Situation-Aware Ambient Assisted Living and Ambient Intelligence Data Integration for Efficient Eldercare - E-Healthcare Systems and Wireless Communications - page 332

on IHE guidelines (IHE International, 2010) and
the data model on HL7 or HL7 CDA Release 2.0.
The RIM model, which CDA is based on, can be
used to develop a model for the healthcare data
and documents. This model guarantees that data
is structured in a simple and interpretable way.
A transfer of knowledge over institutional
borders as well as among different AAL services,
demands a clearly structured language. Consider-
ing nursing care, the related content differs con-
siderably worldwide (Perhab, 2007), because of
different views of the domain and special fields
of nursing care. In currently used data models for
nursing care, the varying needs of different re-
cipients are not or only partially considered.
Therefore, it is necessary to develop a semantic
model based on different data models. For nursing
care, it could, for example, describe the content
of the care summary, its semantics and interpreta-
tion to guarantee semantic interoperability. This
requires standardized structures for documents
and a common language between the mentioned
healthcare service levels. In order to define key
issues for the care summary, the semantic model
has to be developed in cooperation with experts,
favoring the use of internationally accepted and
validated standards, like interRAI (interRAI,
2010). Thus, a basis for cross-enterprise exchange
of care information is developed which provides
the basics for the integration of healthcare service
providers as well as different AAL services.
If a document is based on the data model and
the healthcare model is known, it is simple to map
the document or data to another healthcare model.
Thus, it enables a sound interpretation of the
content, comparison of different data and allows
finding contradictory or incomplete data and to
complement incomplete data. The model can also
be used to check the plausibility of various values,
if supported (Franz, Mayr, Mayr, Pfeifer, Altmann,
& Lehner, 2009). Through IHE compliance, the
models provide interoperability across healthcare
enterprises. Healthcare data can be exchanged
electronically through the data model, and the

data can efficiently be combined/integrated and
interpreted in context. Furthermore, these models
allow the easy integration of further systems and
services.
Using patient information over a long period
of time, a personalized health model can be
derived. This personalized health model allows
the simulation of the medical treatment course.
Processes can be analyzed and optimized, the
quality and accessibility of documents and their
management in the general process of mobile
and stationary nursing care can be increased and
redundancies in the existing workflow eliminated.
An applicable data model allows the representation
of collaboration networks and the processing of
adequate analyses. Details can be found in (Alt-
mann, Pfeifer, Strasser, Franz, & Mayr, 2009).
Qualitative and digital available nursing care
data enables healthcare providers to accurately
evaluate care requirements. This guarantees better
requirements planning, since one does not need
to rely only on estimates. Through continuous
electronic documentation of vital signs, precise
measures for prevention can be set. The conclu-
sions that can be drawn from the models may lead
to advantages for the health care system as well
as for AAL applications, especially in the field of
care for elderly people with need for additional
assistance.

Examples for Efficient Exchange
of Patient Care Data

Currently, several projects are conducted which
focus on the efficient exchange of patient care data.
In this section different projects are presented: (iii)
the regional project e-Care, (iii) the national project
ELGA, and (iii) the European project epSOS. The
Austrian project ELGA (Elektronische Gesund-
heitsakte) is a project from the national health
agency. Its goals are the strengthening of patient
rights through better accessibility of medical data,
the improvement of data security and availability
by building a uniform infrastructure for eHealth