|Year : 2010 | Volume
| Issue : 4 | Page : 277-280
Hospital antibiogram: A necessity
Department of Microbiology, Manipal Hospital, 98 Rustom Bagh, HAL Airport Road, Bangalore - 560 017, India
|Date of Submission||26-Aug-2010|
|Date of Acceptance||26-Aug-2010|
|Date of Web Publication||20-Oct-2010|
Department of Microbiology, Manipal Hospital, 98 Rustom Bagh, HAL Airport Road, Bangalore - 560 017
Source of Support: None, Conflict of Interest: None
The hospital antibiogram is a periodic summary of antimicrobial susceptibilities of local bacterial isolates submitted to the hospital's clinical microbiology laboratory. Antibiograms are often used by clinicians to assess local susceptibility rates, as an aid in selecting empiric antibiotic therapy, and in monitoring resistance trends over time within an institution. Antibiograms can also used to compare susceptibility rates across institutions and track resistance trends. Some hospitals have adequate support from the computer department to be able to extract data from their reporting module. The WHONET software can be freely downloaded and used for analysis. Consensus guidelines have been developed by the Clinical and Laboratory Standards Institute (CLSI) to standardise methods used in constructing antibiograms. These guidelines can be incorporated into the WHONET software for analysis. Only the first isolate from the patient is to be included in the analysis. The analysis should be done on the basis of patient location and specimen type. The percentage susceptibility of the most frequently isolated bacteria should be presented in the antibiogram, preferably in a tabular form. The antibiogram must be printed or put up in the intranet for easy access to all clinicians. Antibiotic policy is one of the mandatory requirements for accreditation, and making an antibiogram is the first step before framing the antibiotic policy. The future of antibiograms would be the incorporation of patient related data to make information more reliable and for predicting outbreaks.
Keywords: Antibiogram, empiric antibiotic therapy, hospitals
|How to cite this article:|
Joshi S. Hospital antibiogram: A necessity. Indian J Med Microbiol 2010;28:277-80
| ~ Introduction|| |
One of the most important activities performed by a clinical microbiology laboratory is the reporting of cumulative and ongoing summaries of institutional patterns of antimicrobial susceptibilities, which are called antibiograms. This article explains how to make an antibiogram, its presentation, and its role in empiric antibiotic policy.
| ~ The Need|| |
The hospital antibiogram is a periodic summary of antimicrobial susceptibilities of local bacterial isolates submitted to the hospital's clinical microbiology laboratory. Antibiograms are often used by clinicians to assess local susceptibility rates, as an aid in selecting empiric antibiotic therapy, and in monitoring resistance trends over time within an institution. Antibiograms can also used to compare susceptibility rates across institutions and track resistance trends.
| ~ The Role of the Microbiologist|| |
The clinical microbiologist plays an important role in making of the antibiogram. The first task is the accurate daily reporting of bacterial cultures with the susceptibility results based on the latest Clinical and Laboratory Standards Institute (CLSI) guidelines. It is a good practice to educate users of the laboratory on the extended meaning of the terms Methicillin Resistant S. aureus (MRSA), Extended Spectrum Beta lactamase (ESBL), Vancomycin Resistant Enterococci (VRE), etc., and to include a note on the implications of such reporting in the results, and advise appropriate therapy and infection control precautions for the same. Then, there is the need for cumulative antibiograms capturing the susceptibility data over a period of time, say annually or six monthly. Lastly, the microbiologist plays a role in the formulation of the hospital empiric antibiotic policy, translating the cumulative antibiogram into practical applications.
| ~ The Method|| |
It seems like a daunting task to analyse all the isolates from an institution. Some hospitals have adequate support from the information technology (IT) department to be able to extract data from their reporting module. However, this may not be always possible. To simplify matters, all that is required is a onetime download of the WHONET software. WHONET is free Windows-based database software developed for the management and analysis of microbiology laboratory data, with a special focus on the analysis of antimicrobial susceptibility test results. The software  has been developed since 1989 by the WHO Collaborating Centre for Surveillance of Antimicrobial Resistance and can be freely downloaded. Once the program has been downloaded and saved, the entry of the isolates with susceptibilities is done in the program. This could be done manually which would take about a minute for each isolate. For those laboratories that already have computer systems for the recording of laboratory test results, WHONET comes with the free BacLink data conversion utility to facilitate the transfer of data from existing laboratory information systems into WHONET in order to avoid the need for double data entry. BacLink, also developed by the WHO Collaborating Centre in Boston, is included and installed as part of the standard WHONET package. In most instances, Baclink can transfer data into WHONET from common commercial database and spreadsheet software; Microsoft Excel, Access, dBase, EpiInfo, and simple text files; and commercial susceptibility test instruments.
| ~ The Guidelines|| |
Consensus guidelines have been developed by the CLSI to standardise methods used in constructing antibiograms, with the goal of promoting the reporting of reliable and consistent antibiogram data. The current guideline is CLSI M39-A3, entitled "Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data".  The salient points  of this document include the following.
- The data should be analysed annually. However, if there are a large number of isolates, this may be done six monthly or more frequently.
- At least 30 isolates should be present for inclusion in the analysis.
- The isolates that are obtained from diagnostic testing should only be included and those from surveillance cultures, e.g., MRSA screening should not be included. Colonisers should not be included.
- Include results for the antibiotics that are routinely tested.
- Only the first isolate from a patient irrespective of the specimen site should be included.
- The cumulative antibiogram should present only the percentage susceptible and not those which are intermediate susceptible.
- It is useful to stratify the antibiogram into outpatient, inpatient and ICU data.
These guidelines can be incorporated into the WHONET software and then the analysis is accordingly done. The analysis is done on the basis of patient location: whether outpatient, ICU or inpatient (non-ICU). The next parameter to be analysed is the specimen type. At least five most frequently isolated organisms from each site should be used for the final antibiogram. The percentage susceptibility to the antibiotics should be depicted separately for Gram positive and Gram negative isolates.
[Table 1] shows an example of a hypothetical cumulative antibiogram for a 6-month period for Gram negative bacilli from urine. The predominant isolate from outpatients and inpatients is Escherichia More Details coli, whereas Pseudomonas aeruginosa isolates predominate in the ICU. The ESBL rate among outpatients is approximately 40%, whereas it is almost 60% from E. coli isolated from the wards and ICU. Looking at the table, the susceptibility patterns to various antibiotic groups can also be analysed. In the above antibiogram, Enterobacteriaceae are noted to be susceptible to amikacin and fluoroquinolone resistance is seen especially among inpatients and ICU patients. Carbapenem resistance in Klebsiella pneumoniae isolates has just made an appearance in wards and ICU patients. Among the betalactam-betalactam inhibitor combinations, cefoperazone-sulbactum seems to be showing a better susceptibility than piperacillin-tazobactum. To plan an empiric therapy for UTI among outpatients based on the above table, fluoroquinolones and nitrofurantoin could be considered; and for inpatients and ICU patients, either cefoperazone-sulbactum for mild to moderate infections and carbapenems for severe infections could be considered. De-escalation of antibiotics may be done once the culture results are available.
|Table 1 :Antibiogram of Gram negative isolates from urine from January to June 2010 (hypothetical data) (numbers indicate percent susceptible) |
Click here to view
| ~ The Presentation|| |
The antibiogram must be presented in a tabular form. The percentage susceptibilities should be mentioned separately for the Gram positive and the Gram negative bacteria. Printed antibiograms should be made easily available to the clinicians and at the nursing stations. It may also be put up on the hospital intranet for easy access.
Several studies have shown that inclusion of duplicate and surveillance isolates in antibiograms affects reported susceptibility rates. When these isolates are included, the data would result in lower susceptibility rates. A study  on the impact of inclusion of duplicate isolates of Staphylococcus aureus (MRSA) from the same patient was done over a 6-year period. They found that 39% of MRSA patients had duplicate isolates as compared to 23% of MSSA. The overall hospital susceptibility rate for S. aureus was significantly affected by the higher number of duplicate isolates of MRSA. In a study in Wales,  United Kingdom, comparison of regional resistance rates from laboratories and seven hospitals was done; the difference in resistance rates between duplicate versus nonduplicate isolates was significant.
| ~ Utility of Antibiograms|| |
The antibiogram helps in monitoring antimicrobial resistance trends over different periods: ICU or ward specific data and inpatient versus outpatient data, etc. Different parts of a healthcare institution can have different patterns of antimicrobial use and resistance. Binkley et al.  compared a unit specific antibiogram versus that of the hospital wide antibiogram and found that the ICUs harboured organisms that were 5-25% more resistant than that otherwise predicted by the overall antibiogram. The impact of data stratification on the resistance rates of S. aureus, especially from blood culture, was studied in Vienna;  isolates from inpatients and OPD showed lower MRSA rates in contrast to isolates from ICU.
Antibiotic resistance trends can be monitored over periods of time. Aggregating antibiograms from specific regions would help in monitoring trends. Increased penicillin and macrolide resistance over a 3-year period was observed in a study in USA.  There is an urgent need for nationwide specific and standard operating guidelines for antibiotic reporting and surveillance studies from our country.  Analysis of antibiograms from different regions of our country would show us the trends and patterns of antimicrobial resistance.
Planning an empiric antibiotic policy in a hospital utilises subgroup specific antibiogram analysis. The recommendations on the treatment of ventilator associated pneumonia published by the American Thoracic Society and Infectious diseases Society of America endorse the use of appropriate empiric antibiotic therapy based on local microbiology results and the local antibiogram.  The hospital antibiogram cannot be used alone to select the optimal empiric therapy in an individual patient, as specific patient factors need to be considered, including the type and severity of infection, the infecting organism, and the patient's medical history and past antibiotic use.
| ~ Limitations of Antibiograms|| |
Any rises in minimum inhibitory concentration (MIC) values that occur during a given time period and that remain below the susceptible breakpoint cannot be detected (i.e., "MIC creep"). A further limitation of antibiograms is that they only capture the aggregate proportion of susceptible isolates for a given organism-antibiotic combination, and we cannot determine cross reactivities of the other antibiotics.
| ~ Outbreak Analysis|| |
Huang et al.  linked two publicly available software systems, the WHONET and SaTScan,  to retrospectively screen microbiology data for statistically significant clusters among pathogens, across wards and services. They could identify 59 clusters of multidrug resistant nosocomial pathogens which could have triggered an outbreak. In contrast, the existing infection control methods could identify only three outbreaks. There could be a role for automated real time monitoring of microbiological data to aid in controlling outbreaks.
| ~ Conclusions|| |
Antibiotic policy is one of the mandatory requirements for accreditation, and making an antibiogram is the first step before framing the antibiotic policy. The clinical microbiology laboratory plays a critical role in formulating antibiograms and providing patient specific culture and susceptibility data. The future of antibiograms would be the incorporation of patient related data to make it more reliable and informative. The antibiogram could be useful in predicting outbreaks in a healthcare institution and in monitoring trends of antimicrobial resistance.
| ~ References|| |
|1.||World Health Organisation. WHO NET5.5 Microbiology laboratory database software. Available from: http://www.who.int/drugresistance/whonetsoftware. [last accessed on 2010 Aug 10]. |
|2.||Clinical and Laboratory Standards Institute (CLSI). Analysis and presentation of cumulative antimicrobial susceptibility test data. 3rd ed. Approved guideline M39-A3. Wayne PA. CLSI, 2009. |
|3.||Hindler JF, Stelling J. Analysis and presentation of cumulative antibiograms: A new consensus guideline from the Clinical and Laboratory Standards Institute. Clin Infect Dis 2007;44:867-73. [PUBMED] [FULLTEXT] |
|4.||Horvat RT, Klutman NE, Lacy MK, Grauer D, Wilson M. Effect of duplicate isolates of methicillin- susceptible and methicillin-resistant Staphylococcus aureus on antibiogram data. J Clin Microbiol 2003;41:4611-6. [PUBMED] [FULLTEXT] |
|5.||Magee JT. Effects of duplicate and screening isolates on surveillance of community and hospital antibiotic resistance. J Antimicrob Chemother 2004;54:155-62. [PUBMED] [FULLTEXT] |
|6.||Binkley S, Fishman NO, LaRosa LA, Marr AM, Nachamkin I, Wordell D, et al. Comparison of unit-specific and hospital-wide antibiograms: potential implications for selection of empirical antimicrobial therapy. Infect Control Hosp Epidemiol 2006;27:682-7. [PUBMED] [FULLTEXT] |
|7.||Daxboeck F, Assadian O, Apfalter P, Koller W. Resistance rates of Staphylococcus aureus in relation to patient status and type of specimen. J Antimicrob Chemother 2004;54:163-7. [PUBMED] [FULLTEXT] |
|8.||Stein CR, Weber DJ, Kelley M. Using hospital antibiogram data to assess regional pneumococcal resistance to antibiotics. Emerg Infect Dis 2003;9:211-6. [PUBMED] [FULLTEXT] |
|9.||Lakshmi V. Need for national/regional guidelines and policies in India to combat antibiotic resistance. Indian J Med Microbiol 2008;26:105-7. [PUBMED] |
|10.||American Thoracic Society and the Infectious Disease Society of America. Guidelines for the management of adults with hospital-acquired, ventilator-associated, and healthcare-associated pneumonia. Am J Respir Crit Care Med 2005;171:388-416. |
|11.||Huang SS, Yokoe DS, Stelling J, Placzek H, Kulldorff M, Kleinman K, et al. Automated detection of infectious disease outbreaks in hospitals: a retrospective cohort study. PLoS Med 2010:7:e1000238. |
|12.||SatScan. Available at: http://www.satscan.org/. [last cited on 2005]. [last accessed on 2010 Aug 10]. |
|This article has been cited by|
||Antibiogram for Haemodialysis Catheter-Related Bloodstream Infections
| ||Abdul Halim Abdul Gafor,Pau Cheong Ping,Anis Farahanum Zainal Abidin,Muhammad Zulhilmie Saruddin,Ng Kah Yan,Siti Qania’ah Adam,Ramliza Ramli,Anita Sulong,Petrick Periyasamy |
| ||International Journal of Nephrology. 2014; 2014: 1 |
|[Pubmed] | [DOI]|
|| New Delhi metallo-beta-lactamase 1: Is there a need to worry
| ||Kanungo, R. |
| ||Indian Journal of Medical Microbiology. 2010; 28(4): 275-276 |