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danmap 2015 20 danmap - 20 years 2. complement danmap with a timely system for
surveillance
of antimicrobial drug
resistance
. this can be done in the form of automated and electronic
surveillance
where users can access
data
on the internet and create tables and graphs. with current information and communication technology, such a system is in principle not difficult to build. it has many advantages, including the possibility of adding algorithms for outbreak detection, set- ting flags for emergence of certain drug-bug combinations, and many other tools for decision support and quality assurance. challenges emerging from limitations of the linnean taxonomy bacteria are prokaryotic microorganisms that traditionally are classified in a linnean hierarchical family tree (species, genus, family, tribe, order), as described by carl von linné. in many respects, this hierarchical system is insufficient in modern microbiology. in the context of antimicrobial
resistance
, the fact that drug
resistance
often is carried by mobile genetic elements constitutes a challenge, because these elements can be exchanged between different species and thereby do not obey hierarchical rules. for example, the same or very closely related extended spec- trum beta-lactamase genes can be found in many different gram negative species due to genetic exchange. furthermore, some of these species may have other characteristics, for example virulence traits that are also distributed across spe- cies or subtypes. moreover, with the current development in typing and classification, including the use of whole genome sequencing and a focus on a dynamic bacterial evolution with exchange of genetic elements, a
data
model based solely on the linnean system is outdated for the purpose of
surveillance
and reporting of test results. in real life, in the medical sector different departments of clinical microbiology manage this situation differently. in test reports to the requesting clinicians, some departments will give the result of an ?mrsa? in the species-field in the it system, almost as if mrsa was a bacterial species in its own right. in contrast, others prefer to answer ?growth of staphy- lococcus aureus? as the result and then make a text remark that it is an mrsa. these text remarks are rarely standardized. furthermore, the antimicrobial
resistance
pattern included in clinical microbiology reports is often restricted to include drugs relevant for treatment. the lack of a common
data
model for exchanging digital information about specific
resistance
mechanisms is one of the bottlenecks for implementing electronic
surveillance
for antimicrobial
resistance
. to develop electronic
surveillance
, we need to extend the currently used
data
model based on the linnean classification. the implementation of flexible property tables in miba broadly speaking, we define properties as characteristics of bacteria that can be measured by various methods (e.g. by de- fined genotypic and phenotypic methods) and at various levels of detail (e.g. a minimum inhibitory concentration (mic) value or an overall interpretation as ?resistant? against a drug). these can be expressed in various ways (from a gene sequence to an overall conclusion, e.g. an esbl producing organism or a multi- locus sequence typing (mlst) type). bacteria can have a very large number of properties, and the same properties can be found across the linnean family tree. joining flexible property tables to the traditional tables of microbiological findings is a solution to the limitations of the current
data
model. the new
data
model for microbiological reporting in denmark will also provide opportunities for sending other types of information along with the result produced by the clinical microbiology department, e.g. patient
data
or exposure information. from 2010, all reports from danish clinical microbiology de- partments have been stored in a national
data
base called miba. at present, only limited and unstructured
data
on antimicrobial
resistance
are stored in the
data
base, for the reasons men- tioned above. currently, miba is suitable for general microbial
surveillance
, but not for detailed
surveillance
of antimicro- bial
resistance
. however, flexible property tables have been developed and are currently being implemented [voldstedlund et al, 2014]. with a consensus about the use and content of these tables, the vision of electronic and timely antimicrobial
resistance
is getting within reach. the eres and mibalert projects in anticipation of the implementation and use of property tables, the next steps include the development of a system for amr
surveillance
. in the beginning, priority will be given to the major indicators and bacteria including mrsa, vre, esbl and cros. however, other types of
resistance
will also be included in a stepwise manner. thereby, it will be possible to describe and analyse trends and distributions of
resistance
in an interactive and timely manner, and develop tools for risk assessment and action. one example of a very specific tool for action is the mibalert project. mibalert is a tool directed toward healthcare person- nel who access a patient?s electronic health record as well as those further involved in the care and treatment of the patient. it is based on a web service using
data
from miba. the alert is generated automatically whenever the health record of a patient is accessed and can thus provide timely informa- tion about for example previous positive cultures for eg. vre, mrsa, cpe and multi-drug-resistant enterobacteriae. this will enable hospital staff to implement timely measures such as isolation of patients and will also assist in the selection of antimicrobial treatment. mibalert is currently implemented in the capital region of denmark and is expected to be implemented in other re- gions as well. experiences from the capital region show that mibalert was one of the helpful components in a bundle approach to control a vre outbreak in copenhagen. mibalert
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