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Preventing healthcare-associated infections: the role of surveillance NS779 Mitchell BG, Russo PL (2015) Preventing healthcare-associated infections: the role of surveillance. Nursing Standard. 29, 23, 52-58. Date of submission: September 14 2014; date of acceptance: November 12 2014.

Aims and intended learning outcomes

Abstract Surveillance of healthcare-associated infections is central to healthcare epidemiology and infection control programmes and a critical factor in the prevention of these infections. By definition, the term ‘infection prevention’ implies that healthcare-associated infections may be preventable. The purpose of surveillance is to provide quality data that can be used in an effective monitoring and alert system and to reduce the incidence of preventable healthcare-associated infections. This article examines the purpose of surveillance, explains key epidemiological terms, provides an overview of approaches to surveillance and discusses the importance of validation.

Authors Brett G Mitchell Associate professor of nursing, Avondale College for Higher Education, Wahroonga, Australia, and honorary research fellow, Australian Catholic University, Dickson, Australia. Philip L Russo PhD scholar, Institute of Health and Biomedical Innovation, School of Public Health and Social Work, Queensland University of Technology, Brisbane, Australia, and adjunct senior lecturer, Griffith University, Brisbane, Australia. Correspondence to: [email protected]

Keywords Epidemiology, healthcare-associated infections, infection control, infection prevention, public health, surveillance

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This article aims to help nurses understand the purpose of surveillance in infection prevention and control, and to understand key epidemiological terms. Readers will gain an awareness of the different approaches to surveillance, their limitations and their advantages. After reading this article and completing the time out activities you should be able to: Describe the purpose of surveillance. List the key attributes of a surveillance programme. Explain the difference between prevalence and incidence. Discuss different surveillance approaches, describing the advantages and disadvantages of each.

Introduction Surveillance is the ‘systematic and continuous collection, analysis and interpretation of data, closely integrated with the timely and coherent dissemination of the results and assessment to those who have a right to know so that action can take place’ (Porta 2008). Slight variations of this definition are applied to healthcare-associated infection (HCAI) surveillance. The United States Centres for Disease Control and Prevention define surveillance as ‘the ongoing, systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice, closely integrated with the timely dissemination of these data to those who need to know’ (Buettner and Muller 2012).

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Surveillance of HCAIs is central to healthcare epidemiology and infection control programmes, and a critical factor in the prevention of HCAIs (Mitchell and Gardner 2014a). This article examines the purpose of surveillance, explains key epidemiological terms, provides an overview of approaches to surveillance, and discusses the importance of validation – processes used to ensure the data collected are as robust as possible.

Purpose of surveillance By definition, the term ‘infection prevention’ implies that HCAIs are preventable. The purpose of surveillance is to provide quality data that can be used in an effective monitoring and alert system, and to reduce the incidence of preventable HCAIs (Damani 2012, Wilson 2013). Surveillance can be viewed as an information cycle, typically starting with the recognition of an event. The process of surveillance incorporates several stages: collection, validation, analysis, interpretation and dissemination, which results in action being taken (Damani 2012) (Figure 1). Feedback or dissemination of data to the right people, to complete the loop and enable appropriate action, is critical to the success of any surveillance programme (Buehler 2008). Unless the information is provided to those who can implement change when required, the efforts of those involved in surveillance will be wasted. Feedback of data also acts as an incentive for ongoing participation (Buehler 2008). Complete time out activity 1 When establishing a surveillance system, careful consideration must be given when determining the data to be collected. Surveillance systems are designed to provide basic epidemiological descriptive data such as the time, place and person involved in the particular event under observation (Garcia-Abren et al 2002). This basic information enables the event to be monitored over time (Garcia-Abren et al 2002). A common error when establishing surveillance systems is to attempt to collect as much data as possible, even though their immediate purpose may not be clear. Collecting data that are not required wastes scarce resources. The complexity of the data to be collected should balance the information needs and available resources (Garcia-Abren et al 2002).

A successful surveillance programme should be epidemiologically sound and balance attributes such as accuracy, timeliness, usefulness, consistency and practicality (Perl and Chaiwarith 2010). Effective surveillance systems deliver information that can be used to inform decisions. The act of collecting HCAI data will not in itself reduce HCAIs: rather, data must stimulate action (Haley 1995). HCAI surveillance systems establish a baseline rate of infection, which can then be used to detect clusters or outbreaks, identify problems, evaluate prevention and control measures, generate hypotheses concerning risk factors, guide treatment and prevention strategies, allow comparisons between facilities, and reduce the incidence of HCAIs (Reilly et al 2009, Perl and Chaiwarith 2010). No surveillance system is perfect. While a good surveillance system does not guarantee the right decisions will be made, it reduces the chances of making the wrong decisions (Langmuir 1963). Clear benefits of HCAI surveillance programmes were demonstrated by a study undertaken by Haley (1995), who set out to determine whether infection control programmes reduced rates of surgical site, bloodstream, and urinary tract infections and ventilator-associated pneumonia. He evaluated hospital infection control programmes over a ten-year period and reviewed the corresponding HCAI rates. He found that hospitals with intensive HCAI surveillance programmes, including feedback and the presence of a nurse to collect and analyse data, demonstrated the lowest HCAI

1 Are you aware of the infection control data collected for your clinical area, for example on hand hygiene compliance rates? If not, liaise with members of the infection control team to find out what information is available.

FIGURE 1 The surveillance cycle

Data collection

Implement interventions

Data validation and analysis

Calculate rates and disseminate data

(Adapted from Buehler 2008) Adapted from Buehler (2008)

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CPD infection control rates (Haley 1995). Many HCAI surveillance programmes have been established on the basis of this work. There is an important distinction between surveillance and research. Good surveillance will often generate research ideas and hypotheses, but surveillance data are descriptive in nature and rarely provide the detailed information necessary to test a hypothesis. Research, in contrast, is experimental in design and tests hypotheses by comparing and contrasting two groups (Garcia-Abren et al 2002). Complete time out activity 2

Key concepts

2 In your own words, explain the difference between incidence and prevalence. Compare your answers with the information provided in this article. 3 List some different approaches that could be used to undertake HCAI surveillance. Consider what the advantages and disadvantages of each might be. Compare your ideas with the provided examples in Table 1.

Data from surveillance systems can be presented in various ways. Prevalence and incidence are important concepts. Prevalence is the fraction (proportion or percentage) of a group of people having the condition or outcome at a given time. It can be measured by surveying a defined population and counting the number of people with the condition of interest (Fletcher et al 2013). Prevalence studies may occur at a specified time or during a specified period. Counting the number of people with an infection in a hospital on a given day is an example of a point prevalence study. Point prevalence studies are used to examine the prevalence of a condition at a given point, for example the proportion of hospitalised patients with urinary tract infections on a given day (Gardner et al 2014). Data obtained from point prevalence surveillance studies are often used to identify areas that require more intense ongoing surveillance or research. Incidence is the fraction or proportion of a group of people initially free of the condition of interest that develop the condition over a given period of time (Fletcher et al 2013). To estimate incidence, it is necessary to follow the health of individuals to determine who acquires the disease of interest and who does not (Buettner and Muller 2012). An incidence rate is the number of new events (cases) divided by the total event-free person-time of observing the population at risk (Buettner and Muller 2012). For example, all persons who are admitted to hospital may be observed to determine whether they acquire a bloodstream infection. Incidence rates are usually expressed as the number of new cases per 100, 1,000 or 10,000 people per time of observation. As another example, you might want to know the incidence of bloodstream infection in individuals with a long-term central venous

catheter. If you followed up 1,000 people with central venous catheters for two months and found one new case, the incidence rate would be 0.5 cases per 1,000 people per month. This type of surveillance allows events to be monitored over time and can be used to identify outbreaks or measure the effects of infection prevention interventions. Complete time out activity 3

Approaches to surveillance There are several important considerations when designing a surveillance programme: the scope of the programme, the purpose of undertaking the surveillance, and the case definitions (how infections are defined) (Buehler 2008). The scope may be as wide as an entire population, or it may be more targeted – to include an entire hospital or a specific location within a hospital, for example (Allen-Bridson et al 2012). Surveillance approaches can vary considerably and include passive and active surveillance in addition to outcome and process surveillance (Table 1). Passive surveillance generally involves using data already collected by other systems, whereas active surveillance involves collecting data not already captured by other systems. Case definitions are a vital component to a surveillance system. Case definitions should be standardised and applied consistently to ensure accurate measurement of the event (Perl and Chaiwarith 2010). The complexity of the definition should take into consideration the objectives of the surveillance, as well as measures of sensitivity, specificity and feasibility. Consideration should also be given to who will be applying the definitions, their requirements for training, the availability of supporting tests and the interpretation of results. Various methods have been described for undertaking HCAI surveillance (Table 1). These can be broadly categorised into two strategies: hospital-wide surveillance and targeted surveillance (Pottinger et al 1997). Hospital-wide surveillance involves continuous surveillance of all areas of the hospital. While comprehensive, it is resource-intensive and costly. Targeted surveillance, while still requiring substantial resources, is more efficient and may be targeted by objective or priority. Targeted surveillance generally involves targeting high-risk patients or clinical areas for prospective surveillance, at the risk of missing HCAIs that may occur elsewhere (Perl and Chaiwarith 2010).

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The introduction of automated technology and use of electronic data as an aid to traditional HCAI surveillance methods is well established (Freeman et al 2013). Automated systems ensure consistent application of surveillance definitions, significantly reduce the burden of data management associated with traditional methods and provide excellent sensitivity and specificity (Freeman et al 2013). Complete time out activity 4

Importance of validation Surveillance and research enable evaluation of interventions used in infection prevention and control. Reliable surveillance data can also provide useful information for clinicians, policy makers and patients, identifying areas that require improvement and demonstrating the effectiveness of interventions in measures such as a reduced infection rate and subsequent decreases in patient morbidity or mortality (Pronovost et al 2006, Guerin et al 2010). Improving the rigour of surveillance makes it possible to provide valid, reliable information, to design and plan future programmes, and to

provide measures for evaluating interventions (Mitchell and Gardner 2014b). Validation studies of HCAI surveillance are expensive to conduct, have inherent methodological difficulties and tend to focus on one aspect of data collection (Fabry et al 2007). However, increased public reporting, the increased use of healthcare service performance measurements and benchmarking, and the potential for HCAI outcome data to be linked to hospital funding have accelerated discussions about the validity and reliability of HCAI data (Perla et al 2009, Fridkin and Olmsted 2011, Klazinga et al 2011). Measuring the sensitivity and specificity of a surveillance programme is one way to estimate its validity. The sensitivity and specificity of a surveillance programme refer to how effective the programme is at identifying true infections and ruling out non-infections respectively. A surveillance programme with low sensitivity will result in some HCAIs not being detected, leading to an underestimate of the true incidence of infection. A surveillance programme with a low specificity will not identify accurately those without the HCAI being measured.

4 Consider your area of clinical practice: which patients or patient groups are at greatest risk of infection? What factors influence this risk? Could surveillance help identify or alert staff to additional infection risks?

TABLE 1 Healthcare-associated infection surveillance methods Approach

Purpose

Outcome

Measures patient outcomes, for example infections.

 Of most interest to patients, healthcare workers and healthcare providers.  Measures all aspects of care.  Provides an important evaluation of the effect of interventions.

Advantages

 May be influenced by differences in interpreting case definitions and issues outside of healthcare delivery.  Limitations may be difficult to understand.

Disadvantages

Process

Collection of data on infection control practices that affect patient outcomes, for example hand hygiene.

 Easy to interpret.  Direct measure of aspects of care.

 Does not measure patient outcomes.  The processes observed may be associated with beneficial outcomes, but may not be the sole or primary cause.

Laboratorybased

Uses existing data sets and systems. Data are obtained from laboratories and patient information systems.

 Potentially less time-consuming and less labour intensive.  Can be performed for a number of organisms.  Useful for measuring trends over time.

 Not necessarily a clinical diagnosis, only a laboratory result. For example, just because an organism is identified in the laboratory does not mean the patient always has an infection.  Subject to ascertainment bias (sampling bias).  Changes in laboratory practice may influence data.

Targeted

Undertakes surveillance focused on a particular organism or infection. May be local surveillance or facility wide.

 Responsive to the needs of the  Other emerging infections or trends may facility and/or local priorities. be missed if performed in isolation.  Directs resources to a specific priority.  May miss clusters of infections in areas that are not undertaking surveillance.

(Allen-Bridson et al 2012, Damani 2012)

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CPD infection control

5 How do you think your ward or clinical area would compare to the national average in a surveillance programme for HCAIs. Are there any patient or organisational factors that would influence this comparison?

Another frequently used metric is the positive predictive value, defined as the proportion of reported cases that have the HCAI under surveillance. The positive predictive value is influenced by the sensitivity and specificity of the programme, and the prevalence of the HCAI. A low positive predictive value (possibility of many false-positive results) may result in investigations into events that are wrongly thought to be HCAIs, implementation of unnecessary interventions and waste of resources. Emori and colleagues measured the accuracy of reporting intensive care unit (ICU) HCAIs to the US National Nosocomial Infection Surveillance System in 1998. They identified a sensitivity range of 30% to 85% and a positive predictive value range of 72% to 87% for prospectively identified HCAIs (Emori et al 1998). The specificity was over 98% for all HCAIs. The authors’ conclusion was that, when an ICU HCAI is reported, it is likely to be a true HCAI, and patients who do not acquire a HCAI are likely to be identified accurately. However, because of the low sensitivity rates it is likely that some HCAIs were not being identified. The authors recommended further training for data collectors to promote consistent application of infection criteria (Emori et al 1998). Large-scale validation studies of national HCAI programmes are complex to conduct, but attempts have been made to validate large-scale surveillance programmes in Germany (Gastmeier et al 2008), Australia (McBryde et al 2009, Van Gessel et al 2010) and the US (Horan et al 2011). These studies have shown variability in sensitivity, specificity and positive predictive value rates. These findings do not imply that missing HCAIs is common in surveillance programmes, but rather that comparability of data and objective performance measurement is severely limited with such a large range of study designs and validation measurements (Rich et al 2013). Surveillance methods, for example case definitions and data analysis, as well as other factors including individual patient factors such as patient age and comorbidities, may also influence the data. Age can be a risk factor in certain HCAIs, including Staphylococcus aureus bacteraemia (Asgeirsson et al 2011), Clostridium difficile infection (Pépin et al 2005, Mitchell 2014), and catheter-associated urinary tract infection (Payne et al 2012). The ability to control for

patient factors including comorbidities permits assessment of the independent effects of HCAIs and allows for the possibility of risk adjustment (Mitchell and Gardner 2014b).

Developing or assessing surveillance Nurses responsible for establishing a surveillance programme or assessing surveillance may like to consider the five attributes for an effective surveillance programme developed by researchers at the National Healthcare Safety Network in the US (Allen-Bridson et al 2012):  Accuracy – this is aided by the use of case definitions and accurate denominator data – that is, ensuring all those in the population under surveillance are at risk of acquiring the infection. The presence and intensity of post-discharge surveillance will strongly influence the identification of cases (numerator) data.  Timeliness – prospective surveillance is recommended to enable quick identification and prompt investigation. Retrospective surveillance is best suited for issues that have little need of intervention, because of the delay in data analysis.  Usefulness – surveillance resources should be directed only towards actionable issues. Consistency – case definitions must be applied uniformly, surveillance methods and data sources should be consistent and education of those involved in identifying cases should be standardised. Routine cross-checking of case determinations should be performed regularly.  Practicality – surveillance objectives must be achievable within the resources available. Complete time out activity 5 Surveillance is of crucial importance in infection control programmes. However, the reliability and validity of data must be sufficient for healthcare professionals to perceive value in the data presented (Mitchell and Gardner 2014b). If the data are accurate and useful, then professionals are more likely to rely on them when making decisions and to alter their behaviour to reduce the risk of HCAIs (Gaynes et al 2001). An overview of important considerations for those considering establishing a surveillance programme at ward or local level is provided in Box 1. Infection prevention staff spend up to 45% of their time undertaking surveillance (Gaynes

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1997). Identification of cases is dependent on effort. Surveillance methodology often requires manual medical record review of all patients at risk of a HCAI. It may also involve visiting patients, reviewing microbiology results and discussions with ward staff or team meetings (van Mourik et al 2013). Application of definitions is subject to interpretation, which is also time-consuming (van Mourik et al 2013). Efficient data-collection processes remain largely elusive, despite experience gained from national HCAI surveillance programmes. Perl and Chaiwarith (2010) have stated that integration of rapidly developing surveillance technologies is essential to improve the efficiency of surveillance resources. Electronic

BOX 1 Considerations for a surveillance programme at ward or local level  What is the purpose of the surveillance? Will the surveillance you are proposing enable you to answer this?  What is the best approach: outcome or process surveillance?  Are you using standardised definitions, a standardised approach and validated tools?  With the approach you are using, are you able to benchmark yourself internally and externally? Will you be able to benchmark performance over time in the future?  Are you going to calculate an infection rate? If so, how you are going to do this? Is the denominator data subject to change?  Does your proposed data collection require statistical analysis? Do you have access to relevant expertise if needed?

BOX 2 Checklist for comparing healthcare-associated infection data  How was a case defined? Does this have limitations?  How is the infection rate calculated? Is the rate influenced by the denominator used?  Are there patient factors that may explain the discrepancies observed? Examples may include age and comorbidities.  Is the statistical analysis appropriate and comparable?  Is the population measured in the study representative?  Are there organisational factors that may have influenced the data? Examples may include introduction and/or changes in policies or practice, changes in governance, staffing levels and skill mix.

surveillance systems can reduce time spent by up to 65% when compared with traditional surveillance methods, and can also improve sensitivity and specificity (Perl and Chaiwarith 2010). If electronic surveillance systems are to play a bigger role in routine HCAI infection surveillance, then they need to be as good as, and less prone to subjectivity, than existing methods. This is particularly important if HCAI rates between hospitals are to be compared or publicly reported. Inconsistent application of case definitions and case-finding methods will influence the meaning of data and any comparisons made. Box 2 provides a checklist that can be used when attempting to compare HCAI data; either literature or infection incidence between hospitals.

Conclusion An effective infection prevention programme is only possible if it is supported by a well-established, robust, efficient and sustainable HCAI surveillance programme. HCAI surveillance is not a static process. It requires ongoing review and analysis of data. Validity and timeliness need to be kept under scrutiny, and objectives and methods need to be assessed frequently to ensure the programme continues to deliver meaningful information. This article has highlighted the aims and purposes of HCAI surveillance programmes and indicates issues that should be considered when establishing or maintaining a programme. The data should be required to improve practice and the objectives of the programme considered in relation to the resources necessary to implement it. HCAI surveillance systems must be developed on sound epidemiological principles. Objectives should be identified clearly and case definitions should be clear, standardised and feasible. Data collection methods and populations under surveillance should also be identified clearly. The data should be analysed and disseminated to all those who need to know, to complete the surveillance cycle NS Complete time out activity 6 Acknowledgement Philip L Russo wishes to acknowledge the Rosemary Norman Foundation and the Nurses Memorial Centre, Victoria, Australia, for the award of the ‘Babe’ Norman Scholarship to enable his PhD studies.

6 Now that you have completed the article, you might like to write a reflective account. Guidelines to help you are on page 62.

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Preventing healthcare-associated infections: the role of surveillance.

Surveillance of healthcare-associated infections is central to healthcare epidemiology and infection control programmes and a critical factor in the p...
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