ABSTRACT
BACKGROUND: Telecare and telehealth are important care-at-home services used to support individuals to live more independently at home. Historically, these technologies have reactively responded to issues. However, there has been a recent drive to make better use of the data from these services to facilitate more proactive and predictive care. OBJECTIVE: This review seeks to explore the ways in which predictive data analytics techniques have been applied in telecare and telehealth in at-home settings. METHODS: The PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist was adhered to alongside Arksey and O'Malley's methodological framework. English language papers published in MEDLINE, Embase, and Social Science Premium Collection between 2012 and 2022 were considered and results were screened against inclusion or exclusion criteria. RESULTS: In total, 86 papers were included in this review. The types of analytics featuring in this review can be categorized as anomaly detection (n=21), diagnosis (n=32), prediction (n=22), and activity recognition (n=11). The most common health conditions represented were Parkinson disease (n=12) and cardiovascular conditions (n=11). The main findings include: a lack of use of routinely collected data; a dominance of diagnostic tools; and barriers and opportunities that exist, such as including patient-reported outcomes, for future predictive analytics in telecare and telehealth. CONCLUSIONS: All papers in this review were small-scale pilots and, as such, future research should seek to apply these predictive techniques into larger trials. Additionally, further integration of routinely collected care data and patient-reported outcomes into predictive models in telecare and telehealth offer significant opportunities to improve the analytics being performed and should be explored further. Data sets used must be of suitable size and diversity, ensuring that models are generalizable to a wider population and can be appropriately trained, validated, and tested.
ABSTRACT
Background: Older age is associated with increased prevalence of sensory impairment and use of medicines. Objectives: To explore the daily "medicine journey" of older people with sensory impairment. Methods: The study used ethnographic-informed methods (using audio-, photo- and video-recordings, diary notes and semi-structured interviews with researchers) and involved community-dwelling adults (aged > 65) in Scotland, with visual and/or hearing impairment and using >4 medicines. Data analysis used the constant comparative method. Results: Fourteen older people with sensory impairment participated and used a mean of 11.0 (SD 5.0) medicines (range 5-22). Participants reported difficulties with medicine ordering, obtaining, storage, administration and disposal. They used elaborate strategies to manage their medicines including bespoke storage systems, fixed routines, simple aids, communication, and assistive technologies. Conclusion: Older people with sensory impairment experience substantial burden, challenges and risk with medicines management. Tailored medicine regimens and assistive technologies could provide greater support to older people with sensory impairment.