BioCon Valley® GmbH, the ScanBalt German liaison office, invites for a workshop on standardization of data at HEC2016, 31 August (Munich)
BioCon Valley® GmbH, the ScanBalt German liaison office, at the occasion of the international conference HEC2016 – Health Exploring Complexity – in Munich, organizes a workshop 31st August 2016 with speakers from Sweden, Denmark, Austria, Germany and Australia.
The main purpose of the workshop is to standardize key data elements in the overlapping domains of surveillance of HAI, antimicrobial resistance monitoring and antibiotic stewardship.
At the workshop experts from clinical microbiology and hygiene management will meet and discuss with IT experts in the field of standardization. Download the draft program for the workshop here.
Everyone interested is cordially invited to join the workshop. Since the workshop is part of the HEC2016 conference, workshop participants have to register for HEC2016 at least for the day of the workshop.
Time: 11:30 – 13:00
Venue: HEC2016, Ludwig-Maximilians-University, Munich, Room A014
More information on HEC2016 is available on the conference website http://www.hec2016.eu
Antimicrobial resistance (AMR), i.e., the ability of microbes such as bacteria, viruses, fungi and parasites to resist the actions of one or more antimicrobial drugs or agents, is a serious global threat.
Bacterial antibiotic resistance poses the largest threat to public health. The prevention of antimicrobial infections and their spread relies heavily on infection control management, and requires urgent, coordinated action by many stakeholders.
This is especially true for nosocomial infections, also known as healthcare-associated infections (HAIs), i.e., infections that are acquired in healthcare settings. It is known that continuous, systematic collection, analysis and interpretation of data relevant to nosocomial infections and feedback for the use by doctors and nurses can reduce the frequency of these infections.
Data from one hospital are more valid and more effective when they are compared with those from other hospitals. In order to avoid false conclusions, comparisons are only possible when identical methods of data collection with fixed diagnostic definitions are used.
The automatic aggregation of standardized data using data from electronic medical records (EMRs), lab data, surveillance data and data on antibiotic use would greatly enhance comparison and computerized decision support systems (CDSSs).
Once standardized, data can be aggregated from unit to institutional, regional, national and EU level, analysed and fed back to enhance local decision support on antibiotic use and detection of nosocomial infections.
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