Hospital Infection Control

Measuring antibiotic use and resistance

How does the ability to measure antibiotic use and resistance impact infection control?

The Infectious Disease Society of America (IDSA) and Society of Healthcare Epidemiologists (SHEA) have promoted better antimicrobial stewardship as a method for reducing antimicrobial resistance. Antimicrobial stewardship and infection control programs share the common goal of managing antimicrobial resistance in order to improve patient healthcare and outcomes. The ability to measure antimicrobial use and resistance appropriately are crucial pieces of information in evaluating such programs. A number of metrics are available for quantifying use and resistance, and practitioners must use caution to understand the implications of each.

Several epidemiologic studies measuring antimicrobial use and resistance have shown the potential to impact the rates of resistance of important pathogens through improved stewardship. Through benchmarking these measurements among similar settings, areas of overuse or inappropriate use can be identified and resolved.

Measurements of resistance and appropriate construction of antibiograms are also a necessary component for guiding the empirical selection of antibiotic drug therapy.

What elements of measuring antibiotic use and resistance are necessary for infection prevention and control?

Practitioners and researchers must adhere to selection of appropriate and standardized metrics for the question(s) being examined. For example, a clinician asking the question of which empiric therapy to start for a patient, will likely turn to their local antibiogram for consultation of an appropriate antimicrobial agent. Standardized methods for constructing antibiograms have been proposed and published by the Clinical Laboratory Standards Institute (CLSI). If the antibiogram is constructed inappropriately (duplicate isolates are included, colonizing and infective samples are both reported, susceptibility data reported for species with thirty or fewer isolates tested, etc.,) then the information regarding antimicrobial resistance may be biased and thus misleading.

Though antibiograms are a useful metric to a hospital based clinician, selection of this metric may not be a particularly appropriate measure of resistance for a researcher examining changes over time or in response to introduction of a new antimicrobial agent. Antibiograms report the proportion of resistant isolates to a given antimicrobial agent. Changes in antimicrobial use itself can alter the number of susceptible isolates without actually changing the number of resistant isolates. Here a researcher could misinterpret changes in the proportion of resistance as a change in the burden of resistance. Instead, a more useful metric could be the rate of resistance, described as the number of resistant isolates per unit time.

Adhering to the proper selection of a standardized metric for measuring antimicrobial use is equally important. One of the most widely used methods is from the Anatomical Therapeutic Chemical/Defined Daily Dose (ATC/DDD) index published by The World Health Organization Collaborating Center for Drug Statistics Methodology. The definition of the DDD is “assumed average maintenance dose per day for a drug used for its main indication in adults”.

While appropriate for adult populations, the DDD is by definition not well suited for studying antibiotic use in pediatric patients. Instead, days of therapy (DOTs) has been suggested as a suitable metric of antibiotic use and shown to be useful in describing changes in such use over time.

Benchmarking of data requires that the comparators be similar enough to draw meaningful conclusions. This may not always be the case and steps must be taken to risk adjust populations.

What are the consequences of not measuring antibiotic use and resistance?

Several studies have identified deficiencies in adherence to standard methodologies for measuring antibiotic resistance through antibiograms. When measuring antimicrobial resistance, if antibiograms are constructed ignoring CLSI guidelines (e.g., duplicate isolates are included, surveillance isolates are included) then the proportion of resistance reported may actually be inflated. If few isolates of a given species are tested, then the proportion of resistance may not reflect the true level of resistance in the population.

Researchers must fully understand the limitations of the metric being chosen for measuring antimicrobial use. A study by Polk and colleagues highlights several important distinctions between the DDD and DOT metrics. The DDD cannot be used to measure antimicrobial use in pediatric populations. It may underestimate drug use in cases where doses are adjusted for interactions or pharmacokinetic reasons (e.g., renal impairment). It is also limited in that the DDD is subject to revision and therefore one must take care to use the appropriate DDD that matches the time period covered by the data set. The calculation of a DOT leaves it vulnerable to overestimation of drug use in cases where a drug is given several times daily. For example, if one gram of vancomycin was prescribed once daily for a patient with renal impairment, a DDD would calculate this as 0.5 DDDs, but the dose would equate to 1 DOT.

Inter-hospital comparisons for measurements of antimicrobial use and resistance should only be made if they are truly similar. In order for the benchmarking to occur, the data must take into account appropriate risk adjustments. A study by MacDougall and colleagues points out that hospital bed size and teaching status, factors traditionally suggested as appropriate risk adjustors, may not work as well as others.

A non standard method of measuring antibiotic use and resistance presents challenges in evaluating epidemiologic studies against one another.

Ignoring inappropriate use of antibiotics can lead to unnecessarily high rates of resistance in the healthcare setting.

What information supports the conclusions of studies on measuring antibiotic use and resistance?

Several epidemiologic observational studies have conducted examining relationships between antimicrobial use and resistance. From these, there are data to suggest that the amount of use, and potentially misuse, of antimicrobials is associated with levels of resistance. Furthermore, a study by Fridkin and colleagues suggests that improvement in antimicrobial stewardship can be associated with improved levels of resistant organisms.

Summary of current controversies regarding the measurement of antibiotic use and resistance.

Which measure is more appropriate, days of therapy (DOT) versus defined daily dose (DDD)?

What is the best measure of antimicrobial resistance, a true rate versus a proportion of resistant isolates?

What are the appropriate risk adjustments for benchmarking data between institutions?

How to use the data to perform future studies?

What type of antimicrobial stewardship strategies work?

What is the impact of measuring antibiotic use and resistance relative to the impact of other aspects of infection control?

Antimicrobial use is only one of several important factors influencing resistance. In a time-series analysis study examining the incidence of MRSA, Aldeyab and colleagues were able to ascribe 78% of resistance variability over time through use of antimicrobials and other infection control practices. The role of modifying the use of antimicrobials and implementation of infection control policies share the common goal of managing resistance.

What national and international guidelines exist related to the measurement of antibiotic use and resistance?

SHEA and IDSA have published guidelines for developing antimicrobial stewardship programs and for prevention of antimicrobial resistance in healthcare settings.

The WHO publishes and index of DDDs, which is based upon the average daily maintenance dose for typical use in an adult patient.

The CLSI publishes a document, M39-A3, which describes the standard methodology for developing antibiograms.

What other consensus group statements exist and what do key leaders advise?

A joint venture between SHEA and the Healthcare Infection Control Practices Advisory Committee (HICPAC) to describe standardized methods for monitoring multidrug resistant organisms (MDRO) were recently released as a position paper. In it, key leaders advise that infection control practitioners evaluate the proposed metrics to identify those which best suit their facilities and available data. Using the standardized measurements will provide a consistent means of detecting changes in these MDROs within their facilities. The authors also caution, as in other studies of benchmarking, that these metrics should not be used for interfacility comparisons without means for proper risk adjustment.

References

Shlaes, D, Gerding, D, John, J. "Society for Healthcare Epidemiology of America and Infectious Diseases Society of America Joint Committee on the prevention of Antimicrobial Resistance: Guidelines for the Prevention of Antimicrobial Resistance in Hospitals". Clin Infect Dis. vol. 25. 1997. pp. 584-95.

Dellit, T, Owens, R, McGowan, J. "Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America Guidelines for Developing an Institutional Program to Enhance Antimicrobial Stewardship". Clin Infect Dis. vol. 44. 2007. pp. 159-77.

"Clinical and Laboratory Standards Institute (CLSI). Analysis and presentation of cumulative antimicrobial susceptibility test data: approved guideline-Third Edition". vol. Vol. 29. 2009. pp. M39-A3.

Schwaber, MJ, De-Medina, T, Carmeli, Y. "Epidemiologic Interpretation of Antibiotic Resistance Studies-What are we missing?". Nat Rev Microbiol. vol. 2. 2004. pp. 979-83.

"World Health Organization (WHO). Collaborating Centre for Drug Statistics methodology: ATC index with DDDs". Oslo, Norway: WHO. 2011.

Pakyz, AL, Gurgle, HE, Ibrahim, OM. "Trends in Antibiotic Use in Hospitalized Pediatric Patients in United States Academic Health Centers". Infect Control Hosp Epidemiol. vol. 30. 2009. pp. 600-603.

MacDougall, C, Polk, RE. "Variability in Rates of Use of Antibacterials Among 130 US Hospitals and Risk-Adjustment Models for Interhospital Comparison". Infect Control Hosp Epidemiol. vol. 29. 2008. pp. 203-211.

Pakyz, AL, Powell, JP, Harpe, SE. "Diversity of Antimicrobial Use and Resistance in 42 Hospitals in the United States". Pharmacotherapy. vol. 28. 2008. pp. 906-912.

MacDougall, C, Powell, JP, Johnson, CK. "Hospital and Community Fluoroquinolone Use and Resistance in Staphylococcus aureus and Escherichia coli in 17 US Hospitals". Clin Infect Dis. vol. 41. 2005. pp. 435-40.

MacDougall, C, Harpe, SE, Powell, JP. "Pseudomonas aeruginosa, Staphylococcus aureus, and Fluoroquinolone Use". Emerg Infect Dis. vol. 11. 2005 Aug. pp. 1197-204.

Fridkin, SK, Lawton, R, Edwards, JR. "Monitoring Antimicrobial Use and Resistance: Comparison with a National Benchmark on Reducing Vancomycin Use and Vancomycin-Resistant Enterococci". Emerg Infect Dis. vol. 8. 2002. pp. 702-7.

Zapantis, A, Lacy, MK, Horvat, RT. "Nationwide Antibiogram Analysis Using NCCLS M39-A guidelines". J Clin Microbiol. vol. 43. 2005. pp. 2629-34.

Pakyz, AL. "The Utility of Hospital Antibiograms as Tools for Guiding Empiric Therapy and Tracking Resistance". Pharmacotherapy. vol. 27. 2007. pp. 1306-12.

Polk, RE, Fox, C, Mahoney, A. "Measurement of Adult Antibacterial Drug Use in 130 US Hospitals: Comparison of Defined Daily Dose and Days of Therapy". Clin Infect Dis. vol. 44. 2007. pp. 644-70.

Aldeyab, MA, Monnet, DL, Lopez-Lozano, JM. "Modelling the impact of antibiotic use and infection control practices on the incidence of hospital-acquire methicillin-resistant Staphylococcus aureus: a time-series analysis". J Antimicrob Chemother. vol. 62. 2008 Sep. pp. 593-600.

Cohen, AL, Calfee, D, Fridkin, SK. "Recommendations for Metrics for Multidrug-Resistant Organisms in Healthcare Settings: SHEA/HICPAC Position Paper". Infect Control Hosp Epidemiol. vol. 29. 2008. pp. 901-13.

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