Decision support at home (DS@HOME) – system architectures and requirements

Abstract

BackgroundDemographic 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.MethodsA 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.Results79 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.ConclusionsFuture 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.

Acceptance and use of health information technology by community-dwelling elders

“…(38) However, many of these assistive technologies have not been systematically reviewed for efficacy. (15, 39)…”

Proof-of-concept trial results of the HeartMan mobile personal health system for self-management in congestive heart failure

“…Patients www.nature.com/scientificreports/ who are actively involved in their own care, and who adhere to the medication and lifestyle regimen, are known to have better prognosis 6 . So in addition to pure tele-monitoring, there is a need for mHealth systems that interpret data generated in home environments directly for the benefit of the patients, but the implementation of DSSs in the context of patient support in home environments is still limited 27 . HeartMan was designed as an advanced disease management support system for stable CHF patients to use in their home environment 11 .…”

Does multimorbitdity interfere with the fundtionality of the physically active elderly?

“…Regarding the functionality of the elderly, it can be seen that the more the elderly showed multimorbidity, the worse their functionality was. This finding shows that older people with multimorbidity have poor functionality, a deficit in their health self-care, and a greater degree of dependence for daily life activity, with negative repercussions on their functional capacity [31][32][33][34]. As the number of diseases increases, the elderly have physical, social and mental complications, and this makes their self-perceived health worse [35].…”