gms | German Medical Science

MAINZ//2011: 56. GMDS-Jahrestagung und 6. DGEpi-Jahrestagung

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V.
Deutsche Gesellschaft für Epidemiologie e. V.

26. - 29.09.2011 in Mainz

Healthcare Analytics: the secret treasure hidden in splitters. State of the art of modern in memory technology in medicine – status and outlook

Meeting Abstract

Suche in Medline nach

  • Peter Langkafel - SAP AG, Berlin
  • Martin Peuker - Charite, Berlin

Mainz//2011. 56. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (gmds), 6. Jahrestagung der Deutschen Gesellschaft für Epidemiologie (DGEpi). Mainz, 26.-29.09.2011. Düsseldorf: German Medical Science GMS Publishing House; 2011. Doc11gmds471

DOI: 10.3205/11gmds471, URN: urn:nbn:de:0183-11gmds4710

Veröffentlicht: 20. September 2011

© 2011 Langkafel et al.
Dieser Artikel ist ein Open Access-Artikel und steht unter den Creative Commons Lizenzbedingungen (http://creativecommons.org/licenses/by-nc-nd/3.0/deed.de). Er darf vervielfältigt, verbreitet und öffentlich zugänglich gemacht werden, vorausgesetzt dass Autor und Quelle genannt werden.


Gliederung

Text

Predictive analytics is an advanced business intelligence tool that can help healthcare financial executives mine data resulting in high-value, actionable improvements for their insight into the operation of any healthcare provider. These number crunching helps to get predictive analytics about the hospital performance, be it financial data, human resources, medical controlling, supply chain or other business indicators .

Predictive analytic solutions can help hospitals increase revenues and improve their decision-making ability to increase revenue and staff productivity.

Performance and Integration is still a challenge in this area for hospitals: Fast real-time and reliable information are needed to manage to run a hospital the best way. To achieve this mid 2010 the Charité started to use a gear changing new technology: the so called “in memory technology” analytics.

In-memory computing leverages new technology innovation to establish a continuous real-time link between insight, foresight, and action to deliver significantly accelerated business performance. In-memory computing combines both transactions and analytics to improve existing business process. In memory computing is made possible through recent technology advances in main memory, multi-core processing, and data management. Target is to improve performance, response time and the increase massively the number of data to get an online real-time view of the business analytics.

Charite started to execute on the vision to have full transparency of

1.
Financial Data
2.
Clinical Data
3.
Research Data

Thus these information as hidden in different systems, data warehouses and silo application HANA (High performance analytics based on in memory technology) offers the chance first time in history to combine these areas. To achieve this transparency a three step roadmap was approached.

Phase 1 (Focus Quality) is the combined use of data from the clinical workstation together with the data for quality management.

Phase 2 (Focus Efficiency) is the improved and fasted finding and combination of pictures, biomarkers, lab results and other sources for clinical, epidemiologic and research purposes

Phase 3 (Focus Innovation) is to offer an integrated platform with unique content for new research questions, public health, study design and clinical performance optimization. Further perspective are to integrate external data (content) of to offer this unique technical platform for other partner in healthcare.

A life demo will be shown at the conference – including modern devices like Ipad / Iphone.

The Hasso Plattner Institute (Hasso-Plattner-Institut für Softwaresystemtechnik GmbH), or HPI, is a German information technology college, affiliated to the University of Potsdam and located in Potsdam-Babelsberg near Berlin. It was founded in 1998 and is the first, and still the only, entirely privately-funded college in Germany


References

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Bradley P, Kaplan J. Turning hospital data into dollars. Healthc Financ Manage. 2010;64(2):64-8.
2.
McCormack J. Number crunching. Predictive analytics helps Presbyterian Healthcare analyze financial data. Health Data Manag. 2010;18(3):99.
3.
Zeier A, Plattner H. In-Memory Data Management: An Inflection Point for Enterprise Applications. Springer; 2010.
4.
Ferranti JM, Langman MK, Tanaka D, McCall J, Ahmad A. Bridging the gap: leveraging business intelligence tools in support of patient safety and financial effectiveness. J Am Med Inform Assoc. 2010;17(2):136-43.
5.
World Health Organisation. World Health Report 2010. Health systems financing. The path to universal coverage.