Authors:
Orhan Konak
1
;
Harry Freitas Da Cruz
1
;
Marvin Thiele
1
;
David Golla
2
and
Matthieu-P. Schapranow
1
Affiliations:
1
Hasso Plattner Institute, Digital Health Center, Rudolf-Breitscheid-Str. 187, 14482 Potsdam and Germany
;
2
Data Experts GmbH, Allee der Kosmonauten 33G, 12681 Berlin and Germany
Keyword(s):
Nursing Care, Software Architecture, Decision Support, In-Memory Database.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Business Analytics
;
Cardiovascular Technologies
;
Computing and Telecommunications in Cardiology
;
Data Engineering
;
Decision Support Systems
;
Decision Support Systems, Remote Data Analysis
;
Health Engineering and Technology Applications
;
Knowledge-Based Systems
;
Symbolic Systems
Abstract:
Germany faces an increase of its elderly population and along with it the number of people reliant on nursing care is also rising. In this context, access to reliable information is key for all actors involved, be they family members or political decision makers. Currently, the country lacks a centralized platform on which such actors can access and exchange relevant information, e.g. as concerns finding a suitable facility or identifying trends on the demand for care spots. Existing solutions are based on regional data silos, which render information exchange time-consuming and error-prone. As a result, nursing care actors lack access to timely, reliable information to support strategic decision-making. In this paper, we introduce a software platform built upon an In-Memory database that meets the information and communication needs of the different user groups involved. The platform establishes the necessary framework for real-time data collection and information exchange, laying t
he foundation for deriving key performance indicators and enabling data exploration and prognoses.
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