In a home care setting, high-quality care is typically associated with continuity of care. In addition, the increasing pressure due to labor shortages calls for cost-efficient operations. This paper focuses on obtaining cost-efficient daily schedules over a longer time horizon, with balanced shift lengths, while ensuring continuity of care (using the continuity of care index). To address this challenge, we propose a novel method based on blueprint routes. This method generates daily schedules by constructing optimized shifts and routes with regard to travel time, (time window) waiting time, and shift costs based on hourly wages. To ensure continuity of care, the daily scheduling decisions are strategically guided using the concept named blueprint routes. The blueprint routes are pre-optimized (partial) routes that help to align the daily schedules to achieve continuity of care in the subsequent nurse-to-shift assignment. Model-based evolutionary algorithms are employed to overcome the NP-hardness of the routing problem and nurse-to-shift assignment. Real-life-based numerical experiments demonstrate that continuity of care does not have to compromise home care schedule costs significantly.
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Background: According to the principles of Reablement, home care services are meant to be goal-oriented, holistic and person-centred taking into account the capabilities and opportunities of older adults. However, home care services traditionally focus on doing things for older adults rather than with them. To implement Reablement in practice, the ‘Stay Active at Home’ programme was developed. It is assumed that the programme leads to a reduction in sedentary behaviour in older adults and consequently more cost-effective outcomes in terms of their health and wellbeing. However, this has yet to be proven. Methods/ design: A two-group cluster randomised controlled trial with 12 months follow-up will be conducted. Ten nursing teams will be selected, pre-stratified on working area and randomised into an intervention group (‘Stay Active at Home’) or control group (no training). All nurses of the participating teams are eligible to participate in the study. Older adults and, if applicable, their domestic support workers (DSWs) will be allocated to the intervention or control group as well, based on the allocation of the nursing team. Older adults are eligible to participate, if they: 1) receive homecare services by the selected teams; and 2) are 65 years or older. Older adults will be excluded if they: 1) are terminally ill or bedbound; 2) have serious cognitive or psychological problems; or 3) are unable to communicate in Dutch. DSWs are eligible to participate if they provide services to clients who fulfil the eligibility criteria for older adults. The study consists of an effect evaluation (primary outcome: sedentary behaviour in older adults), an economic evaluation and a process evaluation. Data for the effect and economic evaluation will be collected at baseline and 6 and/or 12 months after baseline using performance-based and self-reported measures. In addition, data from client records will be extracted. A mixed-methods design will be applied for the process evaluation, collecting data of older adults and professionals throughout the study period. Discussion: This study will result in evidence about the effectiveness, cost-effectiveness and feasibility of the ‘Stay Active at Home’ programme.
The project discussed in this paper is aimed at increasing people’s understanding of the existence and desired workings of ambient technology in the home by demonstrating its potential. For this purpose, an interactive dollhouse is presented. The dollhouse, a miniature model of a sensor-equipped home, was developed and used to engage elderly users in the design of an ambient monitoring system. This paper explains the design of the interactive dollhouse and the ways it was used as an elderly-centered design method for increasing understanding of the desired workings of ambient monitoring in the home.
Due to societal developments, like the introduction of the ‘civil society’, policy stimulating longer living at home and the separation of housing and care, the housing situation of older citizens is a relevant and pressing issue for housing-, governance- and care organizations. The current situation of living with care already benefits from technological advancement. The wide application of technology especially in care homes brings the emergence of a new source of information that becomes invaluable in order to understand how the smart urban environment affects the health of older people. The goal of this proposal is to develop an approach for designing smart neighborhoods, in order to assist and engage older adults living there. This approach will be applied to a neighborhood in Aalst-Waalre which will be developed into a living lab. The research will involve: (1) Insight into social-spatial factors underlying a smart neighborhood; (2) Identifying governance and organizational context; (3) Identifying needs and preferences of the (future) inhabitant; (4) Matching needs & preferences to potential socio-techno-spatial solutions. A mixed methods approach fusing quantitative and qualitative methods towards understanding the impacts of smart environment will be investigated. After 12 months, employing several concepts of urban computing, such as pattern recognition and predictive modelling , using the focus groups from the different organizations as well as primary end-users, and exploring how physiological data can be embedded in data-driven strategies for the enhancement of active ageing in this neighborhood will result in design solutions and strategies for a more care-friendly neighborhood.
