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Appl Clin Inform 2025; 16(05): 1664-1676
DOI: 10.1055/a-2638-8750
Research Article

A Mixed Methods Exploration of Temporospatial Fall Alert Patterns in Australian Aged Care Settings

Autoren

  • Nida Afzal

    1   Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, NSW, Australia

  • Amy D. Nguyen

    2   Centre for Health Systems and Safety Research, Australian Institute of Health Innovation, Macquarie University, Sydney, New South Wales, Australia

  • Annie Y.S. Lau

    1   Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, NSW, Australia

Funding The research was supported by the International Macquarie Research Excellence Scholarship (iMQRES) awarded to N.A. for her PhD studies (grant no: 20224280).
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Abstract

Background

Falls among adults over 60 are a global health concern, including Australia.

Objectives

This study aimed to investigate temporospatial fall alert patterns—across time and location—detected by ambient fall detection sensors in three Australian aged care settings, to inform fall prevention strategies.

Methods

A mixed-methods approach was used to analyze fall alert patterns and fall risks. Ambient fall detection sensors collected data from three care settings (residential aged care facilities [RACFs], retirement villages [RVs], and home dwelling communities [HDCs]; n = 31 households). Quantitative analysis involved fall alerts, temporospatial analysis by time of day and location. Qualitative insights were obtained through semistructured interviews with 14 older adults and 9 caregivers to understand fall risks.

Results

Distinct fall alert patterns emerged. In RACFs, alerts were most frequently recorded in bedrooms at night, linked to physical limitations and cognitive decline. RVs showed a more even distribution of alerts throughout the day, influenced by mobility issues, social activities, and pets affecting sensor accuracy. HDCs had the lowest fall alert rates, with nighttime alerts mainly in bedrooms, reflecting residents' physical status and strong family support. Qualitative data underscored the effect of cognitive and physical impairments in RACFs, mobility challenges, social activities, and pet influences in RVs, and shared living arrangements in HDCs.

Conclusion

Fall alert patterns varied across RACFs, RVs, and HDCs, requiring tailored strategies. In RACFs, prevention should focus on nighttime safety with improved monitoring and bed alarms. Medication reviews are important, as many residents take medications affecting balance and cognition, increasing nighttime fall risks. In RVs, mobility programs and sensor accuracy improvements are needed to reduce false alerts from pets or daily activities. In HDCs, where alerts were fewer, more adaptable fall detection technology is needed to address the effect of shared bedrooms at night.

Keywords

consumer health informatics - geriatrics - ambient assistive technologies - remote monitoring - temporospatial analysis - fall alert patterns - fall detection sensors

Protection of Human and Animal Subjects

The study was performed in compliance with the World Medical Association Declaration of Helsinki on Ethical Principles for Medical Research Involving Human Subjects. The study received ethical approval from the Macquarie University Human Research Ethics Committee (reference number: 520221098339905).


Supplementary Material



Publikationsverlauf

Eingereicht: 16. Februar 2025

Angenommen: 17. Juni 2025

Artikel online veröffentlicht:
07. November 2025

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