Design of a Predictive Scheduling System to Improve Assisted Living Services for Elders

Abstract

As the number of older adults increases, and with it the demand for dedicated care, geriatric residences face a shortage of caregivers, who themselves experience work overload, stress and burden. We conducted a long-term field study in three geriatric residences to understand the work conditions of caregivers with the aim of developing technologies to assist them in their work and help them deal with their burden. From this study we obtained relevant requirements and insights of design that were used to design, implement and evaluate two prototypes for supporting caregivers' tasks (e.g. electronic recording and automatic notifications), in order to validate the feasibility of their implementation in-situ and the technical requirements. The evaluation in-situ of the prototypes was conducted for a period of four weeks. The results of the evaluation, together with the data collected from six months of use, motivated the design of a predictive schedule. Such design was iteratively improved and evaluated in participative sessions with caregivers. PRESENCE, the predictive schedule we propose, triggers real-time alerts of risky situations (e.g. falls, entering off-limits areas such as the infirmary or the kitchen) and, informs caregivers of routine tasks that need to be performed (e.g. medication administration, diaper change, etc.). Moreover, PRESENCE helps caregivers to record caring tasks (such as diaper changes or medication) and wellbeing assessments (such as the mood), which are difficult to automatize. This facilitates caregiver's shift handover, and can help to train new caregivers by suggesting routine tasks and by sending reminders and timely information about the residents. It can be seen as a tool to reduce the workload of caregivers and medical staff. Instead of trying to substitute the caregiver with an automatic caring system, as proposed by others, we propose the design of our predictive schedule system that blends caregiver's assessments and measurements from sensors. We show the feasibility of predicting caregiver's tasks and a formative evaluation with caregivers that provides preliminary evidence of its utility.

An Overview of Sensors, Design and Healthcare Challenges in Smart Homes: Future Design Questions

“…Researchers emphasize the need to focus more on end-user practices out of which healthcare data is constructed [ 114 ]. PRESENCE is one example of a personalized solution designed using a user-centered design approach [ 115 ]. Some authors also used a user-centered design approach to explore the self-annotation of smart home data [ 18 ].…”

Are Notifications a Challenge for Older People?: A Study Comparing Two Types of Notifications

“…a system that sends alerts in real time to help caregivers know about risky situations in geriatric residences [33]. Examples of these systems are systems that allow monitoring of older adults by nurses [4], alerting caregivers about the posture of elderly people (captured by a webcam) [31], and a notification framework that allows the management of several applications and alerts in an assisted living home [6].…”

Fall Detection System for the Elderly Based on the Classification of Shimmer Sensor Prototype Data

“…Rakhman et al [ 15 ] presented a prototype for a ubiquitous fall detection and alert system, uFast, which uses a smartphone. Soto-Mendoza et al [ 16 ] proposed a scheduling system for improving the lives of the elderly. Feldwieser et al [ 17 ] conducted a clinical study to detect falls and analyzed their effects and consequences with the help of a fall protocol using an accelerometer as well as optic and acoustic sensors.…”