Jörn Kiselev

SmartSenior’s Interactive Trainer - Development of an Interactive System for a Home-Based Fall-Prevention Training for Elderly People

In this article we picture the process of development for an interactive training system for the prevention of falls for older people in the project SmartSenior. Initially, we will depict the medical background of falls, which is the basis of the user-centered design of our device. Following a thoroughly evaluation of evidenced-based therapeutic strategies and a detailed requirement analysis, an interdisciplinary team consisting of physical therapists, medical practitioners and system engineers developed a technical architecture to enable older people to train their individual functional deficits via a home based telemedical infrastructure. Furthermore, we describe the sensor technology, feedback system used for motivation and correction of the trainee and the security model for the transmission of movement data to an assisting physical therapist.

Implementation of integrated geriatric care at a German hospital: a case study to understand when and why beneficial outcomes can be achieved

BackgroundMany health systems have implemented integrated care as an alternative approach to health care delivery that is more appropriate for patients with complex, long-term needs. The objective of this article was to analyse the implementation of integrated care at a German geriatric hospital and explore whether the use of a “context-mechanisms-outcomes”-based model provides insights into when and why beneficial outcomes can be achieved.MethodsWe conducted 15 semi-structured interviews with health professionals employed at the hospital. The data were qualitatively analysed using a “context-mechanisms-outcomes”-based model. Specifically, mechanisms were defined as the different components of the integrated care intervention and categorised according to Wagner’s Chronic Care Model (CCM). Context was understood as the setting in which the mechanisms are brought into practice and described by the barriers and facilitators encountered in the implementation process. These were categorised according to the six levels of Grol and Wensing’s Implementation Model (IM): innovation, individual professional, patient, social context, organisational context and economic and political context. Outcomes were defined as the effects triggered by mechanisms and context, and categorised according to the six dimensions of quality of care as defined by the World Health Organization, namely effectiveness, efficiency, accessibility, patient-centeredness, equity and safety.ResultsThe integrated care intervention consisted of three main components: a specific reimbursement system (“early complex geriatric rehabilitation”), multidisciplinary cooperation, and comprehensive geriatric assessments. The inflexibility of the reimbursement system regarding the obligatory number of treatment sessions contributed to over-, under- and misuse of services. Multidisciplinary cooperation was impeded by a high workload, which contributed to waste in workflows. The comprehensive geriatric assessments were complemented with information provided by family members, which contributed to decreased likelihood of adverse events.ConclusionsWe recommend an increased focus on trying to understand how intervention components interact with context factors and, combined, lead to positive and/or negative outcomes.

Validation of the ambient TUG chair with light barriers and force sensors in a clinical trial

ABSTRACT To initiate appropriate interventions and avoid physical decline, comprehensive measurements are needed to detect functional changes in elderly people at the earliest possible stage. The established Timed Up&Go (TUG) test takes little time and, due to its standardized and easy procedure, can be conducted by elderly people in their own homes without clinical guidance. Therefore, cheap light barriers (LBs) and force sensors (FSs) are well suited ambient sensors that could easily be attached to existing (arm)chairs to measure and report TUG times in order to identify functional decline. We validated the sensitivity of these sensors in a clinical trial with 100 elderlies aged 58–92 years with a mean of 74 (±6.78) years by comparing the sensor-based results with standard TUG measurements using a stopwatch. We further evaluated the accuracy enhancement when calibrating the algorithm via a mixed linear model. With calibration, the LBs achieved a root mean square error (RMSE) of 0.83 s, compared to 1.90 s without, and the FSs achieved 0.90 s compared to 2.12 s without. The suitability of measuring accurate TUG times with each of the ambient sensors and of measuring TUG regularly in the homes of elderly people could be confirmed.