Amenazas deliberadas a la seguridad de la información

of key partners. The clinical microbiology labora-tory must be able to rapidly identify MDROs and CDI, information system professionals must develop alerts to monitor and report individual cases and trends suggestive of possible outbreaks, and infec-tion control practiinfec-tioners (also known as infecinfec-tion preventionists) must institute and improve adherence to rigorous hand hygiene, transmission-based precautions, and environmental cleaning aimed at reducing further transmission (Goldmann et al., 1996; Siegel et al., 2006; Dellit et al., 2007; Moody et al., 2012).

The hospital epidemiologist and the antimicrobial stewardship team collaborate closely with the clini-cal microbiology lab. Given a recent increase in the use of rapid diagnostic assays (Bauer et al., 2014), it is possible to both intervene earlier to halt the trans-mission of MDROs and CDI to other patients, and to tailor therapy and limit unnecessary antibiotic exposure. Collaboration with the clinical microbiol-ogy lab is also important for developing local anti-biograms, which can be used to develop guidelines for a rationale for empiric antibiotic prescribing for common clinical conditions. Reductions in unneces-sary antibiotic exposure have been linked to reduced colonization and infection by methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant Enterococcus (VRE), and multidrug-resistant (MDR) Gram-negative bacteria, along with reductions in CDI (Dancer et al., 2013; Davey et al., 2013; Feazel et al., 2014).

16 The Role of the Hospital

Epidemiologist in Supporting Antimicrobial Stewardship

M

S. c

*

Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire, US

*E-mail: [email protected]

In monitoring MDRO and CDI trends, automated surveillance using electronic data has become increas-ingly utilized to improve real-time tracking and cluster detection (Wright et al., 2004; Huang et al., 2010), in addition to its use for identifying specific HAIs (Klompas and Yokoe, 2009; Woeltje et al., 2014). Local development, maintenance, and evolu-tion of these automated tools requires close col-laboration with information systems (IS or IT) specialists. Due to the increasing need to track and publicly report hospital data on multiple HAIs, infection prevention and control teams have a great deal of experience in working closely with IS special-ists to support surveillance activities. This surveil-lance and reporting experience will be increasingly important as antimicrobial stewardship teams are called upon to publicly report antimicrobial usage and resistance data to the US Centers for Disease Control and Prevention (CDC). One expert panel recommended the public reporting both of days of therapy/1000 patient days and numbers of drug-resistant organisms (Morris et al., 2012). This is in line with the data being requested by the CDC’s Antimicrobial Use and Resistance (AUR) module (CDC, 2015), and is in addition to the public report-ing of all CDI cases already mandated in US hospi-tals (CDC, 2016).

Once an increase in MDRO or CDI rates is identi-fied within a given population, the persistence of these HAIs is driven by four factors (Siegel et al., 2006):

1. The availability of vulnerable patients, such as those with a compromised immune system, those who have undergone recent surgery with healing wounds, and those with an indwelling device (i.e., urinary catheter, central venous catheter, endotra-cheal tube).

2. Overall antimicrobial use in the affected health-care setting (selective pressure).

3. Number of patients either colonized or infected with a given pathogen in the affected healthcare set-ting (colonization pressure).

4. Adherence to infection prevention and control policies.

Hospital epidemiologists and infection control practitioners are involved in the implementation of prevention bundles targeting reductions in specific HAIs, such as central line-associated bloodstream infections, catheter-associated urinary tract infections, ventilator-associated infections, and surgical site infections (Yokoe et al., 2014). As interventions by infection prevention and control teams reduce the

number of device-related and procedure-related infec-tions, the number of MDROs in a given healthcare setting declines (Moody et al., 2012). This reduction in the prevalence of MDROs then leads to declines in empiric broad-spectrum antimicrobial use and reduction in the incidence of CDI (Siegel et al., 2006).

Antibiotic prescribing on a hospital ward impacts CDI risk, even in those patients not receiving anti-biotics (Brown et al., 2015). Similar causal links have been discussed between ward-level antimicrobial use and the overall prevalence of antimicrobial resistance (Dellit et al., 2007). This is part of the reason for current policies promoting universal skin decoloni-zation with chlorhexidine bathing in intensive care unit (ICU) settings. Such policies have shown reduc-tions in the acquisition of MDROs (Climo et al., 2013; Huang et al., 2013).

Adherence to rigorous hand hygiene, transmission-based precautions, and environmental cleaning are also necessary to prevent the further transmission of MDROs and CDI within healthcare settings.

Improvements in hand hygiene driven by education, feedback, and reminders have been shown to signifi-cantly reduce the prevalence of HAIs (Kirkland et al., 2012; Schweizer et al., 2014). In addition, transmis-sion-based precautions are recommended to help prevent the spread of MDROs and CDI between patients within a healthcare facility (Siegel et al., 2006, 2007). Finally, hospital surfaces have been shown to be involved in patient-to-patient transmis-sion and have thus become a focus in efforts to halt the spread of MDROs and CDI. Patients admitted to a room where the prior room occupant had MRSA, VRE, and MDR Gram-negative bacteria, or C. dif-ficile are at an increased risk of infection with the same organism (Weber et al., 2013). However, ade-quate cleaning of the environment and equipment in a room can remove the higher risk of infection in the next room occupant (Datta et al., 2011).

Environmental services staff should have the appro-priate education, written room-cleaning guidelines, checklists, and periodic observations to ensure good practice (Carling et al., 2006; Weber et al., 2013).

Conclusion

Working together, a healthcare facility’s antimicro-bial stewardship and infection prevention and control teams can jointly improve patient outcomes through a reduction in MDRO and CDI prevalence and transmission. Antimicrobial stewardship efforts target the selective pressure driving the emergence

of MDROs and CDI (McGowan, 2012; Nowak et al., 2012), but interventions under the direction of a hospital epidemiologist are necessary to con-trol the secondary spread of these infections once they occur, while simultaneously instituting best-practice bundles aimed at prevention.

References

Bauer, K.A., Perez, K.K., Forrest, G.N., and Goff, D.A.

(2014) Review of rapid diagnostic tests used by antimi-crobial stewardship programs. Clinical Infectious Diseases 59(Suppl 3), S134–S145.

Brown, K., Valenta, K., Fisman, D., Simor, A., and Daneman, N. (2015) Hospital ward prescribing and the risks of Clostridium difficile infection. JAMA Internal Medicine 175, 626–633.

Carling, P.C., Briggs, J.L., Perkins, J., and Highlander, D.

(2006) Improved cleaning of patient rooms using a new targeting method. Clinical Infectious Diseases 42, 385–388.

CDC (2015) Updated Operational Guidance for Acute Care Hospitals for 2015. Operational Guidance for Acute Care Hospitals to Report Facility-Wide Inpatient (FacWideIN) Clostridium difficile Infection (CDI) Laboratory-Identified (LabID) Event Data to CDC’s NHSN for the Purpose of Fulfilling CMS’s Hospital Inpatient Quality Reporting (IQR) Requirements.

Centers for Disease Control and Prevention, Atlanta, Georgia. Available at: http://www.cdc.gov/nhsn/PDFs/

mrsa-cdi/FINAL-ACH-CDI-Guidance.pdf (accessed 27 April 2015).

CDC (2016) Surveillance for Antimicrobial Use and Antimicrobial Resistance Options. Resources for NHSN Users Already Enrolled. National Healthcare Safety Network, Centers for Disease Control and Prevention, Atlanta, Georgia. Available at: http://www.

cdc.gov/nhsn/acute-care-hospital/aur/ (accessed 16 May 2016).

Climo, M.W., Yokoe, D.S., Warren, D.K., Perl, T.M., Bolon, M., Herwaldt, L.A., Weinstein, R.A., Sepkowitz, K.A., Jernigan, J.A., Sanogo, K., and Wong, E.S. (2013) Effect of daily chlorhexidine bathing on hospital-acquired infection. The New England Journal of Medicine 368, 533–542.

Dancer, S.J., Kirkpatrick, P., Corcoran, D.S., Christison, F., Farmer, D., and Robertson, C. (2013) Approaching zero: temporal effects of a restrictive antibiotic policy on hospital-acquired Clostridium difficile, extended-spec-trum β-lactamase-producing coliforms and methicillin-resistant Staphylococcus aureus. International Journal of Antimicrobial Agents 41, 137–142.

Datta, R., Platt, R., Yokoe, D.S., and Huang, S.S. (2011) Environmental cleaning intervention and risk of acquiring multidrug-resistant organisms from prior room occupants.

Archives of Internal Medicine 171, 491–494.

Davey, P., Brown, E., Charani, E., Fenelon, L., Gould, I.M., Holmes, A., Ramsay, C.R., Wiffen, P.J., and Wilcox, M. (2013) Interventions to improve antibiotic prescribing practices for hospital inpatients. Cochrane Database of Systematic Reviews 4: CD003543.

Dellit, T.H., Owens, R.C., McGowan, J.E., Jr., Gerding, D.N., Weinstein, R.A., Burke, J.P., Huskins, W.C., Paterson, D.L., Fishman, N.O., Carpenter, C.F. et al.

(2007) Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America Guidelines for developing an institutional program to enhance antimicrobial stewardship. Clinical Infectious Diseases 44, 159–177.

Feazel, L.M., Malhotra, A., Perencevich, E.N., Kaboli, P., Diekema, D.J., and Schweizer, M.L. (2014) Effect of antibiotic stewardship programmes on Clostridium difficile incidence: a systematic review and meta-analysis. Journal of Antimicrobial Chemotherapy 69, 1748–1754.

Goldmann, D.A., Weinstein, R.A., Wenzel, R.P., Tablan, O.C., Duma, R.J., Gaynes, R.P., Schlosser, J., and Martone, W.J. (1996) Strategies to prevent and control the emergence and spread of antimicrobial-resistant microorganisms in hospitals. A challenge to hospital leadership. JAMA (The Journal of the American Medical Association) 275, 234–240.

Huang, S.S., Yokoe, D.S., Stelling, J., Placzek, H., Kulldorff, M., Kleinman, K., O’Brien, T.F., Calderwood, M.S., Vostok, J., Dunn, J., and Platt, R. (2010) Automated detection of infectious disease outbreaks in hospitals:

a retrospective cohort study. PLoS Medicine 7(2):

e1000238.

Huang, S.S., Septimus, E., Kleinman, K., Moody, J., Hickok, J., Avery, T.R., Lankiewicz, J., Gombosev, A., Terpstra, L., Hartford, F. et al. (2013) Targeted versus universal decolonization to prevent ICU infection. The New England Journal of Medicine 368, 2255–2265.

Kirkland, K.B., Homa, K.A., Lasky, R.A., Ptak, J.A., Taylor, E.A., and Splaine, M.E. (2012) Impact of a hospital-wide hand hygiene initiative on healthcare-associated infections: results of an interrupted time series. BMJ Quality and Safety 21, 1019–1026.

Klompas, M. and Yokoe, D.S. (2009) Automated surveil-lance of healthcare-associated infections. Clinical Infectious Diseases 48, 1268–1275.

McGowan, J.E., Jr. (2012) Antimicrobial stewardship—

the state of the art in 2011: focus on outcome and methods. Infection Control and Hospital Epidemiology 33, 331–337.

Moody, J., Cosgrove, S.E., Olmsted, R., Septimus, E., Aureden, K., Oriola, S., Patel, G.W., and Trivedi, K.K.

(2012) Antimicrobial stewardship: a collaborative part-nership between infection preventionists and health care epidemiologists. American Journal of Infection Control 40, 94–95.

Morris, A.M., Brener, S., Dresser, L., Daneman, N., Dellit, T.H., Avdic, E., and Bell, C.M. (2012) Use of a structured

panel process to define quality metrics for antimicrobial stewardship programs. Infection Control and Hospital Epidemiology 33, 500–506.

Nowak, M.A., Nelson, R.E., Breidenbach, J.L., Thompson, P.A., and Carson, P.J. (2012) Clinical and economic out-comes of a prospective antimicrobial stewardship pro-gram. American Journal of Health-System Pharmacy 69, 1500–1508.

Roberts, R.R., Scott, R.D., II, Hota, B., Kampe, L.M., Abbasi, F., Schabowski, S., Ahmad, I., Ciavarella, G.G., Cordell, R., Solomon, S.L. et al. (2010) Costs attributa-ble to healthcare-associated infection in hospitalized adults and a comparison of economic methods. Medical Care 48, 1026–1035.

Schweizer, M.L., Reisinger, H.S., Ohl, M., Formanek, M.B., Blevins, A., Ward, M.A., and Perencevich, E.N. (2014) Searching for an optimal hand hygiene bundle: a meta-analysis. Clinical Infectious Diseases 58, 248–259.

Siegel, J.D., Rhinehart, E., Jackson, M., Chiarello, L., and HICPAC (Healthcare Infection Control Practices Advisory Committee) (2006) Management of Multidrug-Resistant Organisms in Healthcare Settings, 2006.

Centers for Disease Control and Prevention, Atlanta, Georgia. Available at: http://www.cdc.gov/hicpac/pdf/

MDRO/MDROGuideline2006.pdf (accessed 27 April 2015).

Siegel, J.D., Rhinehart, E., Jackson, M., Chiarello, L., and HICPAC (Healthcare Infection Control Practices Advisory Committee) (2007) 2007 Guideline for Isolation Precautions: Preventing Transmission of Infectious Agents in Healthcare Settings. Available at:

http://www.cdc.gov/hicpac/pdf/isolation/isolation2007.

pdf (accessed 27 April 2015).

Weber, D.J., Anderson, D., and Rutala, W.A. (2013) The role of the environment in healthcare-associated infections.

Current Opinion in Infectious Diseases 26, 338–344.

Woeltje, K.F., Lin, M.Y., Klompas, M., Wright, M.O., Zuccotti, G., and Trick, W.E. (2014) Data requirements for electronic surveillance of healthcare-associated infections. Clinical Infectious Diseases 35, 1083–1091.

Wright, M.O., Perencevich, E.N., Novak, C., Hebden, J.N., Standiford, H.C., and Harris, A.D. (2004) Preliminary assessment of an automated surveil-lance system for infection control. Infection Control and Hospital Epidemiology 25, 325–332.

Yokoe, D.S., Anderson, D.J., Berenholtz, S.M., Calfee, D.P., Dubberke, E.R., Ellingson, K.D., Gerding, D.N., Haas, J.P., Kaye, K.S., Klompas, M. et al. (2014) A com-pendium of strategies to prevent healthcare-associated infections in acute care hospitals: 2014 updates.

Infection Control and Hospital Epidemiology 35, 967–977.

Introduction

The use of antimicrobial therapy presents infectious diseases clinicians with an increasing number of chal-lenges. In particular, the rapid development of multidrug-resistant organisms (MDROs) is over-whelming the spectra of available antibiotics, and new agents are needed. Despite this paucity of anti-biotics, regulatory, financial and technical issues have hindered the development of novel antimicro-bial agents. Dose optimization through the applica-tion of pharmacokinetic/pharmacodynamic (PK/PD) principles is a pivotal strategy for maintaining the efficacy and utility of the current antibiotic arma-mentarium. In this chapter, we review PK/PD con-cepts and provide examples of how these concon-cepts can be used to modify and optimize antimicrobial drug regimens in the clinical setting.

Pharmacokinetics and Pharmacodynamics

Pharmacokinetics (PK) describes the influences exerted on a drug by the body from its administra-tion to its removal: namely absorpadministra-tion, distribu-tion, metabolism, and excretion. As a result of the path of an antibiotic through the body, the concen-trations of that antibiotic take on a specific profile in the blood and tissues after administration. This profile is a result of the pharmacokinetic parame-ters that allow the characterization of a drug’s PK profile. Common pharmacokinetic parameters

utilized to describe the PK profile of an antibiotic include the maximum concentration achieved after a dose (Cmax), the minimum concentration achieved after a dose (Cmin), the area under the concentration vs. time curve (AUC), and the antibi-otic clearance (CL) or half-life (t_1/2), which are used to estimate the exposure profile of the compound.

Also of importance is the protein binding capacity of an antibiotic, because only free drug concentra-tions are responsible for microbiological activity.

As such, the above pharmacokinetic parameters are often corrected for the fraction of the drug that is unbound and noted by ‘f’ in front (e.g., fAUC, fCmax) (Levison, 2004). Notably, several physio-logic and disease-specific variables can affect anti-biotic PK parameters and thus increase or decrease drug exposure. Aspects of PK in special popula-tions will be discussed briefly later in this chapter.

Pharmacodynamics (PD) describes the effect of the drug on the bacteria. Of note, infectious dis-eases is the only field where the drug target is not specifically the human host but another living organism residing within the host and causing the infection. As a result, the pharmacokinetic param-eters described above are linked to a surrogate measure of activity, which is typically described as the minimum inhibitory concentration (MIC) of the antibiotic. The MIC is the lowest concentration of antibiotic that inhibits visible growth in vitro.

The lower the MIC, the greater potency the antibi-otic has against the organism; vice versa, more resistant organisms have higher antibiotic MICs,

17 Principles of Pharmacokinetic/

Pharmacodynamic Optimization