ABSOFT v5.0 (C) 2007 GW generates custom antibiogram by just filling in the online excel template. Hours of complex analysis is simplified to generate accurate custom reports. The method uses a database classifying the micro-organism species and the resistance mechanism to various antimicrobial agents compiling for each species and each resistance mechanism, parameters characteristic of the frequency distribution of minimum inhibitory concentrations for a group of antimicrobial agents. The present method for analyzing test results of bacteria susceptibility to antibiotics in key epidemiological niches in order to assist clinicians, microbiologists or infectious disease practitioners in formulating accurate empirical treatment. These comprehensive reports are generated within 1 day of receiving payment (200US$) / comprehensive report and the attached completed excel file. Payment can be made securely online. Custom sections can be added and analyzed.
We welcome you to this site and hope that you will have an useful time. For any clarification, please direct queries to firstname.lastname@example.org. His vision and inputs for automation of the laboratory helped us formulate this software and we are sure it will be a clinically valuable tool in your microbiology laboratory information analysis and antibiotic policies. We also would like to thank him for letting us host this tool on his microbiology site.
Our Vision is to provide service with latest state of art technology with service that remains paramount to the Clinical Laboratory.
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Antibiogram Reporting Standardization
Laboratory-based data underestimate the frequency of several major resistant organisms in patients with hospital-acquired infection or community acquired infection. Most antibiograms generated by the available systems for generation of an antibiogram do not take into consideration the following factors.
1. Test results that are done manually.
2. Location based epidemiological antibiogram (Community and Hospital acquired infections)
3. Sample based approach to an organism.
4. Most samples are not segregated when the hospital setting is a tertiary care setting.
5. It is not recommended also to collate data for the region and should be hospital specific.
6. Only 60% hospitals in the US generate an antibiogram and most of them are printouts from defined bacterial identification systems.
Antibiograms are often taken into account to define a rational selection of
an empirical antimicrobial therapy for treating patients with hospital-acquired
infections. Susceptibility data are used for making empiric antimicrobial
choices and in detecting and assessing changes in antimicrobial susceptibility
patterns. It is important that the methods used for calculating these data are
accurate, reliable, and reported in a transparent and consistent manner. To
address this matter, in 2002, the National Committee for Clinical Laboratory
Standards (NCCLS; now known as the Clinical and Laboratory Standards Institute [CLSI])
published the M39-A guidelines. These guidelines, which were updated in November
2005,[provide recommendations for the collection, analysis, and presentation of
cumulative antimicrobial susceptibility test data, including specific standards
for preparation and dissemination of an institution's antibiogram. The major aim
of the guideline is to provide recommendations for preparing the hospital
antibiogram in order to provide clinicians with useful data regarding selection
of appropriate empiric antimicrobial therapy.
Resistance rates can depend on local culture collection practices and patient hospitalization demographics. Differences in clinical laboratory procedures, which may be dependent on software capabilities. Another recommendation is to avoid reporting susceptibility data for fewer than 10 isolates of a single bacterial species (now changed to 30 isolates in the M39-A2 update) in any analysis period and to exclude surveillance cultures (e.g., rectal cultures to determine if a patient is colonized with vancomycin-resistant enterococci) in susceptibility analyses. It is further advised that susceptibility results be reported for all antimicrobials tested in accordance with CLSI guidelines for a given organism. Susceptibilities for antimicrobials that are only tested on resistant isolates or on the basis of clinician request (e.g., polymyxin B for P. aeruginosa) should not be included.
This document also provides specific recommendations for presenting antibiogram data. It calls for reporting the percentage of isolates that are susceptible versus intermediate or resistant, documenting the inclusive dates of data collection, noting whether duplicate isolates have been excluded and for which organisms they have been excluded, and indicating the total number of isolates evaluated for susceptibility for each organism tested. Another recommendation is that separate tables be prepared for certain clinically relevant gram-positive, gram-negative, and anaerobic organisms.
The guidelines recommend subgroup analyses for guiding clinicians in choosing appropriate empiric therapy for select clinical situations. These analyses might stratify susceptibility data for organisms isolated from patients in a specific location, such as a particular ward (e.g., ICU), long-term care facility, or individual hospital within a health care system; from a specific clinical service (e.g., surgery); from a specific specimen type (e.g., urine); or from a specific patient population (e.g., patients with cystic fibrosis). The guidelines recommend storing results from all isolates tested by the laboratory in a database, as this allows subset analyses while also permitting the analytical software to choose only the first isolate when compiling cumulative percentage susceptibility rates for the annual antibiogram. The recent HICPAC guidelines, "Management of Multidrug-Resistant Organisms in Healthcare Settings," recommend that antibiograms be designed to provide clinicians with information on current trends in resistance. To this end, they call for updating antibiograms at least annually. The authors note that more frequent updates may be limited in accuracy by a small number of isolates. They also call for monitoring unit-specific susceptibility data for areas such as ICUs and oncology units, and they provide recommendations for validating calculations used to prepare cumulative antibiograms.
The goal of this project is to identify the susceptibility patterns of bacterial pathogens and present this information to local health care providers as a reference tool when prescribing antimicrobial medications. Through ABSOFT v5.0 (C) 2007 GW technology, though the need to painstakingly compile and enter data by hand, the results improve infection control and patient safety strategy while reducing costs -- all critical quality-of-care initiatives pursued by leading healthcare institutions today. Avoid manually analyzing information.
About the software:
Due to the variation in data output from automated systems used for microbial
identification and susceptibility testing among laboratories , patient-based
electronic data from participating facilities are submitted in the given
text/data formats. The different microbiology data formats pose challenges for the records
aggregation required to produce a antibiogram. Specialized data extraction and
conversion programs were written to obtain data from various
semi-structured files and to arrange them into desired formats. Data of usable
formats were further processed to reconcile differences in organism and
antimicrobial naming schemes across different laboratories. On these
antibiograms we have chosen to include those antimicrobials which are
recommended by the January 2006 Performance Standards for Antimicrobial
Susceptibility Testing set forth by the Clinical and Laboratory Standards
Institute (CLSI) or those that are routinely tested.
RELIABLE ACCURATE POWERFUL SOFTWARE DRIVEN RESULT DEVELOPED BY A CERTIFIED CLINICAL MICROBIOLOGIST.
Identify current antibiogram based on location ICU, OPD, WARD.
Help fight antibiotic abuse.
Generate reliable antibiotic policies.
Identify unusual resistance patterns.
Identify emerging resistance both in the community and hospital environment.
Outsource your antibiogram.
EVERY REPORT COMES WITH (See sample below)
1. Gram positive organism.
2. Gram negative
3. Sreptococcus pneumoniae
4. Covering letter with logo.
5. Organism distribution within locations.
Add-ons: Custom built report based on 2 specific organism based on site, location, sample, period.
View sample custom generated reports.
Click on the thumbnails below to view sample reports.
Excel template Covering letter Covering letter page 2 Custom report for 2 organisms Page 1
Page 2 Page 3 Page 4 Gram positive organism
Gram negative organisms (Non fermentors) Gram negative organism (Fermentors)
Streptococcus pneumoniae Organism distribution chart
200MHz Intel Pentium processor or better
32MB or more of RAM
65,000-color or better video display card
Windows 95, Windows 98, Windows 2000, Windows 2000 ME (final release version only) or Windows NT 4.0 with Service Pack 4
IE 4.0.1 or Netscape 4.0 or later
Mac* OS 8.5 or later
64MB RAM or more
Virtual Memory turned on, set to 128MB
G3 233 (or faster) PowerPC
Browser support: Microsoft Internet Explorer 4.01 or later or Netscape 4.05 or later
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