very prematurely or are elderly, are debilitated, have severe congenital abnormalities, diabetes or end-stage respiratory, liver, renal, or cardiac disease, have numerous indwelling medical devices or have undergone a major surgical procedure or other invasive procedures will be particularly susceptible to HAIs.
Multihospital Epidemics
As hospitals become more and more specialized, the possibility of multiple hospital outbreaks becomes a greater concern. This occurs most commonly by interhospital spread or movement of patients from LTCFs to hospitals and less commonly through the national distribution of products that cause or predispose to infection. First, a pathogen implicated in an epidemic in one healthcare facility may be introduced into a patient population at another facility, usually via one of three modes of transmission: (1) transfer of colonized or infected patients, particularly those with burns or decubitus ulcers, (2) transfer or movement of colonized or infected HCWs, including medical house staff and nursing personnel, between facilities, and (3) transient colonization of hands of HCWs who rotate among different hospitals and other healthcare facilities. Because the transfer of house staff and seriously ill patients occurs primarily among large, university-affiliated, tertiary referral hospitals, interhospital spread appears to occur most frequently in these facilities and less commonly among smaller community hospitals [98,113]; in fact, almost two-thirds of CDC outbreak investigations during 1990–1999 involved inpatients in acute care hospitals [113]. However, the blurring of the interface between the acute care hospital, free-standing specialty units, LTCFs, and home care and the increasing trend of “floating” nurses and technicians, “moonlighting” physicians, and various other ancillary medical personnel toward working for healthcare systems whose business model includes all of these facilities in one region undoubtedly increase interfacility spread or transfer of HAI pathogens among patients or residents in any of these facilities.
It used to be perceived not infrequently that interhospital transmission of HAI pathogens occurred mainly in epidemics involving one of the many pathogens with antimicrobial-resistant profiles. This is certainly true for various resistant pathogens (e.g., multiresistant Serratia spp., Enterobacteriaceae resistant to aminoglycosides and third-generation cephalosporins, VRE, MRSA, multidrug-resistant M. tuberculosis, and extended spectrum beta–lactamase producing K. pneumoniae) through genetic colinkage of intrinsic antimicrobial resistance properties with factors that facilitate spread, such as the sharing of genetic information that confers resistance to important antimicrobial agents. Similarly, the diversity of strain types involved in epidemiologically clear outbreaks of MRSA or VRE infections suggests the spread of genetic information among different strains that have strong predispositions for causing infections in hospital patients. Alternatively, the association could be due merely to the fact that resistance provides a dramatic marker that increases the likelihood that an epidemic will be recognized and investigated. If so, as IC personnel in hospitals initiate surveillance activities and develop more sensitive means for recognizing outbreaks and clusters of infections and more effectively share surveillance data with their counterparts in other local hospitals (e.g., through areawide surveillance systems supported by local health departments), interhospital transmission of infection will likely be more readily recognized and
P.499
controlled. The main drawback is the uncharacterized confounding variables of LTCFs and home care.
In the second type of multiple-hospital involvement, a widely distributed product used in patient care may cause infections in many hospitals simultaneously because of either intrinsic contamination of the product in the factory (e.g., hemolysis in hemodialysis patients traced to faulty blood tubing sets or intrinsic contamination of peritoneal dialysis solution [162]) or design flaws or common usage errors that encourage in-use contamination in the hospitals [36,163]. In-use contamination is a far more common explanation for infections related to newly introduced products and devices [98,113]. Although intrinsic contamination is still recognized, extrinsic contamination of products during manipulation is much more common [98,113].
In the 1980s, the widespread use of an unlicensed intravenous vitamin E preparation in neonates led to a nationwide problem of unusual illness with high fatality in these patients [105]. The recognition of this new syndrome in several neonatal ICUs in some states led to the identification of the source and U.S. Food and Drug Administration (FDA) recall of the product. Similarly, an outbreak of BSIs or SSIs in five states led to the identification of a newly introduced intravenous anesthetic as the source [110,111]. Although only one species of organism was involved in each outbreak, different institutions had different pathogens, including S. aureus, Enterobacter spp., Moraxella species, and C. albicans. On-site epidemiologic investigations at each hospital identified contamination of the product during preparation by anesthesia personnel. This led the FDA and the manufacturer to alert users of this product of the need for strict aseptic handling during preparation. The outbreaks of BSIs in home infusion therapy patients demonstrate that as a new approach to patient care (i.e., home infusion) evolves, it is essential that the introduction of new techniques, such as needleless devices to reduce HCW blood contacts, be evaluated for their risk of patient complications [36,120]. Furthermore, such studies may document the need for new infection control recommendations (e.g., more frequent end cap changes) [36,120]. These experiences highlight the fact that IC personnel should remain alert to the possibility of infections or toxic reactions associated with newly introduced products or procedures. Suspicion of such problems should immediately be reported through the state health department to the CDC and FDA.
Pseudoepidemics
Not all clusters of reported HAIs constitute true epidemics of disease. HAI pseudo-outbreaks occur when there are an increased number of positive tests in the laboratory that do not correlate with clinical findings, a change in the surveillance system, or an improvement in laboratory methods [164,165]. Weinstein defined pseudo-outbreaks as a real clustering of false infections or artifactual clustering of real infections [166]. Of 181 HAI outbreaks investigated by CDC during 1956 through 1975, 20 (11%) were pseudo-outbreaks [167]. Approximately one-half of these were attributed to processing errors in the microbiology laboratory. The remaining pseudo-epidemics were traced to systematic errors or changes in the definition of infection that resulted in clinical misdiagnosis of infection or surveillance artifacts associated with reporting of infection.
From 1980 to 1990, 6.0% of outbreaks investigated by CDC were pseudo-epidemics. Of these, 75.0% were traced to contaminated products, 12.5% were traced to environmental contamination, and 12.5% were traced to contamination of the culture during laboratory processing. From 1990 through 1994, only one (1.5%) of the epidemics investigated was a pseudo-epidemic; this involved Mycobacterium abscessus contamination of bronchoscopes traced to a contaminated endoscope washer reservoir [152]. In a more recent review of CDC pseudo-outbreak investigations, Manangan and Jarvis reported that of 104 HAI outbreaks that CDC personnel investigated onsite during 1990–2000, 11 (11%) were pseudo-outbreaks of infections involving Mycobacterium abscessus, Tsukamurella paurometabolum, E. cloacae, P cepacia, Enterococcus durans, or Mycobacterium gordonae [165]. Among the 20 pseudo-outbreaks that occurred during 1956 to 1975 and reviewed by Weinstein and Stamm, the most common sites of suspected infection were the blood (20%), respiratory tract (20%) or gastrointestinal tract (20%), tissues (15%), liver (10%), or central nervous system (5%) [166]. Of the 66 pseudo-outbreaks reviewed by Cunha and Klein during 1976 to 1989, the most common sites of suspected infection were blood (53%), respiratory tract (20%), central nervous system (11%), or tissues (4%) [167]. Manangan and Jarvis found that during 1990 to 2000, the most common sites associated with the 86 pseudo-outbreaks they reviewed were the respiratory tract (37%), multiple sites or sterile fluids (24%), or blood (23%) [165]. In the United States, pseudo-outbreaks of respiratory tract infections now exceed pseudo-outbreaks of BSIs [165].
The two most common causes of HAI pseudo-outbreaks of BSIs are either intrinsic or extrinsic contamination of specimens and faulty procedures or misinterpretation of laboratory tests [165]. Cunha and Klein found that the most common microorganisms associated with pseudo-BSIs were Bacillus spp., Pseudomonas spp., or Streptococcus spp. [167]. Maki described four scenarios when a pseudo-outbreak of BSIs should be suspected: (1) when there is a cluster of blood cultures that are positive for new or unusual pathogens, (2) when affected patients do not consistently show signs or symptoms consistent with a BSI, (3) when the putative epidemic BSIs are primary (i.e., not isolated from likely sites of local infection), and (4) when the BSI is inexplicably high grade [168].
The most common causes of pseudo-outbreaks of respiratory tract infections have been contaminated equipment and use of automated reprocessing systems for endoscopes
P.500
or bronchoscopes [167]. In several of these pseudo-outbreaks, the underlying cause included user error, washer malfunction, or contamination of the reservoir or lens [165]. Manangan and Jarvis suggested that users of these devices should carefully read the manufacturers' recommendations for use and for disinfection of these machines. In addition, CDC has published guidelines for cleaning, disinfecting, and inspecting these devices and for monitoring unusual clusters of organisms [169].
All nine reported pseudo-outbreaks of infections in tissues during 1990 through 2000 occurred in North America. Five of them involved contamination of specimen transport media, specimen tubes, or solutions used for processing the specimens; two involved tuberculin skin testing with purified protein derivative (PPD): one linked to manufacturer's error and the other caused by an incorrect dose of PPD [165].
Most of the 21 pseudo-outbreaks of infection at multiple sites or sterile body fluids reported during 1990 to 2000 involved contamination of blood or cerebrospinal fluid with wide range of microorganisms. Seven were caused by contamination of specimen during collection, transport, or processing; five were associated with malfunctioning of hardware or software in the laboratory [165].
Generally, pseudo-epidemics are associated with systematic errors, changes in the definition of infection used for surveillance, misdiagnosis of infection, and inaccuracy in the reporting of infection by infection surveillance staff. In addition, many can be traced to contaminated equipment or their processing and cleaning solutions; contamination of microbiology specimens during specimen collection, transport, or processing; and other errors in the microbiology laboratory which could be accidental, associated with glitches in newly introduced computer software and hardware, or linked to quality control problems in antimicrobial susceptibility testing. Because of the added costs (human and financial) and anxiety involved with investigating pseudo-epidemics, it is imperative that ICPs and hospital epidemiologists be familiar with the ascertainment, investigation, control, and prevention of pseudo-epidemics and to be aware that they may be due to diagnostic and reporting errors, contaminated equipment, or errors in the microbiology laboratory as reflected in the CDC investigations.
Consequences of HAIs
The reader of the scientific literature on HAIs is struck by the disproportionately vast number of articles on the adverse consequences associated with these infections. They include protracted duration of hospital stay, extra hospital costs or charges, additional inpatient care requirements, costly alternative antimicrobials, potential costs, lost productivity, long-term sequelae, untreatable infections, and death. The blurring of the borders between the acute hospital setting, LTCFs, and homecare has rendered the problem and its solutions even more complex. The importance of these studies stems from two factors: first, in contrast to most other healthcare provision services, hospitals have not traditionally been able to charge patients or their insurance carriers directly for the costs of HAI surveillance and control programs. Second, it has been difficult to demonstrate how many HAIs these programs prevent and the cost effectiveness of these programs. Consequently, it has been necessary, or at least very helpful, in many hospitals to estimate the magnitude of adverse effects of HAIs on patients to justify the expenditures of mounting and sustaining a preventive program. The adverse outcomes most often studied are deaths and costs attributable to infection.
Although CDC data confirm that incidence rates of HAIs involving the four major anatomic sites are decreasing in hospitals across the United States, the looming downside is the concomitant increase in the incidence rates of HAIs occurring in LTCFs and homecare and in the rates of infections associated with antimicrobial-resistant pathogens. Nationwide estimates of the number of deaths attributable to HAIs have been increasing over the past three decades up from 19,000 reported in the 1970s (unpublished CDC data) to at least 90,000 deaths annually at the onset of the new millennium [3]. In view of the new strategies of prospective reimbursement for hospital care, the unequivocal evidence for the efficacy of infection surveillance and control programs, and the increasing body of evidence in the medical literature that the cost of implementing HAI surveillance and infection control programs for problem pathogens is substantially offset by savings involved in the reductions of HAIs, healthcare administrations seem loathe to commit fully—both philosophically and financially—to the idea of a total preventive package involving screening and surveillance of HAI pathogens. Home care is now the fastest growing component of healthcare: approximately 34 million people currently receive home care, supported by an increasing outlay of financial resources ($2 billion in 1988 versus $20 billion in 1999) by the Center for Medicare and Medicaid Services. With increasing movement and dynamic interaction of patients and HCWs between home care, LTCFs, outpatient services, and the acute hospital setting, and the fact that few home healthcare companies have designated surveillance personnel, any significant or realistic reduction in HAI rates in the United States is not going to be achieved anytime soon unless there is a concerted effort by healthcare companies and administrators in hospitals, LTCFs, and home care to completely finance evidence-based preventive measures such as those recommended by the Society of Healthcare Epidemiology of American (SHEA), the Association of Professionals in Infection Control (APIC), and CDC [170].
Control and Prevention of HAIs
That endemic and epidemic HAIs are preventable has periodically been reaffirmed by milestone reports dating
P.501
back to Semmelweis; to the myriad of studies published over the past two decades dealing with the unequivocal effect of hand hygiene, proper care of urinary catheters, respirators, intravascular catheters, and surgical wounds; numerous evidence-based IC guidelines published by CDC; and position papers issued by SHEA, APIC, and the Infectious Diseases Society of America.
Although overall HAI rates at the main anatomic sites have been falling, infections caused by resistant pathogens have been increasing. Thus, control of antimicrobial-resistance in the 2000s remains inextricably linked to the control of transmission of HAI antimicrobial-resistant pathogens and the infections they cause. The seriousness of the problem was underscored in a recent editorial by Muto, who made the point that “for as long as CDC has measured the prevalence of hospital-acquired infections caused by multidrug-resistant organisms, it has been increasing” [171].
So, what do we do? Indeed, there is little doubt that we would not be where we are today had more attention been paid to the published evidence-based data regarding which interventions have been effective in controlling the transmission of nosocomial, antimicrobial-resistant pathogens. For example, the Hospital Infection Control Practices Advisory Committee (HICPAC) guidelines to prevent and control vancomycin resistance were published in 1995 [172]. Although implementation of these guidelines following VRE outbreak investigations played no small part in the resolution of these outbreaks, no published outcome studies show how implementation of the HICPAC guidelines might have resulted in HAI rate reduction in facilities across the nation, especially for those HAIs caused by resistant pathogens [132,173].
After decades of discussing control of antimicrobial-resistant HAI pathogens in the medical literature, there is little evidence of control of HAIs caused by resistant pathogens in most healthcare facilities. The myriad of articles published have in effect helped explain this failure because much of the published data on HAIs has been carried out in hospitals that had implemented untried control programs or had substantially ineffective programs. Moreover, despite all of the resources put into surveillance activities for HAIs in facilities across the country, there remains substantial variation in surveillance activities from one medical center to another, inconsistent use of effective control measures (e.g., surveillance cultures not being performed as recommended), or failure of hospitals to use effective measures due to lack of commitment by healthcare companies and administrators alike to initiate and sustain these measures. In addition, there appears to be moderate compliance with goals to optimize antimicrobial use and to detect, report, and control the spread of antimicrobial-resistant pathogens. In 1996, Goldmann et al. found that national guidelines seldom are studied thoroughly by physicians, and, if they are read, rarely are incorporated into everyday practice [174]. They go on to say that “success depends on the hospital leadership—members of the board, the executive administrative staff, and physician opinion leaders—making the campaign against antimicrobial resistance a strategic priority under the aegis of the hospital's overall efforts to improve quality” [174].
Numerous reports presented at the SHEA annual meetings for each of the years 2003–2005 have repeatedly shown control of endemic or epidemic MRSA and/or VRE infections through implementation of the SHEA guidelines with more emphasis on contact precautions and less on standard precautions (25 such reports in the past two SHEA annual meetings). In fact, CDC has not provided any evidence-based data that show standard precautions and passive surveillance have started to control the spread of MRSA and VRE [175].
The tenets of the SHEA guidelines are based on identification and containment of spread through (1) active surveillance cultures to identify the reservoir for spread, (2) routine hand hygiene, (3) barrier precautions for patients known or suspected to be colonized or infected with epidemiologically important antimicrobial-resistant pathogens, such as MRSA or VRE, (4) implementation of an antimicrobial stewardship program, and (5) decolonization or suppression of colonized patients [170]. The importance of active screening cultures was underscored by data presented at the 2003 annual SHEA meeting, which showed that most patients colonized with MRSA at the time of admission to the surgical unit of a Veterans Administration Hospital had no prior evidence of MRSA colonization. These data also suggested that screening cultures may be necessary to identify the majority of MRSA-colonized patients at the time of admission. Other studies have since established that identification of MRSA-colonized patients at admission may enhance implementation of interventions to decrease infection [176]. There is now growing evidence that active surveillance cultures reduce the incidence of MRSA and/or VRE infections and that programs described in the SHEA Guidelines are effective and cost effective [135,175,177].
In conclusion, active surveillance cultures for resistant pathogens in ICUs with isolation of colonized patients is a highly effective strategy for control of HAIs. Isolation purely on the basis of history of previous detection, at least for VRE or MRSA, appears to be of little benefit. Standard precautions and isolation of the occasional patient recognized to be colonized through routine clinical cultures are minimally effective. The onus is now on healthcare professionals and healthcare administrators to invest intelligently in prevention programs, to enhance existing surveillance activities in targeted areas, and to avoid regarding death and morbidity as inevitable. However, hospital epidemiologists and CDC also have a responsibility to evaluate the effectiveness and cost benefit of the programs described in the SHEA Guidelines for gram-positive and gram-negative pathogens and fungi in the acute care hospitals. Enormous challenges
P.502
remain for controlling transmission of HAI pathogens in acute care hospitals and conducting similar evaluations and strategies in LTCFs and the home care setting. These challenges include development of uniform surveillance definitions and protocols and a non-punitive reporting system for HAIs in LTCFs and home care; identification of high-risk infections (e.g., BSI, pneumonia, or SSI) that need to be focused on in these settings; and determination of relevant numerators and denominators for calculating device-specific rates for infections in these settings. These challenges are likely to be tempered by the fact that by focusing on specific, albeit high-risk, infections, the true magnitude of home HAIs will remain unknown for some time to come.
References
P.503
P.504
P.505