Home Care Decision Support Using an Arden Engine - Merging Smart Home and Vital Signs Data
ABSTRACT The demographic change with a rising proportion of very old people and diminishing resources leads to an intensification of the use of telemedicine and home care concepts. To provide individualized decision support, data from different sources, e.g. vital signs sensors and home environmental sensors, need to be combined and analyzed together. Furthermore, a standardized decision support approach is necessary.
The aim of our research work is to present a laboratory prototype home care architecture that integrates data from different sources and uses a decision support system based on the HL7 standard Arden Syntax for Medical Logical Modules.
Data from environmental sensors connected to a home bus system are stored in a data base along with data from wireless medical sensors. All data are analyzed using an Arden engine with the medical knowledge represented in Medical Logic Modules.
Multi-modal data from four different sensors in the home environment are stored in a single data base and are analyzed using an HL7 standard conformant decision support system.
Individualized home care decision support must be based on all data available, including context data from smart home systems and medical data from electronic health records. Our prototype implementation shows the feasibility of using an Arden engine for decision support in a home setting. Our future work will include the utilization of medical background knowledge for individualized decision support, as there is no one-size-fits-all knowledge base in medicine.
- SourceAvailable from: Matthias Gietzelt
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- "This person-centered, ubiquitous care scenario demands new forms of living and care [3,4], and along with this a new kind of information system architecture with regard to health information. This architecture must include not only the personal or home environment as a source of relevant health data, but also the caregivers and other health professionals as opposed to current institution-centric architectures [5,6]. Such systems are called 'sensor-enhanced health information systems (seHIS)' . "
ABSTRACT: Wearable sensor systems which allow for remote or self-monitoring of health-related parameters are regarded as one means to alleviate the consequences of demographic change. This paper aims to summarize current research in wearable sensors as well as in sensor-enhanced health information systems. Wearable sensor technologies are already advanced in terms of their technical capabilities and are frequently used for cardio-vascular monitoring. Epidemiologic predictions suggest that neuropsychiatric diseases will have a growing impact on our health systems and thus should be addressed more intensively. Two current project examples demonstrate the benefit of wearable sensor technologies: long-term, objective measurement under daily-life, unsupervised conditions. Finally, up-to-date approaches for the implementation of sensor-enhanced health information systems are outlined. Wearable sensors are an integral part of future pervasive, ubiquitous and person-centered health care delivery. Future challenges include their integration into sensor-enhanced health information systems and sound evaluation studies involving measures of workload reduction and costs.06/2012; 18(2):97-104. DOI:10.4258/hir.2012.18.2.97
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- "Within this context, we have developed a decision support module based on a dynamic Bayesian network that controls exercise training autonomously based on vital signs data , so that it may be used in an unsupervised training situation at home. A primary focus of our research is the integration of the DSS in existing or new health information system infrastructures, thus enabling to consider clinical context information such as diagnoses, laboratory findings or past test results as well as caregiver and patient information for the purpose of decision making . "
ABSTRACT: Demographic change with its consequences of an aging society and an increase in the demand for care in the home environment has triggered intensive research activities in sensor devices and smart home technologies. While many advanced technologies are already available, there is still a lack of decision support systems (DSS) for the interpretation of data generated in home environments. The aim of the research for this paper is to present the state-of-the-art in DSS for these data, to define characteristic properties of such systems, and to define the requirements for successful home care DSS implementations. A literature review was performed along with the analysis of cross-references. Characteristic properties are proposed and requirements are derived from the available body of literature. 79 papers were identified and analyzed, of which 20 describe implementations of decision components. Most authors mention server-based decision support components, but only few papers provide details about the system architecture or the knowledge base. A list of requirements derived from the analysis is presented. Among the primary drawbacks of current systems are the missing integration of DSS in current health information system architectures including interfaces, the missing agreement among developers with regard to the formalization and customization of medical knowledge and a lack of intelligent algorithms to interpret data from multiple sources including clinical application systems. Future research needs to address these issues in order to provide useful information - and not only large amounts of data - for both the patient and the caregiver. Furthermore, there is a need for outcome studies allowing for identifying successful implementation concepts.BMC Medical Informatics and Decision Making 05/2012; 12(1):43. DOI:10.1186/1472-6947-12-43 · 1.50 Impact Factor
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ABSTRACT: Worldwide, ageing societies are bringing challenges for independent living and health care. Health-enabling technologies for pervasive health care and sensor-enhanced health information systems offer new opportunities for care. In order to identify, implement and assess such new information and communication technologies the 'Lower Saxony Research Network Design of Environments for Ageing' (GAL) has been launched in 2008 as interdisciplinary research project. In this publication we inform about the goals and structure of GAL, including first outcomes, as well as to discuss the potentials and possible barriers of such highly interdisciplinary research projects in the field of health-enabling technologies for pervasive health care. Although GAL's high interdisciplinarity at the beginning slowed down the speed of research progress, we can now work on problems, which can hardly be solved by one or few disciplines alone. Interdisciplinary research projects on ICT in ageing societies are needed and recommended.