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Decision support at home (DS@HOME)--system architectures and requirements
1Hanover Medical School, Peter L, Reichertz Institute for Medical Informatics, Carl-Neuberg-Str 1, Hanover 30625, Germany. Michael.Marschollek@plri.de
BMC Medical Informatics and Decision Making
|May 30, 2012
Summary
Decision support systems (DSS) are lacking for interpreting home-based sensor data in aging societies. Future research must integrate DSS into health systems and develop intelligent algorithms for better patient and caregiver support.
Area of Science:
- Gerontology and Health Informatics
- Smart Home Technology and Sensor Networks
Background:
- Aging populations and increased home care demand drive research in smart home technologies.
- Existing sensor devices and smart home technologies lack integrated decision support systems (DSS) for data interpretation.
Purpose of the Study:
- Present the state-of-the-art in DSS for home environment data.
- Define characteristic properties of home care DSS.
- Identify requirements for successful home care DSS implementation.
Main Methods:
- Conducted a literature review of 79 papers, analyzing cross-references.
- Identified and analyzed 20 papers describing decision support components.
- Derived system requirements from the literature.
Main Results:
- Most identified DSS are server-based, with limited details on architecture or knowledge bases.
- Key drawbacks include poor integration with health information systems, lack of standardized medical knowledge formalization, and insufficient intelligent algorithms.
- Identified requirements for successful DSS implementation.
Conclusions:
- Future research must focus on integrating DSS into existing health information systems and developing intelligent algorithms.
- There is a need for outcome studies to identify successful home care DSS implementation strategies.
- The goal is to transform raw data into actionable information for patients and caregivers.
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